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Arxives Research Seminars

2021/2022

2022

September, 14

12.00 h

52.323, Roc Boronat Building

 

Invited Research Seminar

David Barber is Director of the UCL Centre for Artificial Intelligence.

Lossless Compression using Deep Learning 

Abstract: Lossless compression can be achieved using entropy coding. The efficiency of the compression then relies on the quality of the distribution of the data. I'll give an introduction to the high level idea around Bits Back Coding, which gives an efficient scheme for using latent variable models and some of the work carried out in this area. When coupled with a variational deep learning model, the method gives strong performance and suggests potential future approaches for efficient lossless compression.

Biosketch: David Barber received a BA in Mathematics from Cambridge University and subsequently a PhD in Theoretical Physics (Statistical Mechanics) from Edinburgh University. He is Director of the UCL Centre for Artificial Intelligence, which aims to develop next generation AI techniques. He has broad research interests related to the application of probabilistic modelling and reasoning. David is also a Fellow of the Alan Turing Institute and the CSO of re:infer, an AI spin-out from UCL.

 

Host: Vicenç Gómez

September, 13

15.00 h - 16.00 h

Poblenou Campus Auditorium, Roc Boronat Building

 

 

 

Invited Research Seminar

Dr. Gonzalo Daniel Maso Talou is a senior research fellow at Auckland Bioengineering Institute.

An integrative view of neurovascular physiology 

Abstract: The cardiovascular system is highly regulated by the nervous system to sustain homeostasis and allostasis in our daily life. The synergistic role of these two systems allows us to gracefully change the metabolic requirements of our different tissues through a myriad of different activities without depriving our tissues of oxygen and nutrients. However, the intricated mechanisms in these adaptative and transforming responses are largely unknown. In this talk, we present the recent efforts from the Virtual Brain Research group at the Auckland Bioengineering Institute in computational modelling and image processing to unravel these phenomena in applications related to Alzheimer's disease and hypertension.

Biosketch: Gonzalo Daniel Maso Talou is a senior research fellow at Auckland Bioengineering Institute, and he is currently co-leading the Virtual Brain Research Group. He completed his undergraduate studies in Software Engineering at the National University of Central Buenos Aires in 2010 and his MSc in Scientific Computing and PhD in Computational Modelling at the National Laboratory for Scientific Computing in 2013 and 2017, respectively.  

In 2019, he founded the Advanced AI-driven Image Processing workforce as part of the Virtual Brain group activities, focusing on the automatic generation of subject-specific neurovascular models and the analysis of neurofluid dynamics. Currently, he is starting his independent research on neurodynamics modelling to describe the systemic interactions between the vascular and nervous systems. This project aims to improve the mechanistic understanding of the nervous system's control over the cardiovascular system.

 

Host: Oscar Camara

July, 8

11.00 h

55.309 Tànger Building

 

 

Invited Research Seminar

Dr. Tommaso Mansi is VP of Artificial Intelligence (AI) and Digital Health, Data Science, at Janssen R&D.

Creating transformational medicines through data science and AI 

Abstract: The past few years has seen the convergence of biology, data science and AI, which is poised to impact how novel medicines are discovered and developed. In this talk, I will present the opportunities ahead of us, and give concrete examples of how J&J Janssen R&D is harnessing the power of data and AI to create transformational medicines, faster.

Biography: Dr. Tommaso Mansi is VP of Artificial Intelligence (AI) and Digital Health, Data Science, at Janssen R&D. He holds a PhD in biomedical engineering from INRIA Sophia Antipolis, France. After graduating, Dr. Mansi worked at Siemens Healthineers, Digital Technology and Innovation, where he took roles of increasing responsibility and eventually led a team focusing on the development and translation of AI solutions for image-guided therapy and robotics. He then joined Janssen R&D, Data Science, in 2021. In his current position, Dr. Mansi focuses on the research and development of AI approaches spanning digital health, computer vision, and biology, to derive advanced insights from multimodal, biomedical data and accelerate drug discovery and development. Throughout his career, Dr. Mansi and the teams he worked with received several awards and gave multiple keynotes at international conferences. He holds 70+ granted US patents, co-edited 1 monograph and co-authored 100+ scientific publications. 

 

Host: Oscar Camara

June, 30

11.30 h

55.309 Tànger Building

 

Invited Research Seminar

Ittay Eyal. Senior Lecturer (Assistant Prof.), ECE, Technion. Associate Director, Initiative For Cryptocurrencies & Contracts.

Blockchain Incentive-Based Security 

Abstract: The security of blockchain protocols critically relies on incentive compatibility. This talk will review the basic principles of game-theoretical analysis of blockchain protocols and recent results. It will focus on a novel protocol, Colordag (link below), which achieves a strict Nash Equilibrium with high probability. 

 

Host: Vanesa Daza

June, 27

12.00 PM

55.410 Tànger Building

(https://meet.google.com/zmx-ftfn-spg)

 

Invited Research Seminar

Prof. Volkan Cevher is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University

Optimization challenges in adversarial machine learning 

Abstract: Thanks to neural networks (NNs), faster computation, and massive datasets, machine learning (ML) is under increasing pressure to provide automated solutions to even harder real-world tasks beyond human performance with ever faster response times due to potentially huge technological and societal benefits. Unsurprisingly, the NN learning formulations present a fundamental challenge to the back-end learning algorithms despite their scalability, in particular due to the existence of traps in the non-convex optimization landscape, such as saddle points, that can prevent algorithms from obtaining “good” solutions.

In this talk, we describe our recent research that has demonstrated that the non-convex optimization dogma is false by showing that scalable stochastic optimization algorithms can avoid traps and rapidly obtain locally optimal solutions. Coupled with the progress in representation learning, such as over-parameterized neural networks, such local solutions can be globally optimal.

Unfortunately, this talk will also demonstrate that the central min-max optimization problems in ML, such as generative adversarial networks (GANs), robust reinforcement learning (RL), and distributionally robust ML, contain spurious attractors that do not include any stationary points of the original learning formulation. Indeed, we will describe how algorithms are subject to a grander challenge, including unavoidable convergence failures, which could explain the stagnation in their progress despite the impressive earlier demonstrations. We will conclude with promising new preliminary results from our recent progress on some of these difficult challenges.

Bio: Volkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University. His research interests include machine learning, signal processing theory, optimization theory and methods, and information theory. Dr. Cevher is an ELLIS fellow and was the recipient of the Google Faculty Research award in 2018, the IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011. 

 

Host: Gergely Neu

May, 24

14.30 h

55.309 Tanger's Building (streaming)

 

Invited Research Seminar

Professor Alistair Young is Professor of Cardiovascular Data Analytics and AI at King’s College, London. Principal investigator of the Cardiac Atlas Project

The Shape of Heart: New Measures of Remodelling 

Abstract: This talk will discuss cardiac imaging in relation to heart failure, congenital heart disease, and biomechanics, with a focus on large scale statistical modelling of cohorts.  This involves machine learning methods for automatic detection of heart structure and function, automatic identification of regional and global heart muscle disease, quantification of phenotypes and analysis of mechanisms for functional impairment.

Bio: Alistair has developed methods for understanding heart function using MRI, atlas-based characterisation of heart disease in large populations, and evaluation of heart stiffness and contractility from non-invasive medical imaging exams. He is a founding member and past Board of Trustees member of the Society of Cardiovascular Magnetic Resonance, past Chair of the Flow and Motion Study Group of the International Society of Magnetic Resonance in Medicine, and serves on the editorial boards of several journals including Medical Image Analysis, Journal of Biomedical and Health Informatics, and GigaScience. He is Principal Investigator for the Cardiac Atlas Project, a world-wide consortium for the re-use of imaging data. This project has made cardiac imaging examinations available to the community for research into the analysis and population variation of heart disease. His work is funded by the New Zealand Health Research Council, the NZ Marsden Fund, the UK Wellcome Trust, and the USA National Institutes of Health. 

 

Host: Oscar Camara

March, 18

11.00 h

Auditorium (streaming)

 

Invited Research Seminar

Corey P. Neu, Ph.D.Donnelly Family Professor, Department of Mechanical Engineering, University of Colorado Boulder

 A view across space and scale: noninvasive imaging technology for mechanobiology

Abstract: Knowledge of the mechanics of cells and tissues in their native physiologic environment is critical to understand the conditions that must be replicated when engineering replacement biomaterials. A thorough understanding of the micromechanical environment of healthy tissue will improve the ability to quantify cellular responses to physical stimuli, track the progression of tissue damage or degeneration, and fabricate and evaluate biomimetic biomaterials. My lab is dedicated to the study of multiscale biomechanics, mechanobiology, and regeneration of soft biological tissues, with an emphasis placed on the design of tools to assess diseases of the musculoskeletal and cardiovascular systems. Here, we will present our efforts to implement novel imaging techniques, involving MRI and optical microscopy, to noninvasively describe internal patterns of strain and material properties throughout the volume of tissues and single cells. We will highlight recent achievements, including hybrid methods to characterize deformation in tissues, in addition to challenges for single cell measures in vivo. Preliminary biomechanical data in musculoskeletal and cardiac tissues and single cells, with direct implications for mechanobiology and regeneration, will be presented.

 

Bio: D Dr. Corey Neu received his Sc.B. in mechanical engineering and Sc.M. in biomedical engineering from Brown University in Providence, Rhode Island. He completed his Ph.D. in biomedical engineering in 2004 at the University of California at Davis. He was a postdoctoral scientist with A. Hari Reddi in the Center for Regeneration and Repair at UC Davis Medical Center, and was co-advised by Kyriakos Komvopoulos in mechanical engineering at the University of California at Berkeley, from 2004 to 2007. He was an assistant adjunct professor of orthopedic surgery at the University of California at Davis until 2008, and assistant and associate professor in the Weldon School of Biomedical Engineering at Purdue University in West Lafayette, Indiana. He is now the Donnelly Family Endowed Associate Professor of Mechanical Engineering at the University of Colorado Boulder. He also serves as Founding Graduate Chair of the Program in Biomedical Engineering (on sabbatical until summer, 2022), and is a Member of the BioFrontiers Institute.

 

Host: Jérôme Noally

2020/2021

2021

February,18

16.30

Link

Invited Research Seminar - This seminar has been cancelled

By Balder ten Cate 

Database queries, schema mappings, and data examples

Abstract:

In this talk I will give an overview of work that I have done around example-driven approaches to the specification of database queries and schema  mappings. Using techniques from logic and finite model theory, computational learning theory, and the theory of constraint satisfaction problems, my collaborators and I were able to develop algorithmic solutions and systems for various tasks such as generating uniquely-characterizing examples from specifications and learning specifications from examples; as well as identify  boundaries of efficient computability. In the process, we established some  deep connections with work in other areas of logic and computer science. I will also briefly review some other work I have done in the broader area of logic, data management, and knowledge representation.

Host: Victor Dalmau

February, 15

14:30

Link

Invited Research Seminar - This seminar has been cancelled

By Laura Ines Furlong

Enabling precision medicine by translational bioinformatics

Abstract: 

Genomics is transforming health care and drug development. During the last 25 years, we have witnessed an unprecedented progress in the discovery of genetic variation associated with diseases thanks to the advent of high-throughput sequencing technologies. This has opened the possibility of using this information to improve disease diagnosis, to develop new treatments or to predict the individual susceptibility to diseases. Despite these progresses, some challenges hamper the exploitation of genomic data and translating it into clinically actionable information. I will briefly present those challenges and how we are addressing them from the perspective of systems medicine and big data analytics, with different applications such as variant interpretation, patient stratification, and nomination of candidate drug targets.

Host: Jérôme Noailly

February, 12

16:00h

Link

PhD Seminar
 
By Ricardo Baeza-Yates  following the previous FATE series 
 
Ethics in AI: A Challenging Task 
 
Abstract:

In the first part we cover current specific challenges: (1) discrimination (e.g., facial recognition, justice, sharing economy, language models); (2) phrenology (e.g., biometric based predictions); (3) unfair digital commerce (e.g., exposure and popularity bias, antitrust); and (4) non-rational stock market (e.g., Signal and Gamestop) . These examples do have a personal bias but set the context for the second part where we address three generic challenges: (1) cultural differences (e.g., Christian vs. Muslim); (2) legal issues (e.g., privacy, regulation) and (3) too many principles (e.g., principles vs. techniques).
 

Registration is needed using this form

February, 8

14.30 h

Link 

Invited Research Seminar

By Gergely Neu

Scaling up Reinforcement Learning with Guarantees                    

Abstract:

Recent years saw a massive surge of interest in a subfield of machine learning called reinforcement learning (RL). Reinforcement learning models the interaction between a learning agent and a dynamically changing environment, aiming to develop efficient algorithms for the agent to identify good strategies that maximize long-term performance metrics specified in terms of a reward function. While RL techniques have contributed to several recent breakthroughs of artificial intelligence, these techniques are far from being deployable in real-world scenarios, particularly due to their lack of performance guarantees. Accordingly, there has been a lot of recent interest in developing RL algorithms with provable performance guarantees. This talk summarizes my contributions to this movement. 

Host:  Anders Jonsson

2019/2020

2020

April, 21

15.30

55.309

Invited Research Seminar

By Jorg Fachner

TBA

Bio:

Dr. Fachner, since 2013 Professor for Music, Health and the Brain at Anglia Ruskin University in Cambridge, UK, is interested in translational issues of interdisciplinary research topics between medicine, humanities and music sciences. Starting in Germany 20 years ago, he has been working as a professional in the field of Music Therapy (MT) and brain research, was and is active in EU and Academy of Finland MT research projects and serves on international MT advisory and policy boards. Studying Music Therapy processes, brain responses and treatment of depression, as well as consciousness states and time perception, his scientific output comprises over 100 publications in journals and books across disciplines. Recent projects, collaborations and publications focus on biomarkers, neurodynamics, timing and kairological principles of the MT process and effectiveness.

March, 26

15.30

55.309

PhD Research Seminar

By Simone Tassani

Statistical course and Design of Experiments - course composed on 6  2-hour sessions

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.
Material from last edition available at
https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments

Bio:

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

March, 19

15.30

55.309

PhD Research Seminar

By Simone Tassani

Statistical course and Design of Experiments - course composed on 6  2-hour sessions

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.
Material from last edition available at
https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments

Bio:

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

March, 19

12.00

55.309

Invited Research Seminar

By Petri Toiviainen, Finnish Centre for Interdisciplinary Music Research, University of Jyväskylä

fMRI meets MIR: studying neural correlates of music listening with a naturalistic paradigm

Abstract:

The past two decades have witnessed a surge of neuroimaging studies that have attempted at identify brain structures involved in the perception of music-related perceptual features, such as pitch, sensory dissonance, rhythm, timbre, and key, typically in controlled conditions wherein the feature of interest has been presented in isolation and manipulated artificially. Such studies have inspected phenomena relatively distinct from the actual music listening situation where listeners continuously and subconsciously extract several musical features that are changing and integrate them into coherent percepts. 

To alleviate this shortcoming, our team has introduced and employed a naturalistic paradigm, wherein neural correlates of music processing are investigated using brain imaging data collected during continuous listening of music recordings and modelled using features computationally extracted from the presented music. I will give an overview of this work, including approaches of both encoding neural activation from music and decoding musical content and listener characteristics from neural activation.

I will also present our ongoing work in which we aim to switch from feature engineering to feature learning in order to model the neural correlates of implicit music learning and enculturation. To this end, we will employ unsupervised deep neural networks to learn style-specific musical features at a range of abstraction levels and compare the thus learned representations with neural representations to investigate how music is processed in the brain at different hierarchical levels and how this depends on previous musical exposure.

Host: Xavier Serra Casals

March, 12

14.00 h 

55.309

PhD Research Seminar

By Simone Tassani

Statistical course and Design of Experiments - course composed on 6  2-hour sessions

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.
Material from last edition available at
https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments

Bio:

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

March, 5

15.30 h 

55.309

PhD Research Seminar

By Simone Tassani

Statistical course and Design of Experiments - course composed on 6  2-hour sessions

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.
Material from last edition available at
https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments

Bio:

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

March, 5

15.30 h 

55.309

Invited Research Seminar

By David Barber (author of the book "Bayesian Reasoning and
Machine Learning")

Spread divergences

Abstract:

For distributions p and q with different support, the divergence D(p||q) may not exist. We define a spread divergence on modified p and q and describe sufficient conditions for the existence of
such a divergence. We give examples of using a spread divergence to train implicit generative models, including linear models (Independent Components Analysis) and non-linear models (Deep Generative Networks).
We also show how a general privacy preserving machine learning mechanism results as a natural application of the spread divergence.

Bio:

David Barber is the Director of the recently created UCL Centre
for Artificial Intelligence, which aims to develop next generation AI
techniques. He has broad research interests related to the application of probabilistic modelling and reasoning. David is also a Fellow of the Alan Turing Institute and the CSO of re:infer, an AI spin-out from UCL.

March, 3

15.30 h 

55.309

PhD Research Seminar

By Simone Tassani

Statistical course and Design of Experiments - course composed on 6  2-hour sessions

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.
Material from last edition available at
https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments

Bio:

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

February, 27

15.30 h 

55.309

PhD Research Seminar

By Simone Tassani

Statistical course and Design of Experiments - course composed on 6  2-hour sessions

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.
Material from last edition available at: https://www.upf.edu/web/mdm-dtic/course-statistics-and-design-of-experiments

Bio:

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

February, 20

15.30 h 

55.309

PhD Research Seminar

By Alastair Porter

Software development best practices for research reproduceability

Abstract:

In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups. A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time. For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time. In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available.

Bio:

I'm a developer in the Music Technology Group at the Universitat Pompeu Fabra in Barcelona, Spain. I specialise in developing bespoke software in collaboration with academic researchers to help complete and promote their research, and providing technical and development support to the department. I received my MA at McGill University working in the Distributed Digital Music Archives and Libraries lab

February, 17

15.30 h 

55.309

Invited Research Seminar

By Rafael Caro Repetto, Institute of Ethnomusicology, Kunstuniversität Graz, Austria.

Technology for aiding understanding of music cultures: The Musical Bridges project

Abstract:

We live in an increasingly connected world. People, objects, customs, behaviors, ideas, and also sounds, travel with ever growing speed and scope. As a result, multiculturality is an unavoidable condition of contemporary societies. However, the cohabitation in a particular local community of elements from external origins do not necessarily imply their mutual understanding, and even acceptance. In this project we aim at using technology for building Musical Bridges between cultures. A musical tradition is deeply rooted in the thought systems, religious ideas, aesthetic principles, social structures and economic trends of the communities that developed it. Therefore, unraveling the elements of a musical system can aid the understanding of its originating culture. Furthermore, being able to experience them in musical performance allows the embodiment of their underlying cultural phenomena. Existing materials for approaching alien musical cultures are mostly addressed to students or scholars, and in their vast majority consist in written explanations illustrated with accompanying audio or video recordings. Thus, a gap remains between aural perception and intellectual comprehension, generally only addressed via music scores. In Musical Bridges we design interactive, online tools which offer as intuitive as possible visualizations of selected musical aspects from audio recordings with the aim of guiding the user’s listening attention, and her/his bodily engagement with the listening experience. To this aim, we draw on the audio recordings corpora gathered in the previous CompMusic project for the computational study of North Indian and South Indian classical music, Turkish makam music, Chinese jingju music and Moroccan Andalusian music. The visualizations offered by the Musical Bridges tools, tailored to the specific characteristics of each of these music traditions, are based on automatically extracted features using audio signal processing methods, as well as manual annotations by experts. Adopting an approach that could be framed as applied computational musicology, the Musical Bridges project also organizes public educational activities to put these tools, and the project’s philosophy, in action, and bring these music traditions, and their corresponding cultures, closer to the Barcelona audience. In this presentation, I report about, and demonstrate, the current state of the research carried out in the Musical Bridges project.

Bio:

Rafael Caro Repetto is an ethnomusicologist specialized in Chinese traditional music. After several years of research in Beijing and Shanghai, he obtained a master’s degree in ethnomusicology at Soas (University of London). In 2013 he joined the CompMusic project at the Music Technology Group from Universitat Pompeu Fabra, focusing on jingju music research. In 2018 he received his Ph.D. degree with a thesis on computer aided analysis of the jingju’s melodic system. Currently, Rafael Caro is a senior scientist at the Institute of Ethnomusicology from Kunstuniversität Graz (Austria), and member of the Musical Bridges project, extending his research scope to Indian classical music and Moroccan Andalusian music.

Host: Xavier Serra

February, 17

11.00 h 

55.309

Invited Research Seminar

By Dr. Mehran Ebrahimi, Ontario Tech University, Canada

Inverse Problems in Image Processing

Abstract:

In many practical problems in the field of applied sciences, the features of most interest cannot be observed directly, but have to be inferred from other, observable quantities. The problem of solving an unknown object from the observed quantities is called an inverse problem. Many classical problems in imaging can be modelled as inverse problems. Many real-world inverse problems are ill-posed, mainly due to the lack of existence of a unique solution. The procedure of providing an acceptable unique solution to such problems is known as regularization. Indeed, much of the progress in image processing in the past few decades has been due to advances in the formulation and practice of regularization. This, coupled with the progress in the areas of optimization and numerical analysis, has yielded much improvement in computational methods of solving inverse imaging problems.

In this talk, we will revisit a number of inverse problems including image registration (alignment), image inpainting (completion), super-resolution (resolution enhancement), and present some recent research ideas mainly aimed at medical imaging applications. Furthermore, we present an approach based on deep convolutional neural networks to address two image restoration problems, image inpainting and super-resolution. The method applies our so-called “Edge-Connect”, a two-stage adversarial model that contains an edge generator followed by an image completion network. We evaluate the model and observe that it outperforms current state-of-the-art techniques quantitatively and qualitatively.

Bio:

Dr. Mehran Ebrahimi is an Associate Professor in the Faculty of Science at Ontario Tech University in Canada, where he is directing the Imaging Lab. He received his PhD in Applied Mathematics in the area of inverse problems in imaging from the University of Waterloo, Canada, in 2008. He was an NSERC postdoctoral fellow at Sunnybrook Hospital and Dept. of Medical Biophysics at the University of Toronto during 2008-2012. Since 2013, he has been a faculty member of Modelling and Computational Science at Ontario Tech. His research interests include medical image analysis, inverse problems, computer-assisted surgery and computer vision.

Host: Miguel Ángel González Ballester

February, 13

15.30 h 

55.309

PhD Research Seminar

By Marianna Nadeu (CIREP) and Marc Vives (UPF Data Protection Officer)

Introduction to ethical issues in research

Abstract:

The Institutional Committee for Ethical Review of Projects wants to contribute to the improvement of ethics and personal data protection standards in research activities and academic practices related to human beings within the UPF community. Among other tasks, CIREP is in charge of evaluating research projects subject to ethics review and giving its approval by issuing binding reports. In this talk we will introduce basic research ethics principles that researchers need to take into account when designing and conducting their research projects. We will also review key concepts related to the European General Data Protection Regulation that regulates the processing of personal data. The ethical review process (from application to approval) will also be discussed.

February, 7

15.30 h 

55.309

Invited Research Seminar
 
By Barış Bozkurt, Electrical Engineering at Izmir Democracy University, Turkey
 
Automatic assessment for student music performances

Abstract:
 
Online learning has impacted and changed music education significantly all over the world in the last decade. One of the biggest challenges in online music education, such as mobile apps or online courses, is the assessment of the learner performances to create meaningful feedback for the learner. This talk will review various approaches to perform automatic assessment in various context (singing melodies, performing rhythmic patterns, playing chords on guitar, etc.) and discuss challenges involved in this domain of research as well as future directions.
 
Biography:
 
Barış Bozkurt is a Prof. of Electrical Engineering at Izmir Democracy University, Turkey. He is a collaborator of the Music Technology Group (MTG) at the Universitat Pompeu Fabra in Barcelona since 2011 and has taken part in recent studies in MTG on automatic assessment of music performances. He has obtained his PhD degree (on speech analysis) in 2005 from Faculte Polytechnique De Mons, Belgium and also worked in speech industry after his PhD. Since 2007, he has been teaching in Electrical Engineering and Computer Science departments, and carrying research in the fields of audio signal processing and computational musicology.
 
Host: Xavier Serra

February, 6

15.00 h 

55.309

PhD Research Seminar

By Laura Díaz,  Scientists Dating Forum (SciDF)

Creating an elevator pitch

January, 31

16.10 h 

55.003

PhD Research Seminar  
 
By Solon Barocas (Cornell University / Microsoft Research)
 
Privacy Dependencies
 
Abstract:
 

This seminar offers a comprehensive survey of privacy dependencies—the many ways that our privacy depends on the decisions and disclosures of other people. What we do and what we say can reveal as much about others as it does about ourselves, even when we don’t realize it or when we think we’re sharing information about ourselves alone.

We identify three bases upon which our privacy can depend: our social ties, our similarities to others, and our differences from others. In a tie-based dependency, an observer learns about one person by virtue of her social relationships with others—family, friends, or other associates. In a similarity-based dependency, inferences about our unrevealed attributes are drawn from our similarities to others for whom that attribute is known. And in difference-based dependencies, revelations about ourselves demonstrate how we are different from others—by showing, for example, how we “break the mold” of normal behavior or establishing how we rank relative to others with respect to some desirable attribute. 

We elaborate how these dependencies operate, isolating the relevant mechanisms and providing concrete examples of each mechanism in practice, the values they implicate, and the legal and technical interventions that may be brought to bear on them. Our work adds to a growing chorus demonstrating that privacy is neither an individual choice nor an individual value—but it is the first to systematically demonstrate how different types of dependencies can raise very different normative concerns, implicate different areas of law, and create different challenges for regulation.

Reference: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3447384

Bio:

Solon Barocas is a Principal Researcher in the New York City lab of Microsoft Research and an Assistant Professor in the Department of Information Science at Cornell University. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University.

His research explores ethical and policy issues in artificial intelligence, particularly fairness in machine learning, methods for bringing accountability to automated decision-making, and the privacy implications of inference.

He co-founded the annual workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) and later established the ACM conference on Fairness, Accountability, and Transparency (FAT*).

He was previously a Postdoctoral Researcher at Microsoft Research as well as a Postdoctoral Research Associate at the Center for Information Technology Policy at Princeton University. He completed his doctorate at New York University, where he remains a Visiting Scholar at the Center for Urban Science + Progress.

January, 31

15.00 h 

55.003

PhD Research Seminar - 
 
By Asia J. Biega (Microsoft Research)
 

Wanted and Unwanted Exposure: Designing Ethically and Socially Responsible Information Systems

Abstract:

Information systems have the potential to enhance or limit opportunities when ranking people and products in systems such as job portals or two-sided economy platforms. They also have the potential to violate privacy by accumulating queries into detailed searcher profiles or returning ranked subjects as answers to sensitive queries. This talk will cover various measures and mechanisms for mitigating the aforementioned threats to fairness and privacy. In particular, I’m going to focus on the dual nature of ranking exposure and argue that platforms need to develop fairness mechanisms in cases where exposure is wanted, as well as privacy awareness mechanisms in cases where exposure is unwanted.

Bio:

Asia J. Biega is a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) Group at Microsoft Research Montréal. A common theme in her research is that of protecting user rights and well-being. She design ethically and socially responsible information and social computing systems and study how they interact with and influence their users.

Her background is in information retrieval, information extraction, and data mining. She completed her PhD summa cum laude at the Max Planck Institute for Informatics and Saarland University advised by Gerhard Weikum and Krishna P. Gummadi. During that time, she was also a member of the Max Planck Institute for Software Systems. Her doctoral work focused on the issues of privacy and fairness in search systems. She hold a B.Sc. and an M.Sc. in Computer Science from the University of Wrocław, Poland. Outside of academia, she worked as an engineering intern in the privacy infrastructure team at Google and as a software developer in e-commerce.

January, 30

15.30 h 

55.003

PhD Research Seminar 

By Ryan Armstrong

PhD Well-being & Systems thinking

Getting your PhD but keeping your sanity. A workshop:

Abstract:

Recent studies suggest that PhD students suffer a mental health issues at alarming levels—around six times the level of the general population—issues which impact not only productivity and program outcomes but also the long-term well-being of the developing researcher. Research centers have begun to address the issue, but it resists a simple policy solution. Indeed, the issue of mental health and well-being in PhD programs has the characteristics of a “wicked problem”. For example, it lacks a definitive solution, every problem is unique, it can be explained in a number of ways, and it tightly intertwined with a number of interconnected systems, also experiencing issues. In light of these challenges, this workshop takes a collaborative, action-oriented approachto generate awareness and empower PhD students. Based on methods developed in psychology, organizational studies, and design thinking, it provides a means of understanding and addressing the challenges PhD students face in a way that allows for the variety of forms these are likely to take. Participants will gain increased awareness of the complexity of the issue and propose their own solution in a hands-on, supportive setting.

Bio:

Ryan Armstrong is a researcher in the field of management and organizations. His research interests lie in exploring how to promote learning and well-being at work. He has published and presented on the topics of organizational learning, systems thinking, applied philosophy, and interdisciplinarity. His latest research project is on using skills training for emotional regulation as a means of promoting adaptation, lowering defensiveness, and increasing well-being in the workplace. Ryan is currently working as an advisor and facilitator for organizations struggling with complex issues, and he is also an adjunct professor at the University of Barcelona in the topics of Operations Management and Organizational Behavior. Since July 2018 he has served as Treasurer for Scientists Dating Forum.

January, 23

15.30 h 

55.309

PhD Research Seminar -  REGISTRATION is needed here

By Ryan Amstrong and Carla Conejo

Science Dating Forum

The Scientists Dating Forum (SciDF) will present to the community in DTIC their approach to promote that researchers are more actively involved in society. We first got to know SciDF during the Falling Walls Lab qualifying round we co-organised in 2017, and their interests to impact on a broad number of topics, ranging from general outreach to science diplomacy, are quite well aligned with several of the priorities of the María de Maeztu transversal actions, that include opening up scientific work and setting the means that guarantee that excellent science also results in positive impacts in society.
 
Bio:
 
Ryan Armstrong is a researcher in the field of management and organizations. His research interests lie in exploring how to promote learning and well-being at work. He has published and presented on the topics of organizational learning, systems thinking, applied philosophy, and interdisciplinarity. His latest research project is on using skills training for emotional regulation as a means of promoting adaptation, lowering defensiveness, and increasing well-being in the workplace. Ryan is currently working as an advisor and facilitator for organizations struggling with complex issues, and he is also an adjunct professor at the University of Barcelona in the topics of Operations Management and Organizational Behavior. Since July 2018 he has served as Treasurer for Scientists Dating Forum.
 
Carla Conejo González is the Vice-president of Scientist Dating Forum. She works at Fundació Catalunya La Pedrera, where she is the Science Projects Leader of the Area of Knowledge, Education & Research. BS in Human Biology and MS in Pharmaceutical and Biotechnological Industry at Universitat Pompeu Fabra with a degree specialization in neurobiology and research internships in the Center for Genomic Regulation in Barcelona and in the Dipartamento di Scienze Biomediche e Neuromotorie at the Università di Bologna in Italy. Scientific advisor, content researcher and creator of the TV program Quèquicom of the Canal33 (TV3). In the field of science advocacy, she is also a board member of WhatIf – Passionately Courious and has volunteered at MAGMA – Association for Promoting Youth Research, both initiatives aimed at promoting science education and dissemination by connecting science to society and facilitating access to research. Carla is also one of the founders of Associació Babu, a non-governmental humanitarian organization aimed at developing programs of health and psychological assistance worldwide

January, 16

15.30 h 

55.410

 

PhD Research Seminar

Experiences after PhD. Some career paths in academia, industry and social organisations 

In this seminar five senior researchers will share their experiences and learnings since PhD, showing different successful career paths.
 
- Alberto Betella. DTIC-UPF PhD alumni. Chief Technology Officer, Health Moonshot, Telefonica Alpha
- Judith Chamorro Servent. MSCA-IF Fellow at BCN MedTech, DTIC-UPF.
- Giovanni Geraci. Assistant Professor and Junior Leader Fellow in the Wireless Communications Research Group, DTIC-UPF
- Goretti Mallorquí Fernández. Head of Core Facilities. IRB Barcelona.
- Alp Öktem. DTIC-UPF PhD alumni. Co-founder of Col·lectivaT SCCL and Computational linguist at Translators without Borders
2019  
DECEMBER  

December, 17

11.00 h 

55.309

Invited Research Seminar

By Franz Zotter

Beamforming with compact spherical loudspeaker arrays

Abstract:
 
The lecture addresses beamforming with compact spherical loudspeaker arrays such as louspeaker cubes and the icosahedral loudspeaker (20 transducers, 3rd order), and what we perceive when shooting beams of sound into the surrounding room. There are several other prototypes built in Graz (loudspeaker cubes), whose measurements are available online for own experimentation. Some of the basics are already in the 2019 book on Ambisonics, and newer developments cover the actually quite simple electroacoustic model, as well as how new mixed-order prototypes work. Their spherical enclosure is cost-efficiently 3D printed, providing affordable rehearsal instruments for electroacoustic music.
 
Bio:
 
Franz Zotter's background is acoustics and signal processing. He received his diploma in audio engineering in 2004 (speech enhancement, TU Graz) and was awarded a doctoral degree in 2009 by the University of Music and Performing Arts, Graz, and the Lothar-Cremer medal by the German acoustical society (DEGA) in 2012, with works on spherical arrays for sound radiation analysis and synthesis, and Ambisonics. He works at the Institute of Electronic Music and Acoustics in Graz and chairs the German Acoustical Society (DEGA) TC on virtual acoustics. Franz Zotter is one of the world leading researchers in spatial audio in general and Ambisonics in particular, having written more than 100 papers in the subject, many of them highly cited. 
 
Host: Frederic Font, Music Technology Group

December, 12

15.30 h 

55.309

By Irene Torres and Adrián Ponce 

Gender and Science: the importance of intersectional feminism in academia

Abstract:
 
Women in Science, Technology, Engineering and Mathematics (STEM) fields remain severely underrepresented. For instance, in Spain, women represent about 15% of full (catedras) professorships. Moreover, women are judged to be less competent, receive less payment and research facilities, and are less likely to be awarded research grants compared with male scientists. The different mechanisms leading to this disparity have been investigated and more is brought to light by ongoing research. In this talk we will explain the different challenges faced by women in STEM careers, the reasons and the mechanisms through which they emerge, and changes (big and small) that we can all do to improve the current dire scenario. We will also show how gender, race, class, and sexual identity discriminations are entangled and contribute to leaving out minorities from academia.
 

Supplementary information on gender issues in research:

- UPF equity plan https://www.upf.edu/web/pla-igualtat/eixos
- Gendered Innovation Checklist. Set of key questions for incorporating sex and gender analyses into engineering http://genderedinnovations.stanford.edu/methods/engineering_checklist.html
- DTIC-UPF María de Maeztu Gender and ICT program https://www.upf.edu/web/mdm-dtic/gender-and-ict
NOVEMBER  

November, 28

17.00 h 

51.100

Invited Research Seminar

By Mar Pérez-Sanagustín

How do we learn? Key results on the study of self-regulated learning strategies

Abstract:

We are living a time of continuous change. In an increasingly globalized world, changing jobs, and even country is part of the daily life of many people. Today, working in interdisciplinary groups and in a variety of contexts, from online to face to face, is very common. Given these circumstances, today's workers need to continually learn, individually and in groups, and be flexible in order to adapt successfully to change. In this context, learning to learn is key, and having the skills that allow us to plan, organize and control our learning goals are necessary to be successful. That is, having the ability to self-regulate our own learning. But, how do we learn to learn? What are the strategies and skills that make us become actual continuous learners? In this talk, I will present what we have learned at the Technology for Digital Learning Lab (T4D Lab) about the characteristics that define self-regulated learners and their behavioral patterns in online learning environments. I will introduce some of the experiments we conducted, the analytical methods we employed to extract behavioral patterns and the results of a set of interventions we conducted for supporting self-regulated learning strategies. The results and methods presented rise new questions on how to advance the Learning Analytics field for better understanding complex learning behaviors and what are the implications for the design of learning environments of the future.

Bio:

Mar Pérez-Sanagustín  is  Associate Professor at the Université Paul Sabatier Toulouse III (France), researcher at the Institute de Recherche Informatique de Toulouse (IRIT), and associate researcher at the Pontificia Universidad Católica de Chile (PUC). Mar also founded the team T4DLab at PUC, and she continuous collaborating with it. Mar worked from 2011 until 2014 as a researcher at the Gradient Lab of the Gradient del Grupo de Aplicaciones y Servicios Telemáticos (GAST) at the Universidad Carlos III de Madrid (UC3M) and as a teacher of the department of Telematics Engineering, where she was with a Post-Doctoral Fellow Alianza 4 Universidades. She is a Doctor in Information and Communication Technologies since July 2011 by the University Pompeu Fabra, where she obtained the cum laude grade with European Mention. During her PhD, Mar completed her studies with a moths stage at the LTRI group from the London Metropolitan University in London.  From November 2013 until March 2014 Mar was with a Fulbright fellow visiting the Stanford Research Institute (SRI) in San Francisco (USA). From 2014 until September 2018 she worked as an Associate Professor at the Pontificia Universidad Católica de Chile where she also was the vice-dean of Engineering Education. Currently, she is still associate researcher at this university. Her research focuses on the study of self-regulation in MOOCs, MOOC-based hybrid methodologies, collaborative learning with mobile devices and engineering education.

Host: Davinia Hernández-Leo

November, 28

15.30 h 

55.309

PhD Research Seminar

Previous experience from recent / current PhD Students

In this seminar four PhD students of the department (two having defended their thesis this term, and two in their second year) will share their experiences and learnings.

- Cecilia Nunes. Thesis “Towards the improvement of decision tree learning: a perspective on search and evaluation” defended in October 2019, co-supervised in the research groups Physense and AI & Machine Learning, as well as in Philips France, will make a summary of what she learnt during PhD.
 
- Indre Pileckyte is in her second PhD year at the Mutisensory Research Group and will explain how she is approaching the development of competences and skills, inspired by the Researcher Development Framework
 
- Pablo Aragón. Thesis “Characterising online participation in civic technologies” defended in November 2019 in the AI and Machine Learning research group. He will focus on how his active outreach activities supported the success of his research
 
- Valerio Lorini. Second year PhD student working on Social Media for Disaster Risk Management at the Joint Research Center of the EC at Ispra, supervised at DTIC in the Web Science and Social Computing Research. He will share the way he organises his research, taking especially into account that he is based in Italy.

November, 22

16.00 h 

55.309

Invited Research Seminar

By Robert West, Director of the Data Science lab at EPFL. School of Computer and Communication Science, Switzerland

Message Distortion in Information Cascades

Abstract:

Information diffusion is usually modeled as a process in which immutable pieces of information propagate over a network. In reality, however, messages are not immutable, but may be morphed with every step, potentially entailing large cumulative distortions. This process may lead to misinformation even in the absence of malevolent actors, and understanding it is crucial for modeling and improving online information systems. Here, we perform a controlled, crowdsourced experiment in which we simulate the propagation of information from medical research papers. Starting from the original abstracts, crowd workers iteratively shorten previously produced summaries to increasingly smaller lengths. We also collect control summaries where the original abstract is compressed directly to the final target length. Comparing cascades to controls allows us to separate the effect of the length constraint from that of accumulated distortion. Via careful manual coding, we  annotate lexical and semantic units in the medical abstracts and track them along cascades. We find that iterative summarization  has a negative impact due to the accumulation of error, but that high-quality intermediate summaries result in less distorted messages than in the control case. Different types of information behave differently; in particular, the conclusion of a medical abstract (i.e.,  its key message) is distorted most. Finally, we compare abstractive with extractive summaries, finding that the latter are less prone to semantic distortion. Overall, this work is a first step in studying  information cascades without the assumption that disseminated content is immutable, with implications on our understanding of the role of word-of-mouth effects on the misreporting of science.

Host: Vicenç Gómez

November, 21

15:30 h

52.217

PhD Research Seminar

By Aurelio Ruíz

Competences and skills in research
 
Abstract:
 
The Vitae Researcher Development Framework (RDF) is structured into four domains covering the knowledge, behaviours and attributes of researchers. It sets out the wide-ranging knowledge, intellectual abilities, techniques and professional standards expected to do research, as well as the personal qualities, knowledge and skills to work with others and ensure the wider impact of research. Within each of the domains there are three sub-domains and associated descriptors. We will review this framework during this seminar.
 
Bio:
Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program ( https://www.upf.edu/mdm-dtic )

November, 21

12:30 h

Auditorium

PhD Research Seminar

By José Luis Martí, Vice-rector of innovation and Associate Professor of law and political philosophy , UPF 

 

Global democracy, CrowdLaw, and the role of digital technologies

Abstract:

Many of the most important threats our societies nowadays face (climate change, global inequalities, global health, immigration flows, nuclear security, digital security, etc.) are global or have a clear global dimension. The majority of international law and international relations scholars agree that the current global order does not respond effectively and legitimately to these new challenges. Some of them advocate for what has been called a global democracy agenda, which basically consists in several attempts to give the current global institutions -and the new ones we must probably create- more power under the condition of making them more legitimate from a democratic point of view. Given the difficulties of developing mechanisms of electoral democratic representation worldwide, all the efforts are currently put in developing new forms of non-electoral democratic legitimation. One of the most promising ideas there is the concept of Open Governance, and derived from that, the idea of CrowdLaw, both of them heavily dependent on digital technologies.

Bio:

José Luis Martí is Vice-rector of innovation and Associate Professor of law and political philosophy at Pompeu Fabra University of Barcelona. He does research on republicanism, global governance, and democratic theory (particularly on deliberative democracy, participatory democracy, and collective intelligence). He has published dozens of articles and several books, including La República Deliberativa (Marcial Pons, 2006), Deliberative Democracy and Its Discontents, co-edited with Samantha Besson (Ashgate, 2006), Legal Republicanism, also co-edited with Samantha Besson (Oxford University Press, 2009), and A Political Philosophy in Public Life, co-authored with Philip Pettit (Princeton University Press, 2010). He has been Laurance Rockefeller Visiting Fellow at the University Center for Human Values (Princeton University, 2008-2009) and Visiting Professor at University of Richmond (2014). He is now collaborating with the GovLab’s CrowdLaw project.

November, 15

15:30 h

55.309

Invited Research Seminar

By Geoffroy Peeters, Juhan Nam, Fabian-Robert Stöter, Antoine Liutkus
 
Three talks on Deep-learning for music processing 
 

15:30 - Geoffroy Peeters (Télécom Paris): Depth, triplet and conditioning for deep-MIR

Bio: Geoffroy Peeters received his PHD on signal processing for speech processing in 2001 and his Habilitation (HDR) on Music Information Retrieval in 2013 from University Paris VI. From 2001 to 2018, he led research related to MIR at IRCAM. His research topics concern signal processing and machine learning (including deep learning) for the automatic analysis of music (timbre description, audio features, singing voice, source separation, beat/downbeat/rhythm estimation, chord/key/multi-pitch estimation, music structure/summary, audio-identification, cover-version, auto-tagging), evaluation methodologies and corpus creation. Since 2018, he his full professor in the Image-Data-Signal department of Télécom Paris, Institut Polytechnique de Paris where he teaches those topics. He is the author of numerous articles and several patents in these areas and co-author of the ISO MPEG-7 audio standard. He has been co-general chair of the DAFx-2011 and ISMIR-2018 conferences and is member of the DAFx board, IEEE Task Force on Computational Audio Processing and has been elected in the ISMIR board in 2016.

16:30 - Juhan Nam (KAIST):  Deep Metric Learning for Music: Beyond the Conventional Classification Framework

Bio: Juhan Nam is an associate professor at Korea Advanced Institute of Science and Technology (KAIST), South Korea. He received his Ph.D. degree in Music from Stanford University in 2013, studying at the Center for Computer Research in Music and Acoustics (CCRMA). Before joining KAIST, he was a staff research engineer at Qualcomm from 2012 to 2014. He was also a software/digital signal processing engineer at Young Chang (Kurzweil) from 2001 to 2006.

17:00 - Fabian-Robert Stöter (Inria): Open-Unmix: tools for reproducible music separation research

Bio: Fabian-Robert Stöter received the diploma degree in electrical engineering in 2012 from the Leibniz Universität Hannover and worked towards his Ph.D. degree in audio signal processing in the research group of Bernd Edler at the International Audio Laboratories Erlangen, Germany. He is currently researcher at Inria, France. His research interests include supervised and unsupervised methods for audio source separation and signal analysis of highly overlapped sources.

 
Host: Xavier Serra

November, 14

15.30 h

55.003

PhD Research Seminar

By Miquel Martínez, UPF IT Services
 
An approach to HPC: the computational cluster at DTIC-UPF
 
Abstract:
This seminar will be an introduction to  DTIC's HPC cluster. This cluster is intended to provide high performance calculation support to all DTIC members. http://hpc.s.upf.edu/

November, 13

15.30 h

55.003

Invited Research Seminar
 
By Oriol Nieto, Pandora
 
Spectral Analysis and Detection of Extreme Vocal Effects
 
Abstract:
 
Extreme Vocal Effects are aggressive singing techniques that have increased in popularity in the past two decades mostly due to the evolution of heavy metal music. In this talk we introduce and classify such effects, discuss some of their spectral qualities, and show how they might be able to be automatically detected using deep convolutional architectures.
 
Bio: 
 

I am Oriol Nieto (Uri), a Senior Data Scientist at Pandora who previously pursued a Ph.D in Music Data Science at the Music and Audio Research Lab (MARL) in NYU. My current research focuses on topics such as music information retrieval, large scale recommendation systems, and machine learning with especial emphasis on deep architectures. My Ph.D thesis is about trying to better teach computers at "understanding" the structure of music. You can find it here. I develop open source Python packages (such as msaf), play guitar, violin, and sing (and scream) in my spare time.

Host: Xavier Serra

November, 7

15.30 h

54.004

PhD Research Seminar
 
By Gemma Álvarez Cruellas, UPF Library
 
UPF Library services for PhD students
 
Abstract:
 

Library & IT Services - LRC (Learning and Research Center) is a set of professionals who share the mission of providing library, computing and audiovisual quality services to the university community, so as to contribute to innovation and excellence in teaching, learning, research and management of Pompeu Fabra University. In this seminar, we will introduce the different services (IT services, Information resources, services for scientific publishing and PhD thesis publication), with a special focus on Mendeley, a manager for bibliography.

November, 7

12.30 h

Auditorium

Special Invited Research Seminar: Planetary Wellbeing

By Prof. Dr. Zehra Cataltepe, CEO tazi.ai, Prof. Istanbul Technical University, Comp Eng. Faculty

Better AI:  Usable, Understandable and Reactive

Abstract: 
 

Machine Learning solutions are being used in different industries for complex business usecases. Some of these cases involve human lives directly, from auto or health insurance premiums to whether someone"s CV should be considered for a job.

While data scientists work with business units in creation of successful solutions, there is a clear need for involvement of business users more in the process of creation, monitoring, updates and taking actions. These capabilities allow more people to inspect the ML models, reducing biases. In addition, ability of humans to update the models allow them to be corrected whenever they are not in line with human goals. Finally, continuous learning technologies allow ML to be responsive to changes in the world, enabling continuous service.

 
Bio:
 
Zehra Cataltepe is the CEO and Co-Founder of Tazi, one of four worldwide Gartner “Cool Vendor in AI Core Technologies” (May 2019). At Tazi, her aim is to help transform Machine Learning into a technology that can be used easily and useful for everyone. After she got her Ph.D. from Caltech in Computer Science, Zehra worked at Bell Labs and Siemens Corporate Research. She is a Professor at Istanbul Technical University Computer Engineering Department and has been teaching courses on Machine Learning. She has 18 patents and over 90 publications on theory of machine learning and its applications in finance, health, energy and transportation.
OCTOBER  

October,24

15.30

 

55.309

PhD Research Seminar
 
By Aurelio Ruiz, PhD Seminars Coordinator
 
Introduction to PhD Seminars
 
Abstract:
The PhD seminars aim at creating reflection on PhD students about non-technical skills and management processes required to conduct research projects and work in international teams (such as the capability to present objectives and results to specialised and layman audiences; anticipate the ethical implications of own research; basic project and self-management skills, especially those linked to networking, team working and collaboration or understand the critical aspects linked to Intellectual Property Rights and related legal aspects), facilitate the the optimal use of all tools available at UPF and the PhD program to conduct the PhD Project (such as library services or the computational cluster) and increase the knowledge of the research conducted in the broad range of ICT areas covered by the research groups involved in the program and their collaborators
 
Bio:

Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program ( https://www.upf.edu/mdm-dtic )

October,16 15.30

 

Auditorium

Invited  Research Seminar
 
By Damijan Miklavčič
 
Electrochemotherapy – a simple concept turned into a complex story
 
Abstract:
In this lecture a personal view on the past, present and future of electrochemotherapy will be given by Damijan Miklavčič who has been involved in the development of electrochemotherapy from 1992 and has been also responsible for bringing it to the market. A combination of high voltage electric pulses to increase cell membrane permeability and chemotherapeutic drug was termed electrochemotherapy. A chemotherapeutic drug with intracellular target like bleomycin and cisplatin, which also have hindered transport across the membrane, is ideal as electroporation greatly potentiates its cytotoxicity. Membrane electroporation however also results in leakage of intracellular components (DAMP molecules) which unavoidably elicit immune response. Application of electric pulses reduces blood flow and tissue perfusion, modifies vascular permeability in tumors and disrupts blood-brain barrier. Is this all?
 
Bio:
Damijan Miklavčič was born in Ljubljana, Slovenia, in 1963. He received his Ph.D. degree in electrical engineering from the University of Ljubljana in 1993. He is currently a Professor at the Faculty of Electrical Engineering, University of Ljubljana, where he is also the Head of the Laboratory of Biocybernetics (http://lbk.fe.uni-lj.si/en/). His current research interests include electroporation-based treatments and therapies, including cancer treatment by means of electrochemotherapy, cardiac tissue ablation by irreversible electroporation and gene transfer for DNA vaccination. His research involves biological experimentation, numerical modeling of biological processes and hardware development.
 
Host: Antoni Ivorra
SEPTEMBER  

September,19 15.30

 

55.309

Invited Research Seminar

By Yasin Abbasi-Yadkori

Efficient exploration in sequential decision making problems

Abstract:

I will discuss recent results in designing more adaptive bandit algorithms. Our first approach is based on the bootstrap method and leads to a more efficient and data-dependent algorithm for the multi-armed bandit problem. Our second approach is a model-selection method for bandit problems. As an example of the usefulness of the approach, when the reward function is largely independent of the contexts, the method will automatically converge to the simpler and more efficient non-contextual algorithm.

Bio:

Yasin Abbasi-Yadkori is a researcher at VinAI, Vietnam. He received his Ph.D. in Computing Sciences from University of Alberta in 2012 under the supervision of Csaba Szepesvari. He was a postdoctoral researcher in Queensland University of Technology with Peter Bartlett, and he was a researcher in Adobe San Jose from 2016 until 2019. He is broadly interested in developing autonomous and adaptive agents that perform well in challenging environments.

https://yasin-abbasi.github.io/

2018/2019

2019
SEPTEMBER  

September, 12

15.30

 

55.309

Invited Research Seminar

By Esteban Maestre, McGill University

Virtual Acoustic Rendering by stave wave synthesis

Abstract: 

We present State Wave Synthesis (SWS), a framework for the efficient rendering of sound traveling waves as exchanged between multiple directional sound sources and multiple directional sound receivers in time-varying conditions. We introduce a mutable state-space system modal 
formulation through which input/output matrices change size and coefficients in time-varying conditions, and perceptually motivated designs are possible. SWS enables the accurate simulation of frequency-dependent source directivity and receiver directivity, provides means for simulating frequency-dependent attenuation of propagating waves, and allows an alternative realization through which state variables are treated as propagating waves.

Biography:

B.Sc. and M.Sc. degrees in Electrical Engineering from Universitat Politècnica de Catalunya, Barcelona, in 2000 and 2003; and the D.E.A. Master and Ph.D. degrees in Computer Science and Digital Communication from Universitat Pompeu Fabra, Barcelona, in 2006 and 2009. 
Lecturer at UPC, Department of Electrical Engineering, in between working as a Junior Researcher at Philips Research Laboratories Aachen.
Researcher (Music Technology Group) and a Lecturer (Department of Information and Communication Technologies) at Universitat Pompeu Fabra, working on diverse topics in Music Technology, 2004-2013.
I spent close to four years at the Center for Computer Research in Music and Acoustics, Stanford University. Also visiting Researcher at the Department of Mathematics, Universidad Federico Santa María, Santiago, Chile.
Through a Marie Curie IOF fellowship, I spent the years between 2014 and 2017 pursuing my research at the Computational Acoustic Modeling Lab / Center for Interdisciplinary Research in Music Media and Technology of McGill University, and also at the Music Technology Group of Universitat Pompeu Fabra.
Since early 2017, I am a Research Associate at the Computational Acoustic Modeling Lab, McGill Univeristy, where I also lecture on Music and Audio Computing.
My research interests include audio digital signal processing, gesture control and numerical schemes for efficient sound synthesis by physical models, computational modeling of music performance, cognitive aspects of sensory-motor integration in music performance, and artificial reverberation.
https://ccrma.stanford.edu/~esteban/bio.html

September, 10

15.00

 

55.309

Invited Research Seminar

By Caroline Essert

Modelling the surgical knowledge for computer-assisted preoperative planning

Abstract: 

Minimally invasive surgery, and more particularly percutaneous surgical interventions, are very popular alternatives to open surgery. However, the main difficulty with such interventions is the lack of visibility on the surgical sites. A thorough preoperative planning is essential for the best efficacy and safety of the procedure, to select the most optimal tools placement while preserving the surrounding sensitive organs. However, an optimal plan is usually complex to imagine and requires a high expertise. In this talk, we will show how a computer model of the surgical knowledge coupled with patient-specific images is used to assist the surgeon to choose the best intervention strategy before performing the surgery.

Biography:

Caroline Essert received her PhD of Computer Science in 2001 and her Habilitation in 2011 from the University of Strasbourg / ICUBE lab, where she is an associate professor since 2003. Her main research interests are preoperative surgery planning applied to abdominal surgery and neurosurgery, computer-assisted surgery and navigation, virtual reality and haptics for surgery. She obtained a number of national and international grants on that topics, and authored or co-authored more than 50 scientific articles. She initiated the PILOT software project for preoperative surgical planning. She has been involved in the organization of conferences in the fields of medical imaging or computer graphics for many years. In 2019, she is a co-Program Chair for MICCAI, a member of the PC of IPCAI and CARS, and is a member of the organizing committee of CARS in Rennes. In 2014, she co-organized the international conference Eurographics in Strasbourg, and will be the general chair of MICCAI 2021. She is a member of the international boards of the MICCAI Society and the ISCAS Society. At a national level, she has been a committee member of the French National Research Agency (ANR), and she is currently a member of the Computer Science section of the French National Council of Universities (CNU).

Host: Miguel Angel González Ballester

JULY  

July, 23

12.00

 

55.410

Invited Research Seminar

By Gabriela Ferraro

Extracting Normative Rules from Legal Texts: Challenges (short presentation)

Laws and regulations govern our daily lives, and we often require expert’s consult to deal with them. Having an automated system capable of interpreting and reasoning about laws and regulations from legal documents would indeed ease the burden required with dealing with the subject. However, a required first step in order to automatise the process, is to extract such laws and regulations in a formalised format that a machine can interpret and reason about. To do so, it is necessary to extract normative rules from sentences written in natural language.
In this talk, I will present some of the NLP related challenges of extracting normative rules from sentences, and explore promising research avenues to approach this problem.

Transfer Learning for Hate Speech Detection in Social Media (long presentation)

In today's society more and more people are connected to the Internet, and its information and communication technologies have become an essential part of our everyday life. Unfortunately, the flip side of this increased connectivity to social media and other online content is cyber-bullying and -hatred, among other harmful and anti-social behaviors. Models based on machine learning and natural language processing provide a way to detect this hate speech in web text in order to make discussion forums and other media and platforms safer. The main difficulty, however, is annotating a sufficiently large number of examples to train these models. In this paper, we report on developing automated text analytics methods, capable of jointly learning a single representation of hate from several smaller, unrelated data sets.
We train and test our methods on the total of 37,520 English tweets that have been annotated for differentiating harmless messages from racist or sexists in the first detection task, and hateful or offensive tweets in the second detection task.
Our most sophisticated method combines a deep neural network architecture with transfer learning. Its prediction correctness is the macro-averaged F1 of 78% and 72%  in the first and second task, respectively. This method enables generating an interpretable two-dimensional text visualization - called the Map of Hate - that is capable of separating different types of hate speech and explaining what makes text harmful. These methods and insights hold a potential for not only safer social media, but also reduced need to expose human moderators and annotators to distressing online-messaging.

Biography:

Gabriela Ferraro is a research scientist in Natural Language Processing and Computational Linguistics at the Commonwealth Science and Industrial Research Organization in Australia, and an Adjunct Research Fellow in the College of Engineering and Computer Science at the Australian National University.
She received a BA in Computer Science from Champagnat University (Argentina) in 2004, and a Master degree in Science of Language and Applied Linguistics from Universitat Pompeu Fabra (Spain) in the following year. In 2006, she joined the TALN Research Group from the same university and received a PhD under the supervision of Leo Wanner in 2012. In 2013, she joined the Machine Learning Research Group at NICTA for four years, and the Australian National University, where she is been a lecturer ever since.

Host: Leo Wanner

July, 17

15.00

Auditorium

Invited Research Seminar

By Ulises Cortés (UPC) and  Darío Garcia-Gasulla (BSC)

AI & Health @ High Performance Artificial Intelligence

Abstract:

Artificial intelligence (AI) is having a significant impact on Health care. As a matter of fact, AI in Health care is redefining the medical care field and all its functions. We bring a presentation of the eHealth care-related research topics and challenges that we have been exploring, at the HPAI & KEMLg, along the last years. We present an analysis on how the use of the AI techniques - in particular, Deep Learning- to improve the management of the data generated by the eHealth activity, permitting to take more advanced decisions on the diagnosis, treatment and supervision of the patients. 
We stress the need for responsible use of AI technology, stressing that the potential harms related to the use of AI technology must be transparent to all involved.

Biography:

Dr.Ulises Cortés is a Full-Professor and Researcher of the Technical  University of Catalonia (UPC) since 1982 (tenured since 1988 and habilitated as Full-Professor since 2006) working on several areas of Artificial Intelligence (AI) in the Computer Science (formerly Software Department) including knowledge acquisition for and concept formation in knowledge-based systems, as well as on machine learning and in autonomous intelligent agents. Since 1989 Professor Cortés and his group have been applying their work in Artificial Intelligence to Environmental Sciences in special to Wastewater Treatment Plants with the financial support of CICyT and CIRIT and the European Union. Professor Cortés advised 22 PhD. Thesis, two of them have been awarded with the ECCAI AI Dissertation Award, and more than 20 Master Thesis in the field of Artificial Intelligence and has more than 50 papers in international journals.

Dr. Darío Garcia-Gasulla is a Senior Researcher at BSC, where he has worked since 2015. Before that, he was an assistant researcher for 4 years  at  the  KEMLg  group (UPC),  participating  in  several  research  projects  related to Artificial Intelligence (particularly in Knowledge Representation and Reasoning, Machine Learning and Data Mining). His PhD thesis tackled the large-scale graph-mining problem, bringing together AI and HPC topics. As a Post Doc, he is now leading several research projects in Deep Learning and its internal representations, and Graph Analytics.

Host: Jérôme Noailly

July, 10

15.30

55.309

Invited Research Seminar

Facebook News Feed Integrity

By Lluís Garcia-Pueyo

Abstract: 

Facebook goal with News Feed is to show people the stories that matter most to them, every time they visit Facebook. News Feed is a personalized, ever-changing collection of photos, videos, links, and updates from the friends, family, businesses, and news sources they've connected to on Facebook. People on Facebook value meaningful, informative stories, and accurate and authentic content. Integrity teams within Facebook are responsible to maintain and enforce Community Standards that reflect our collective values for what should and should not be allowed on the platform. In this talk, I'll give an overview of how the News Feed works, and how we enforce Integrity in the News Feed, as well as the challenges in combining maximizing relevance while minimizing bad experiences. 

Biography:

Lluis Garcia-Pueyo is an Engineer Manager at Facebook (2017 - now), working on discovering and reducing negative experiences in News Feed ranking. Prior to this, he worked in information extraction and information retrieval at Google Research (2012-2017), and multimedia retrieval and display advertising at Yahoo Research (2007-2012). Luis holds an MS in Computer Science from the Universitat Politècnica de Catalunya (UPC). His research has been published in top-tier conferences such as WWW, KDD, SIGIR, ACM Multimedia, and WSDM, and he is a usual PC member for KDD, WWW and other conferences.
 
Host: Aurelio Ruíz
JUNE  

June, 20

15.30

52.S29

PhD Research Seminar 

Impact of machine intelligence in healthcare

By Sergio Sánchez-Martínez

Abstract:

This talk aims at advancing the scientific understanding of machine learning (ML) related to healthcare and at studying the impact of ML algorithms on humans, focusing on clinical decision-making. The talk will be articulated around the essential building blocks to achieving the high-level task of clinical decision-making, namely data acquisition, feature extraction, interpretation and decision support. For each of these blocks, the speaker will provide a concise review of state-of-the-art applications, followed by the challenges still to overcome and the potential benefits of their application in clinical practice. At the end, there will be a discussion on the main problems to tackle when creating algorithms to analyze clinical data and also implementation challenges, such as which interaction paradigms we should use, or the competences medical doctors should have. 

Biography:

Sergio Sánchez-Martínez, Postdoctoral Research Fellow at Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS).

June, 18

15.30

55.309

Invited Research Seminar 

Exact Time Series Motif Discovery using a Commercial GPU Cluster: How to 
Execute More than One Quintillion Pairware Comparisons in a Single Day

By Philip Brisk

Abstract 

The ability to discover motifs, conserved (repeated) patterns in time series, is arguably the most important computational primitive in time series data mining. Time series motifs are useful in their own right, as they provide insight to domain scientists about the behavior or physical  phenomena that the time series characterizes. Time series motifs can also be used as inputs into and are also used as inputs into classification, clustering, segmentation, visualization, and anomaly detection algorithms. In recent years, the Matrix Profile has emerged as a promising way to represent highly similar subsequences within a larger time series, and allows the efficient exact computation of the top-k motifs. Many scientific domains, such as astronomy and seismology exhibit an insatiable appetite to consider ever-large time series data 
sets. To meet the needs of scientists, the Matrix Profile can be computed in a rapid and scalable manner by deploying on commercial GPU clusters in the cloud; using this framework, it is possible to achieve throughput as high as one quintillion exact pairwise time series comparisons in a single day. For the first time, it has been possble to perform exact motif discover on more than one year's worth of continuous earthquake data in a single run; this has led to the discovery of what may be subtle precusor earthquakes that have previously escape attention, along with other novel seismic irregularities that domain scientists are presently studying.

Biography

Philip Brisk received the B.S., M.S., and Ph.D., all in Computer Science, from UCLA in 2002, 2003, and 2006 respectively. From 2006-2009, he was a postdoctoral scholar at EPFL in Lausanne, Switzerland. Since 2009, he has been with the University of California, Riverside; he has been promoted to Professor effective July 1, 2019. Dr. Brisk's research interests lie at the intersection between processor architecture, VLSI/CAD, compilers, FPGAs, and reconfigurable computing; most recently, he has been applying these principles to the design and analysis of biological instruments. He is a Senior Member of the ACM and IEEE, and is presently an Associate Editor of the IEEE Transactions of Computer-Aided Design on Integrated Circuits and Systems (TCAD) and Integration: The VLSI Journal. 

June, 17

15.30

55.309

Invited Research Seminar 

Spatial representations and high level descriptors for symbolic music analysis

By Louis Bigo 

Abstract

This talk focus on two computational approaches to symbolic music analysis. The first approach includes the notion of pitch/chord space, that we use to reformulate in spatial terms different musical tasks as style recognition and harmonic transformations. Musical spaces are formalized with topological structures named simplicial complexes. Elementary musical objects (for example pitches or chords) are represented by simplices that are organized according to a neighborhood relationship which translates a musical property, for example consonance. Such spatial formulation of musical structures enables the application of geometrical and topological operations, such as translations, rotations, embeddings and filtrations, that bring original approaches to music composition and analysis.
The second approach focus on the extraction of high level musicological features that can serve automated analysis of classical forms. We will discuss the detection of cadences and the retrieval of section boundaries in sonata form with different machine learning methods.

Biography

I am associate professor (maître de conférence) in computational musicology at University of Lille in the Algomus team (Algorithmic musicology) at CRIStAL laboratory since 2016. My research interests include mathematical models and machine learning for automatic music generation, analysis and classification. I received my Ph.D in Computer Science on the topic of symbolic music representations and spatial computing in 2013 at IRCAM (French Institute for Research and Coordination in Acoustics/Music) and LACL, University Paris 12. I joined the European project Learning To Create on music and machine learning from 2014 to 2016 in the Music Informatics Group at the University of Basque Country in San Sebastian, Spain.

Host: Xavier Serra

June, 12th

15.30

52.217

PhD Research Seminar 

Profiling and automated decision making under the General Data Protection Regulation

By  Antoni Rubí-Puig

Abstract:

The session aims at discussing the rules on profiling and automated individual decision-making under the General Data Protection Regulation and at assessing their adequacy from the standpoint of the Fairness, Accountability, Transparency and Ethics (FATE) framework. Our focus will be on profiling, that is, the automated processing of personal data with the goal of evaluating certain personal aspects relating to an individual, such as for instance analyzing or predicting her performance at work, economic situation, health, personal preferences, interests, willingness to pay, reliability, behavior, location or movements.

Progresses in technology and the use of big data analytics, artificial intelligence and machine learning have made it easier to elaborate profiles. Profiling can be in the advantage of individuals and organizations as it may lead to increased efficiencies and cost savings. However, it also involves significant risks for individuals’ rights and freedoms, not only to privacy. Rules in the GDPR aim at finding a balance between those advantages and risks but the final trade-off may not be the most adequate one for the FATE framework.

Biography:

Antoni Rubí-Puig,  Associate Professor in Civil Law and Associate Director for Research at the Law Department at UPF (research group).

June, 4th

15.30

55.309

PhD Research Seminar

By Simone Tassani

Abstract

The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis.

Biography

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

June, 6th

10.30

55.309

Invited Research Seminar 

The value of Aligning Learning Analytics with a Theory-Grounded Learning Design 

By Korah Wiley   

Abstract

Learning analytics can provide teachers with information about students’ engagement with and performance on learning tasks. When these tasks are components of a theory-grounded learning design, the associated analytics have the potential to provide teachers with insight into the learning process. In this talk, I will describe the design of such theory-grounded learning analytics. Additionally, I will present findings on how teachers used these learning analytics to develop instructional interventions. I will also present findings regarding the effect of these interventions on student learning.

Biography

Korah Wiley is a doctoral candidate in the Graduate Group in Science and Mathematics Education (SESAME) program at the University of California-Berkeley and a National Science Foundation CADRE Fellow. Prior to pursuing her doctorate, she earned a Bachelor of Science in Biochemistry, a Master of Science in Molecular Cancer Biology, and taught for over 10 years as a biology instructor at the North Carolina School of Science and Mathematics. Her time teaching inspired her current research interest to support equitable STEM classroom teaching and learning. Currently, in her dissertation work, Korah investigates how to develop learning analytic solutions that promote implementation by teachers and the development of coherent science knowledge in students.

Host: Davínia Hernandez-Leo

MAY  

May,31

15.30

55.309

PhD Research Seminar

Human behaviour and machine intelligence

By Emilia Gómez

Biography

Emilia Gomez, lead scientist of the HUMAINT project at the Centre for Advanced Studies, Joint Research Centre, European Commission, and head of the MIR (Music Information Research) lab of the Music Technology Group (MTG) at UPF.

May,30

15.30

55.309

PhD Research Seminar

By Simone Tassani

Abstract

The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis.

Biography

Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.

May,29

15.30

55.309

Multi-modal hearing devices and their evaluation

By Volker Hohmann

Abstract

Spatial filtering and decomposition of sounds into acoustic source objects is increasingly investigated for speech enhancement in hearing aids. However, with increasing performance and availability of these "space aware" hearing aid algorithms, knowledge of the user’s personal listening preferences and knowledge of the attended source becomes crucial.

Here we present an algorithm, which combines information of the subject’s eye gaze with an acoustic analysis of the sound source positions to identify the attended source(s) from a mixture of sources. Gaze direction is recorded by electrooculography (EOG) combined with a head tracking system, which could in principle be integrated in hearing aids. The spatio-temporal distribution of source positions is estimated from input signals to a binaural hearing device. Beamformer techniques are then used to enhance the source (or the sources) that are estimated as being attended. By using (electro-)physiologic sensor signals to estimate attention and behavior, the hearing device becomes part of the active communication loop between environment and behaving subject.

Such closed-loop hearing devices require “subject-in-the-loop” evaluation methods, which simulate realistic interactive environments to reproduce natural behavior. This means that audio-visual signals are required that also include behavioral simulation of the sources, e.g., simulated lip movement, or simulated conversational gaze behavior. The current status of our developments towards such an audiovisual interactive lab are presented in this talk.

Project funded by DFG SFB 1330 project B1 and EU H2020 MSCA ITN No
675324 (ENRICH).

Biography

Volker Hohmann received the Physics degree (Dipl.-Phys.) and the doctorate degree in Physics (Dr. rer. nat.) from the University of Göttingen, Germany, in 1989 and 1993. From 1993-2012 he was a faculty member of the Physics Institute, Oldenburg University, Germany, and was appointed full professor at the Faculty for Medicine and Health Sciences at Oldenburg University in 2012. His research expertise is in acoustics and digital signal processing with applications to signal processing in speech processing devices, e.g., hearing aids. He is a consultant with the Hörzentrum Oldenburg GmbH and with HörTech gGmbH Oldenburg. He was a Guest Researcher at Boston University, Boston, MA, (Prof. Dr. Colburn) in 2000 and at the Technical University of Catalonia, Barcelona, Spain (Prof. Dr. C. Nadeu) in 2008. Prof. Hohmann received the Lothar-Cremer prize of the German acoustical society (DEGA) in 2008 and the German President’s Award for Technology and Innovation in 2012.

Host: Federico Sukno

May,23

15.30

55.309

PhD Research Seminar

Automation of personal data and consumer law enforcement using AI

By Francesca Lagioia

Abstract

Despite the European Consumer Law and EU General Data Protection Regulation (GDPR) are in place, and despite enforcers’ competence for abstract control, Terms of Services and Privacy Policies of online services  still often fail to comply with regulations. Artificial intelligence and in particular machine learning methods can be used for automating the legal evaluation of both terms of services and privacy policies, in order to empower the civil society representing the interests of consumers. 

Biography

Francesca Lagioia, postdoctoral research fellow at Interdepartmental Centre for Research in the History, Philosophy, and Sociology of Law and in Computer Science and Law (CIRSFID) at the University of Bologna, and Research Associate at the European University Institute (EUI)

May, 22
 
15:00
 
55.309

Invited Research Seminar 

Medical image analysis, artificial intelligence & tech transfer

By Sir Michael Brady

Host: Miguel Angel González Ballester

Abstract

After a very brief summary of my research career, I discuss several topics in medical image analysis and their transfer to clinical practice, via a number of start-up companies that I have founded. My work has always been driven by clinical applications. It has also been guided by a number of principles: (i) the huge variation in the appearances of medical images, with the need for algorithms in clinical practice to work reliably and robustly implies modelling the physics of image acquisition; (ii) AI, including machine learning, can play a valuable role in encoding and mobilising prior knowledge about medical images; (iii) variation in signal characteristics necessitates the definition of what constitutes an image “feature”; and (iv) since information is intrinsically uncertain, representations need to be developed of probability density functions. My talk illustrates these points with particular reference to breast cancer (mammography) and to liver disease (MRI).

Biography

Professor Sir Michael Brady, FRS FREng FMedSci HonFIET FInstP FBCS PhD, holds BSc, MSc and PhD degrees in mathematics from the University of Manchester and the Australian National University in Canberra. After 10 years as senior lecturer at the University of Essex, Prof. Brady joined the Artificial Intelligence Lab at MIT (1980-1985), where he developed fundamental contributions to artificial intelligence, mobile robotics and computer vision. He then became a Professor at the Department of Engineering Science in Oxford, of which he became director, and later joined the Department of Oncology, where he is Professor of Oncological Imaging. Prof. Brady has supervised 115 PhD students, published over 750 articles and filed 26 patents. He holds 9 honorary doctorates and important distinctions, including the IEEE Third Millenium Medal and the Henry Dale Prize from the Royal Institution. He is a member of the Royal Society and the Academie des Sciénces, amongst other prestigious institutions, and was knighted as Sir Brady in 2003. In addition to academic work, he has founded numerous startups, including Perspectum Diagnostics, Volpara Solutions, Mirada Medical Limited, ScreenPoint, Optellum, and Guidance Navigation Holdings, and was director of ISIS Innovation in Oxford from 1993 until 2011.

May, 8th
 

15.30 h

 

55.003

Invited Research Seminar 

PET/MR: GE's perspective 

By Gaspar Delso

Abstract

The combination of MR and PET data has received increasing attention in recent years, in fields such as clinical oncology and neuroimaging research. In comparison to currently used PET/CT scanners, PET/MR scanners offer improved soft-tissue contrast, reduced ionizing radiation and a wider range of contrast mechanisms, such as functional, spectroscopic and diffusion tensor imaging. The design of integrated PET and MR detectors has required a remarkable engineering effort, due to several compatibility and interference challenges, culminating in the commercialization and world-wide adoption of clinical PET/MR scanners. In this talk, we review the SIGNA PET/MR scanner, briefly describing its technical design, current performance and ongoing R&D work.

Biography

Gaspar Delso is a Biomedical Engineering PhD with a long experience in medical imaging, having published on key topics such as hardware attenuation, truncation correction and system performance. After completing his Thesis on multimodal non-rigid registration at the Universitat Politècnica de Catalunya and École Nationale Supérieure des Télécommunications in 2016, he accepted a scientific position with Philips Medical Systems, where he worked in the development of novel denoising algorithms for three-dimensional medical imaging. In 2007 he joined the Technische Universität München, where he collaborated with Siemens in the development of the first clinical PET/MR scanner. His paper describing the performance evaluation of this system has been referenced in over 600 publications. In 2012 he moved to Zurich, where he worked for GE Healthcare at the UniversitätsSpital Zürich in the development of the next generation of clinical PET/MR. In 2016, he accepted a Senior Scientist position with GE Healthcare at the University of Cambridge, collaborating with the UK Dementias Platform (DPUK) and developing the next generation of attenuation correction software for the SIGNA PET/MR system. He has recently moved to Barcelona, where he is collaborating with the Hospital Clínic in the development of novel cardiac MR applications. Dr. Delso has co-authored over 200 scientific publications in peer-reviewed journals and conferences, as well as several patents and book chapters.

Host: Jérôme Noailly

May, 2nd
 

15.30 h

 

Auditorium

Invited Research Seminar

The Fourth Phase of Water: Beyond Solid, Liquid, and Vapor

By Gerald H.Pollack

Abstract

Everyone knows that water has three phases: solid, liquid and vapor. But we have recently uncovered a fourth phase. This phase occurs next to water-loving (hydrophilic) surfaces. It is surprisingly extensive, projecting out from the surface by up to millions of molecular layers. And, its properties differ markedly from those of bulk water. Of particular significance is the observation that this fourth phase is charged; and, the water just beyond is oppositely charged, creating a battery that can produce electrical current. We found that light charges this battery. Thus, water can receive and process electromagnetic energy drawn from the environment in much the same way as plants. Absorbed electromagnetic (light) energy can then be exploited for performing work, including electrical and mechanical work. Recent experiments confirm the reality of such energy conversion. This energy-conversion framework seems rich with implication. Not only does it provide an understanding of how water processes solar and other energies, but also it may provide a foundation for simpler understanding natural phenomena ranging from weather and green energy all the way to issues such as the origin of life, transport, and osmosis. The talk will present evidence for the existence of this novel phase of water — how come nobody’s seen it before? — and will consider the potentially broad implications of this phase for health. The book dealing with this subject is now available http://www.amazon.com/The-Fourth-Phase-Water-Beyond/product-reviews/0962689548

Biography

Gerald Pollack received his PhD in biomedical engineering from the University of Pennsylvania in 1968. He then joined the University of Washington faculty and is now professor of Bioengineering. He is also Founding Editor-in-Chief of the journal, WATER, convener of the Annual Conference on the Physics, Chemistry and Biology of Water, and Executive Director of the Institute for Venture Science. His interests have ranged broadly, from biological motion and cell biology to the interaction of biological surfaces with aqueous solutions. His 1990 book, Muscles and Molecules: Uncovering the Principles of Biological Motion, won an “Excellence Award” from the Society for Technical Communication. His 2001 book, Cells, Gels and the Engines of Life, and his newest book, The Fourth Phase of Water: Beyond Solid, Liquid, and Vapor won that Society’s “Distinguished Award,” their highest distinction. The latter book went on to receive the World Summit Excellence Award. Pollack received an honorary doctorate in 2002 from Ural State University in Ekaterinburg, Russia, and was more recently named an Honorary Professor of the Russian Academy of Sciences, and foreign member and Academician of the Srpska Academy. He received the Biomedical Engineering Society’s Distinguished Lecturer Award in 2002. In 2008, his colleagues chose him as the recipient of his university’s highest annual distinction: the UW Faculty Lecturer Award. Pollack is a Founding Fellow of the American Institute of Medical and Biological Engineering and a Fellow of both the American Heart Association and the Biomedical Engineering Society. He received an NIH Director’s Transformative R01 Award. He was the 2012 recipient of the Prigogine Medal for thermodynamics of dissipative systems, and in 2014 he received the Scientific Excellence Award from the World Academy of Neural Therapy, as well as the Dinsdale Prize from the Society for Scientific Exploration. He has presented two TEDx talks on water. In 2015, he won the Brandlaureate Award, previously bestowed on notables such as Nelson Mandela, Hillary Clinton and Steve Jobs. In 2016 he was awarded the 1st Emoto Peace Prize. And, he appears briefly in the 2016 Travis Rice sports-action film, The Fourth Phase, named after his recent book.

Host: Jérôme Noailly

APRIL  
April, 30th
 

10:30 h

 

Room 55.309

Invited Research Seminar 

Network based approaches for drug discovery in osteoarthritis  

By Michael Neidlin

Abstract

In order to obtain a mechanistic understanding of complex multivariate diseases, various experimental and numerical techniques from systems biology can be used. More specifically, pathway and network based approaches provide an interesting option to unravel molecular mechanisms and pinpoint pharmaceutical treatment strategies using whole-genome sequencing data. In this talk co-expression network analysis and network based drug discovery methods will be presented and applied to osteoarthritis (OA), a complex multi-tissue disease with high prevalence in the western world.

Biography

Michael Neidlin is a postdoctoral researcher from the Biomedical Systems Laboratory at the National Technical University of Athens. He graduated as a mechanical engineering from RWTH Aachen University in Germany where he wrote his dissertation at the Institute of Applied Medical Engineering in 2016. During his work he is focusing on the biomechanics and systems biology of cartilage degradation in order to leverage drug discovery for osteoarthritis. He is interested in applying engineering approaches to in vitro experiments in order to better understand the dynamics in biological systems.

 Host: Jérôme Noailly 

April, 25th
 

15:30 h

 

Room 55.309

Invited Research Seminar

Compositionality and Automated Hierarchical Skill Discovery Using KL Control

By Andrew Saxe

Abstract

Hierarchical architectures are critical to the scalability of reinforcement learning methods. Most current hierarchical frameworks execute actions serially, with macro-actions comprising sequences of primitive actions. We propose an alternative to these control hierarchies based on concurrent execution of many actions in parallel. Our scheme exploits the guaranteed concurrent compositionality provided by the linearly solvable Markov decision process (LMDP) framework, which naturally enables a learning agent to draw on several macro-actions simultaneously to solve new tasks. We introduce the Multitask LMDP module, which maintains a parallel distributed representation of tasks and may be stacked to form deep hierarchies abstracted in space and time. Next we turn to the problem of learning an appropriate hierarchical decomposition of a domain into subtasks. In the compositional setting afforded by the LMDP, the subtask discovery problem can be posed as finding an optimal low-rank approximation of the set of tasks the agent will face in a domain. We use non-negative matrix factorization to discover this minimal basis set of tasks, and show that the technique learns intuitive multilevel hierarchical decompositions in a variety of domains. Our method has several qualitatively desirable features: it is not limited to learning subtasks with single goal states, instead learning distributed patterns of preferred states; it learns qualitatively different hierarchical decompositions in the same domain depending on the ensemble of tasks the agent will face; and it may be straightforwardly iterated to obtain genuinely deep hierarchical decompositions.
Joint work with Adam Earle and Benjamin Rosman.

Biography

Dr. Andrew Saxe is a Postdoctoral Research Associate in the Department of Experimental Psychology, University of Oxford working with Christopher Summerfield and Tim Behrens. He was previously a Swartz Fellow at Harvard University with Haim Sompolinsky. He completed his PhD in Electrical Engineering at Stanford University, advised by Jay McClelland, Surya Ganguli, Andrew Ng, and Christoph Schreiner. His dissertation received the Robert J. Glushko Dissertation Prize from the Cognitive Science Society. His research focuses on the theory of deep learning and its applications to phenomena in neuroscience and psychology.

Host: Vicenç Gómez

April, 11th
 

15:30 h

 

Room 55.003

Invited Research Seminar

NUMEDIART - Creative Technologies for Creative Industries

By Thierry Dutoit

Abstract

In this talk, Thierry Dutoit will browse activity of the research institute he leads at University of Mons, the NUMEDIART institute (https://numediart.org/), in terms of research, teaching initiatives, and community services. The talk will give examples of recent project results in 5 areas: audio, speech and music – motion capture – AR/VR – media information retrieval – smart spaces. He will conclude by the list of things he expects to take back from his 1-month stay at the MTG.

Biography

Thierry Dutoit is an electrical engineer and doctor in applied sciences. He is specialist in voice synthesis and his patents led to the creation in 1996 of ACAPELA SA, a spin-off of UMONS, which now has 40 employees in Belgium, France and Sweden. He completed a 15-month postdoctoral fellowship at AT & T's Bell Labs in Murray Hill, NJ (New York). Since 2010, he is the president of the NUMEDIART institute for creative technologies of UMONS. Artificial intelligence is at the heart of its activities. In 2016, he created in Mons the Wallon living lab of creative industries, CLICK , which contributes to the valorization and creation of new activities in the sector of creative industries. Since 2017 he directs the service of Circuits Theory and Signal Processing (Polytechnic Faculty of Mons).

Host: Xavier Serra

April, 8th
 
12.00 h
 
55.003

Invited Research Seminar

Divergence based motivation for online EM and for combining hidden variable models

By Manfred Warmuth

Abstract

Expectation-Maximization (EM) is the fall back method for parameter estimation of hidden (or latent) variable models. In each iteration the EM algorithm forms an upper-bound for the negative log-likelihood of the data and then updates to the minimizer of this upper bound. While EM is naturally a batch algorithm, online variants are strongly desirable when processing data streams or large datasets. We introduce a versatile online variant of EM. Our motivation is based on the relative entropy divergences between two joint distributions over the hidden and visible variables. We show that for the typical mixture models where EM is applied such as mixtures of exponential families, Hidden Markov Models, Kalman Filters, the joint density is again an exponential family distribution. Therefore the EM upper-bound is essentially a negative log likelihood of the joint and it is natural to use the divergence between the joints between old and new parameters as an inertia term for motivating our online EM update.

 

The resulting update is more widely applicable than previous versions. In particular it leads to an online update for Kalman filters. Additionally, the finite sample form of the inertia term provides a framework to apply the online EM algorithm when the updates do not have a closed form. Experimentally, sweeping the data with an online update converges much faster than the vanilla batch update. Our divergence based methods also lead to a simple way to combine hidden variable models and this immediately gives efficient algorithms for the distributed setting.

 

Joint work with Ehsan Amid, UC Santa Cruz.

Host: Gergely Neu

April, 4th
 
15.30 h
 
55.003

PhD Research Seminar

Workshop: Getting your PhD but keeping your sanity

By Scientists Dating Forum.

As part of the PhD seminars and as a complement to the activities during the 7th PhD workshop (April 4th) this workshop will be offered by Scientists Dating Forum. Previous registration is required.
 
Abstract

Recent studies suggest that PhD students suffer a mental health issues at alarming levels—around six times the level of the general population—issues which impact not only productivity and program outcomes but also the long-term well-being of the developing researcher.

Research centers have begun to address the issue, but it resists a simple policy solution. Indeed, the issue of mental health and well-being in PhD programs has the characteristics of a “wicked problem”. For example, it lacks a definitive solution, every problem is unique, it can be explained in a number of ways, and it tightly intertwined with a number of interconnected systems, also experiencing issues.

In light of these challenges, this workshop takes a collaborative, action-oriented approach to generate awareness and empower PhD students. Based on methods developed in psychology, organizational studies, and design thinking, it provides a means of understanding and addressing the challenges PhD students face in a way that allows for the variety of forms these are likely to take.

Participants will gain increased awareness of the complexity of the issue and propose their own solution in a hands-on, supportive setting.

April, 3rd
 
15.30 h
 
55.309

Invited Research Seminar

Data processing under uncertainty and tractability limitations 

By Santiago Mazuelas

Abstract
 
General data-driven problems can be seen as decision problems in which actions are chosen with the aid of data. For instance, supervised classification uses training data to choose a classification rule; and sequential inference uses time series to sequentially choose a target variable. 
The development of data processing techniques to address such problems is hindered by the fact that actual probability distributions of state variables are often unknown or intractable in practice. For instance, in supervised classification the actual distribution of features-label pairs is often unknown, and in sequential inference the actual posterior distribution of target values is often intractable. 
In this talk, I will describe approximation techniques to address uncertainty and tractability limitations based on optimization methods. In particular, I will present data processing techniques that address distributions' uncertainty in supervised classification and distributions' intractability in sequential inference.
 
Biography
 
Santiago Mazuelas received the Ph.D. in Mathematics and Ph.D. in Telecommunications Engineering from the University of Valladolid, Spain, in 2009 and 2011, respectively. 
Since 2017 he has been Ramon y Cajal Researcher at the Basque Center for Applied Mathematics (BCAM). Prior to joining BCAM, he was a Staff Engineer at Qualcomm Corporate Research and Development from 2014 to 2017. He previously worked from 2009 to 2014 as Postdoctoral Fellow and Associate in the Wireless Information and Network Sciences Laboratory at the Massachusetts Institute of Technology (MIT). He is a frequent visitor of the Laboratory for Information and Decision Systems (LIDS) at the MIT, where he holds the Research Affiliate appointment. His general research interest is the application of mathematics to solve engineering problems, currently his work is primarily focused on statistical signal processing, machine learning, and data science. 
Dr. Mazuelas is Associate Editor for the IEEE Communications Letters and served as Co-chair for the Symposiums on Wireless Communications at the 2014 IEEE Globecom and at the 2015 IEEE ICC. He has the Young Scientist Prize from the Union Radio-Scientifique Internationale (URSI) Symposium in 2007, and the Early Achievement Award from the IEEE ComSoc in 2018. His papers received the IEEE Communications Society Fred W. Ellersick Prize in 2012, and Best Paper Awards from the IEEE ICC in 2013, the IEEE ICUWB in 2011, and the IEEE Globecom in 2011. 
MARCH  
March, 28th
 
15.30 h
 
55.309

Invited Research Seminar

Learning of musical structures for automatic improvisation systems 

By Ken Déguernel

Abstract

This work is part of the "Creative Dynamics of Improvised Interaction" project (DYCI2) that aims at creating digital musical agents able to listen, learn and interact with human performers to generate creative improvisations. The aim of this work is to create a system able to learn the dependencies between several dimensions (e.g. pitch, harmony, rhythm…), take into account the form of music upon several levels of organisation (e.g. beat, measure, section…), and use this information to generate more creative and more artistically credible improvisations. 
I will first present a system combining interpolated probabilistic models with a factor oracle. The probabilistic models are trained on a corpus and provide information on the correlation between dimensions and are used to guide the navigation in the factor oracle that ensure a logical improvisation. The improvisations are therefore generated in a way where the intuition of a context is enriched with multidimensional knowledge. We create then a system creating multidimensional improvisations based on interactivity between dimensions via message passing through a cluster graph. The communications infer some anticipatory behaviour on each dimension now influenced by the others, generating consistent multidimensional improvisations. 
Then, I propose a method taking into account the form of a tune upon several levels of organisation to guide the music generation process. Phrase structure grammar are used to represent a hierarchical analysis of a chord progression and this multi-level structure is then used to enrich the possibilities of guided machine improvisation.
Finally, I will present the final results from the DYCI2 projects, in particular, the DYCI2lib, a FLOSS library for automatic improvisation.

Biography
 
Ken Deguernel is a doctor in Computer Music. His research interests include music informatics, formal language theory, semigroup theory, probabilistic models and musicology. In particular, his work focuses on the understanding, the analysis and the modelling of order and disorder parts of creative processes employed by musicians during improvisation and composition in different contexts and different styles.
 
Host: Xavier Serra
March, 27th
 
10.30h
 
55.309

Invited Research Seminar

Design for effective orchestration and pedagogical interventions aligned with learning analytics in technology-enhanced learning ecosystems: Notes of a sabbatical year

By Yannis Dimitriadis

Abstract

Technology-enhanced learning ecosystems are becoming quite complex, especially when non-conventional approaches, such as collaborative or inquiry learning are employed. On the other hand, the recent advances in the learning analytics field have been very promising, for purposes of understanding and optimizing learning and the environments in which it occurs. However, the alignment between design for learning and learning analytics has been recently shown to be a pending, albeit essential, issue that would allow for effective and efficient pedagogical interventions and orchestration. This informal seminar – colloquium will discuss some recent work during and after the sabbatical year of Prof. Dimitriadis (2017-2018) at University of Edinburgh, EPFL Lausanne and UC Berkeley. Some topics include:

- Design for orchestration and analytics (theoretical frameworks and principles)

- Examples of on-going work, as e.g. inquiry science learning using WISE units in K-12, coaching in Agile Software Engineering course in Higher Education

- Reflections on research mobility and its effects on personal and community trajectories

Biography

Dr. Yannis Dimitriadis (https://www.gsic.uva.es/members/yannis and https://scholar.google.es/citations?user=xrzS-v4AAAAJ&hl=es&oi=ao) is Full Professor of Telematics Engineering and ex Dean of the School of Doctoral Studies of the University of Valladolid, Spain. He is also the coordinator of the GSIC/EMIC research group, an inter-disciplinary group, integrating 20 researchers and practitioners from the field of Information and Communications Technologies (ICT) and Pedagogy. His research interests include learning design, design patterns and the conceptual and technological support to the orchestration of computer-supported collaborative learning processes. He has participated in more than 55 competitive research projects on technology-enhanced learning, such as the Kaleidoscope Network of Excellence in technology enhanced learning, Sharetec, Metis, EEE or Reset, being the PI in 24 of them. Dr. Dimitriadis has co-authored more than 90 journal papers (52 indexed in ISI-JCR), 190 conference papers, and 24 book chapters.

Host: Davinia Hernandez-Leo

March, 21st
 
15.00 h
 
55.309

PhD Research Seminar

Sounds of Science: share your ideas with sounds

March, 21st
 
12.00 h
 
55.230

Invited Research Seminar

Shaping the City with Data Science

By Eduardo Graells-Garrido

Abstract

Cities are growing at a fast rate, and transportation networks need to adapt accordingly. To design, plan, and manage transportation networks, domain experts need data that reflect how people move from one place to another, at what times, for what purpose, and in what mode(s) of transportation. However, traditional data collection methods are not cost-effective or timely. For instance, travel surveys are very expensive, collected every ten years, a period of time that does not cope with quick city changes, and using a relatively small sample of people. Considering this context, In this talk I give an overview of how we can infer patterns of transportation and mobility in a city by analyzing non-traditional data sources. I focus mainly on Mobile Phone Data, but I also mention Social Media and Volunteered Geographic Information. As result, the audience will learn about individual- and city-level insights related to transportation, mobility, and visualization. http://bit.ly/ShapingTheCity

Biography

Eduardo Graells-Garrido: Profesor Investigador en el Instituto de Data Science de la Universidad del Desarrollo, Facultad de Ingeniería, y fellow de Telefónica I+D Chile. Obtuvo su doctorado en la Universitat Pompeu Fabra de Barcelona, a través de una estadía en los laboratorios de Yahoo! Research. En su tesis investigó los sesgos de comportamiento utilizando computación centrada en las personas y análisis de redes sociales. Sus temas de investigación actuales son informática urbana, transporte computacional, y ciencia social computacional.

Host: Carlos Castillo

March, 15th
 
17.00 h
 
55.309
PhD Research Seminars
 
Science & beer event
 
- Ahmed Ghassan Tawfiq Abura'ed (DTIC, UPF) - Towards automatic generation of related work reports
- Venelin Ornilov Kovatchev (CLiC, UB) - Paraphrasing, textual entailment, and semantic similarity
- Laura Diaz, Ryan Armstrong (SciDF) - Scientists Dating Forum: how to close gaps between society, science, and politics 
March, 14th
 
15.30 h
 
55.309

PhD Research Seminar

Statistical course and Design of Experiments 

By  Simone Tassani

Abstract

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.

Projects with more than two factors will be presented. This will lead to the presentation of some examples of Design of Experiment (Latin and Greek-Latin squares) for the reduction of the number of experiments and to the concept of orthonormality.
The course will close with the description of linear regression.
 
Biography
 
Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.
March, 13th
 
15.30 h
 
55.309

Tutorial - Data driven-text simplification

By  Sanja Štajner, Horacio Saggion

Abstract

In this tutorial, we aim to provide an extensive overview of automatic text simplification systems proposed so far, the methods they used and discuss the strengths and shortcomings of each of them, providing direct comparison of their outputs. We aim to break some common misconceptions about what text simplification is and what it is not, and how much it has in common with text summarisation and machine translation. We believe that deeper understanding of initial motivations, and an in-depth analysis of existing TS methods would help researchers new to ATS propose even better systems, bringing fresh ideas from other related NLP areas. We will describe and explain all the most influential methods used for automatic simplification of texts so far, with the emphasis on their strengths and weaknesses noticed in a direct comparison of systems outputs. We will present all the existing resources for TS for various languages, including parallel manually produced TS corpora, comparable automatically aligned TS corpora, paraphrase- and synonym- resources, TS-specific sentence-alignment tools, and several TS evaluation resources. Finally, we will discuss the existing evaluation methodologies for TS, and necessary conditions for using each of them.

Previous registration necessary: https://www.upf.edu/web/mdm-dtic/tutorial-data-driven-text-simplification

Host: Aurelio Ruiz

March, 11th
 
15.30 h
 
55.309

Invited Research Seminar

Entity-centric information access for high-end semantic applications

By  Simone Paolo Ponzetto

Abstract

In the past years a great deal of work across different communities, ranging from Natural Language Processing (NLP) and Information Retrieval (IR) all the way through the Semantic Web (SW) and Digital Libraries (DL), has focused on entities as central tools to build semantic models of ever increasing complexity. Entity Linking, for instance, has arguably brought `classic' sense disambiguation tasks, historically confined to the domain of computational semantic analysis, to a much larger audience, including real-world applications like semantic search, producing as a consequence full-fledged, entity-aware and entity-centric document search models.

All in all, this is good news, since these lines of research all seem to point out the benefits of text understanding for high-end applications. Even more important is the fact that work on entity-centric models prompts, perhaps even requires, lines of research from related, yet far apart research communities like NLP, IR, SW and DL to synergistically come together.

In this talk, I will elaborate on this topic of entity-centric information access and explore a variety of different high-end applications that leverage entities to make sense and bring order within large datasets of textual data. These include ranking entities for Web search queries, building event-centric corpora from Web archives, as well as using entity-aspect linking to predict relevant entities for user queries, events and tweets. 

Biography

Simone Paolo Ponzetto is Professor of Information Systems at the University of Mannheim and member of the Data and Web Science Group, where he leads the Natural Language Processing and Information Retrieval group. His main research interests lie in the areas of knowledge acquisition, text understanding, and the application of natural language processing methods for research in the digital humanities and computational social sciences.

Host: Horacio Saggion

March, 7th
 
15.30 h
 
55.309

PhD Research Seminar

Statistical course and Design of Experiments 

By  Simone Tassani

Abstract

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.

In the second class the non-parametric "equivalent" of ANOVA will be introduced: Kruskal-Wallis test.

Monofactorial and multifactorial analysis will be presented, together with the definition of Type I and Type II error, multiple comparison errors and tests for multiple comparison.

Biography
 
Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.
March, 5th
 
15.30 h
 
55.309

Invited Research Seminar

MobInsight - Approach to Interpretation of Urban Dynamics through Crowdsourced Local Knowledge

By Souneil Park

Abstract

Collective urban mobility embodies the residents' local insights on the city. Mobility practices of the residents are produced from their spatial choices, which involve various considerations such as the atmosphere of destinations, distance, past experiences, and preferences. The advances in mobile computing and the rise of geo-social platforms have provided the means for capturing the mobility practices; however, interpreting the residents' insights is challenging due to the scale and complexity of an urban environment, and its unique context. In this talk, I will present MobInsight, a platform for localized interpretations of urban mobility that reflect various aspects of the urbanism. MobInsight provides a scalable solution for localized mobility interpretation; first, by extracxting urban contextual knowledge from diverse online sources such as geo-social media, open government data, second, by developing tailored machine learning and visualization techniques which augments the urban contextual knowledge with large-scale mobility data. The talk will mainly go through the techniques in detail, but also cover various examples and applications. 

Biography

Souneil Park is currently at Telefonica Research, working in the areas of social computing, HCI, and information visualization. His recent research interest is in expanding our understanding of the urban dynamics, by applying NLP/AI techniques (used for semantic analysis) to the data that does not explicitly carry semantics, such as mobility and sensory data. Prior to joining Telefonica, he worked on analyzing online media use and developing technologies to enhance people's ability to comprehensively understand, reason, and make well-informed decisions. 

Host: Carlos Castillo

March, 4th
 
15.30 h
 
55.309

Invited Research Seminar

The Hearing Device of the Future

By Waldo Nogueira

Abstract

Hearing is the ability to perceive sounds by detecting vibrations and is one of the most important senses, as humans rely on speech to communicate in daily life. Recent advances in engineering, computing and neuroscience are contributing to novel approaches to recover the hearing sense based on devices such as hearing aids, cochlear implants and central auditory prostheses including the auditory nerve implant and the auditory midbrain implant. These new approaches are based on stimulating the hearing system at different stages, from the periphery to the central auditory system, recovering binaural hearing with cochlear implants and the use of closed-loop systems that record cortical activity and use it to actively control the signal processing of the hearing device.

During the seminar I will present novel contributions in the field of signal processing, sound coding and electrophysiology within the common topic of designing the hearing device of the future.

Biography

Waldo Nogueira received his Dipl.-Ing. and Dr.-Ing. degree from the Polytechnic University of Catalonia and the Leibniz University of Hannover in 2003 and 2008, respectively. In 2008 he joined the R&D labs of Advanced Bionics in Belgium and Germany. In 2011 he was a Post-Doc at the Pompeu Fabra University in Barcelona. Since 2013 he is Junior Professor at the Hannover Medical School within the Cluster of Excellence Hearing4all.

March, 1st
 
15.30 h
 
55.309

Invited Research Seminar

Learning, Representations, and Planning in AI

By Blai Bonet

Abstract

Planning, or the use of predictive models for generating goal-directed behaviors is a key capability of flexible, intelligent agents.The research challenges in planning are of two types. One is algorithmic:how to plan is presence of complex models with many variables.The other is representational: how to learn the models from experience. In this talk, I will review these central problems in AI, from the perspective of generalized planning, where plans represent general  strategies for solving a whole family of problem, and which connects with current work in learning. I'll look at the formulation of generalized planning, at the representation challenge that it raises, and at the structural learning methods that are being developed.

Biography

Blai Bonet is a professor in the computer science department at Universidad Simón Bolívar, Venezuela. He received a Ph.D. degree in computer science from the University of California, Los Angeles. His research interests are in the
areas of automated planning, heuristic search, and knowledge representation. Blai has received two ICAPS Influential Paper Awards for pioneering work on automated planning, and other best paper awards. He is a co-author (with Hector Geffner) of the book titled "A Concise Introduction to Models and Methods for Automated Planning." Blai Bonet is an Associate Editor of Artificial Intelligence and the Journal of Artificial Intelligence Research. He served as Conference co-Chair of ICAPS-12 and as Program co-Chair of AAAI-15, and he is a member of the AAAI Executive Council.

Host: Ralph Andrzejak

February 2019  
February, 28th 
 
15.30 h
 
55.309

PhD Research Seminar

Statistical course and Design of Experiments 

By  Simone Tassani

Abstract

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.

The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis.
Than the first part of the course will follow introducing General Linear Modelling and its most common applications: F-test, Monofactorial Analysis of Variance (ANOVA) 
 
Biography
 
Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group.
February, 28th 
 
12.00 h
 
55.309

Invited Research Seminar

A Theory of Regularized Markov Decision Processes 

by Matthieu Geist

Abstract

Many recent successful (deep) reinforcement learning algorithms make use of regularization, generally based on entropy or on Kullback-Leibler divergence. We propose a general theory of regularized Markov Decision Processes that generalizes these approaches in two directions: we consider a larger class of regularizers, and we consider the general modified policy iteration approach, encompassing both policy iteration and value iteration. The core building blocks of this theory are a notion of regularized Bellman operator and the Legendre-Fenchel transform, a classical tool of convex optimization. This approach allows for error propagation analyses of general algorithmic schemes of which (possibly variants of) classical algorithms such as Trust Region Policy Optimization, Soft Q-learning, Stochastic Actor Critic or Dynamic Policy Programming are special cases. This also draws connections to proximal convex optimization, especially to Mirror Descent.

Biography

Matthieu Geist obtained an Electrical Engineering degree and an MSc degree in Applied Mathematics in Sept. 2006 (Supélec, France), a PhD degree in Applied Mathematics in Nov. 2009 (University Paul Verlaine of Metz, France) and a Habilitation degree in Feb. 2016 (University Lille 1, France). Between Feb. 2010 and Sept. 2017, he was an assistant professor at CentraleSupélec, France. In Sept. 2017, he joined University of Lorraine, France, as a full professor in Applied Mathematics (Interdisciplinary Laboratory for Continental Environments, CNRS-UL). Since Sept. 2018, he is on secondment at Google Brain, as a research scientist (Paris, France). His research interests include machine learning, especially reinforcement learning and imitation learning.

Host: Gergely Neu

February, 26th 
 
17.30 h
 
Auditorium

Invited Research Seminar

Deep Reinforcement Learning with demonstrations  

by Olivier Pietquin

Abstract

Deep Reinforcement Learning (DRL) has recently experienced increasing interest after its success at playing video games such as Atari, DotA or Starcraft as well as defeating grand masters at Go and Chess. However, many tasks remain hard to solve with DRL, even given almost unlimited compute power and simulation time. These tasks often share the common problem of being "hard exploration tasks". In this talk, we will show how using demonstrations (even sub-optimal) can help in learning policies that can reach human level performance or even super-human performance on some of these tasks, especially the remaining unsolved Atari games or human-machine dialogues.

Biography

Olivier Pietquin obtained an Electrical Engineering degree from the Faculty of Engineering, Mons (FPMs, Belgium) in June 1999 and a PhD degree in April 2004. In 2011, he received the Habilitation à Diriger des Recherches (French Tenure) from the University Paul Sabatier (Toulouse, France). Between 2005-2013, he was a professor at the Ecole Superieure d'Electricite (Supelec, France), and subsequently joined the University Lille 1 as a full professor in 2013. In 2014, he has been appointed at the Institut Universitaire de France as a junior fellow. He is now on leave with Google, first at Google DeepMind in London and, since 2018, with Brain in Paris. His research interests include spoken dialog systems evaluation, simulation and automatic optimisation, machine learning (especially direct and inverse reinforcement learning), speech and signal processing. Title: Deep Reinforcement Learning with demonstrations Abstract: Deep Reinforcement Learning (DRL) has recently experienced increasing interest after its success at playing video games such as Atari, DotA or Starcraft as well as defeating grand masters at Go and Chess. However, many tasks remain hard to solve with DRL, even given almost unlimited compute power and simulation time. These tasks often share the common problem of being "hard exploration tasks". In this talk, we will show how using demonstrations (even sub-optimal) can help in learning policies that can reach human level performance or even super-human performance on some of these tasks, especially the remaining unsolved Atari games or human-machine dialogues. Web: https://ai.google/research/people/105812 http://www.lifl.fr/~pietquin/

Host: Gergely Neu

February, 26th 
 
12.30 h
 
Room 55.309

PhD Research Seminar

Facial Analysis for Emotions, Interaction and Beyond

By Federico Sukno

Abstract

In this talk I will present our research in facial analysis over the last 4 years. I will start by motivating the interest in facial analysis for diverse applications, briefly covering the more traditional ones related to identity recognition for law enforcement and to the automatic recognition of facial expressions. The latter has become especially relevant in the last few years, given its importance for the understanding of human behavior and for advanced human-computer interaction. This will be showcased from specific research work done in our group in automatic head pose estimation, emotion recognition (both from discrete and dimensional approaches) and automatic lip reading.

In the second part of the talk, I will discuss other emerging applications that go beyond the traditional analysis of identity and expressions to target extracting more subtle information from the face. Some of this information, however, might be not apparent or it might even be hidden to us, and it could only be recovered by means of specialized techniques. This will be showcased from applications in photoplethysmography, facial asymmetries, craniofacial dysmorphologies and human factors.

Biography

Dr Federico Sukno is a Ramón y Cajal Fellow at UPF. He received the degree in electrical engineering at La Plata National University (Argentina, 2000) and the Ph.D. degree in biomedical engineering at Zaragoza University (Spain, 2008). His research activity has been framed in the field of image analysis with statistical models of shape and appearance, targeting diverse applications, most of which related to facial analysis. He is the author or co-author of more than 60 peer-reviewed publications, including 21 journal publications (from which 16 are Q1 journals and 10 are in the top-ranked journals in the fields of artificial intelligence and medical imaging, e.g. IEEE T Pattern Anal, IEEE T Med Imaging, IEEE T Image Process, IEEE T Cybernetics, Int J Comput Vision, Med Image Anal, Pattern Recogn). He has participated in 4 national and 5 international research projects (FP6, FP7, H2020 and Welcome Trust), as well as in 5 technology transfer projects acting as coordinator or PI in several of them. He has been a Marie Curie and a Ramon & Cajal fellowships in 2012 and 2015, which constitute two highly-competitive and prestigious individual grants in the EU and the Spanish systems, respectively.

February, 22nd 
 
15:30 h
 
Room 55.309

PhD Research Seminar

euCanSHare: Bypassing the long and winding road towards “true” big data in biology, medicine and beyond

By Karim Lekadir

Abstract

The big data revolution continues to have a transformative effect on research and innovation in a wide range of scientific and societal domains. In computer vision, for example, databases such as ImageNet now include tens of millions of images from tens of thousands of semantic categories, leading every year to important methodological advances and technological applications. However, in other domains such as in biomedicine, the promise of big data is faced with ethical/legal, operational and financial constraints, which have made it a very hard challenge to establish large-scale research databases covering multiple data types and populations. In this talk, I will first present the euCanSHare H2020 project, which aims at addressing the lack of large heterogeneous databases (including biological, imaging and clinical data), by developing the information technology tools and the data science algorithms that will enable to integrate and co-analyse multiple smaller databases, thus totalling an unprecedented 1,000,000 records. I will also describe the computational challenges and investigated solutions to enable automated and robust large-scale, multi-type and multi-cohort data analysis like never before. I will list emerging opportunities that the euCanSHare project will offer for personalised medicine and translational research. I will conclude with future perspectives in integrative data science at UPF for bypassing the long and winding road towards “true” big data in biology, medicine and beyond.

Biography

Dr Karim Lekadir is a Ramon y Cajal researcher at the Barcelona Centre for New Medical Technologies, Universitat Pompeu Fabra, Barcelona. He received a PhD in Computing from Imperial College London and was a postdoctoral researcher at Stanford University, USA. His algorithm developed during his PhD for cardiac functional quantification has been FDA/CE marked and is used in more than 250 clinical centres worldwide. He participated in several EU projects in the field of computational biomedicine, including the euHeart project for computational modelling of personalised interventions in cardiology. Through his work on statistical shape modelling using partial least squares, he finished in the first position of the MICCAI 2015 Challenge on myocardial infarct classification. His current research focuses on the development of data science, machine learning and image computing approaches for the integrative analysis of large-scale biomedical data. He is currently the Project Coordinator of the euCanSHare H2020 project (2018-2022) funded by the European Commission (6 million Euros), leading a consortium of 16 institutions to address data sharing and big data approaches in cardiovascular personalised medicine. He is an Associate Editor of the IEEE Transactions on Medical Imaging and a Guest Associate Editor on the Frontiers Special Issue on Artificial Intelligence and Cardiac Imaging.

February, 21st 
 
15:30 h
 
Room 55.309
Invited Research Seminar
 
Grades in the Machine: What Machine Learning Means for Cognitive Models
 
By Charles Lang, Columbia University 
 
Abstract
 
Regardless of the specific algorithmic methodology employed, building an intelligent agent involves the reduction of complex data into a lower dimensional representation that the machine can use to make predictions about the world. For an autonomous vehicle the machine must reduce complex sensor inputs into representations about the physical surroundings. Within education technology applications this means creating representations of students from student data. As these models become more sophisticated and begin modeling cognitive ability and other psycho-social constructs it is important that we ask critical questions about the use and meaning of these machine representations within educational contexts. Machine representations have substantial similarities with older data representations of students such as grades, standardized tests and rubric scoring, but differ in one important way, the number of dimensions that inferences may be based on. High dimensional representations may create problems for educational organizations (for example, they are not human interpretable) while at the same time the new representations do not solve any of the well documented social, cultural, political and pedagogical tensions inherent in older formats.
 
Biography
 
Charles Lang is Visiting Assistant Professor in Learning Analytics at Teachers College, Columbia University where he is co-Director of the Masters of Science in Learning Analytics. His research interests center on the use of big data in education and the role of online assessment data in understanding student learning. Specifically, Charles studies innovative methodologies for assessing student learning (predictive analytics, personalization and graphical models of knowledge) and how these new tools can be incorporated into instructional workflow.
 
Host Davínia Hernández-Leo
February, 14th  
 
15:30 h
 
Room 55.410

PhD Research Seminar

Ethics working with social media

By Carlos Castillo

Abstract

Online social data such as user-generated content, expressed or implicit relationships between people, and behavioral traces are at the core of many popular web applications and platforms, driving the research agenda of many researcher in both academia and industry. The promises of social data are many, including the understanding of “what the world thinks” about a social issue, brand, product, celebrity, or other entity, as well as enabling be er decision-making in a variety of elds including public policy, healthcare, and economics.

However, many academics and practitioners are increasingly warning against the naive usage of social data. The seminar will mostly focus on the ethical boundaries and unexpected consequences that are overlooked. Such an overlook can lead to wrong or inappropriate results that can be consequential.

Biography

Carlos Castillo is a Distinguished Research Professor at Universitat Pompeu Fabra in Barcelona. He is a web miner with a background on information retrieval, and has been influential in the areas of crisis informatics, web content quality and credibility, and adversarial web search. He is a prolific researcher with more than 75 publications in top-tier international conferences and journals, receiving a test-of-time award, two best paper awards, two best student paper awards, 11,000+ citations and having an h-index of 52. His works include a book on Big Crisis Data, as well as monographs on Information and Influence Propagation, and Adversarial Web Search.

Carlos received his Ph.D from the University of Chile (2004), and was a visiting scientist at Universitat Pompeu Fabra (2005) and Sapienza Universitá di Roma (2006) before working as a scientist and senior scientist at Yahoo! Research (2006-2012), as a senior scientist and principal scientist at Qatar Computing Research Institute (2012-2015), and as director of research for data science at Eurecat (2016-2017).

He has served in the Program Committee (PC) or Senior PC (SPC) of all major conferences in his area (WWW, WSDM, SIGIR, KDD, CIKM, etc.), and is part of the editorial committee of ACM Transactions on the Web and ACM Transactions in Social Computing He has been PC Co-Chair of ACM Digital Health 2016, 2017, and 2018 and of WSDM 2014; co-organized the Adversarial Information Retrieval Workshop and Web Spam Challenge in 2007 and 2008, the ECML/PKDD Discovery Challenge in 2010 and 2014, the Web Quality Workshop from 2011 to 2014, and the Social Web for Disaster Management Workshop in 2015, 2016, and 2018. He is an ACM Senior Member, an IEEE Senior Member, and an advanced researcher accredited by AQU in Catalonia.

More information including recent publications: http://chato.cl/research/

February, 12th  
 
12:00 h
 
Room 55.309
PhD Research Seminar

Introduction to PhD program and PhD seminars for newcomers

By Aurelio Ruiz
 
Abstract
 
Special introductory session to the PhD program and PhD seminars for the students having arrived after the initial session that took place in October 2018
Biography
 
Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program.
February, 11th  
 
17:00 h
 
Room 55.309

Invited Research Seminar

Music Recommendation - Current state-of-the-art and challenges

By Fabien Gouyon

Abstract

In this talk I will present an overview of recommendation systems in the music streaming industry. We will go over the practical case of playlist generation and station continuation. I'll also highlight what I think are interesting challenges in this field. Let's make it interactive and discuss your own questions!

Biography

Fabien Gouyon leads Pandora’s data science research team in Europe, working on Music Information Retrieval, Recommender Systems, and Natural Language Processing, and applying research to personalized music recommendation. Before joining Pandora, he received a PhD in Computer Science from Universitat Pompeu Fabra and was a co-founder of Barcelona Music and Audio Technologies (BMAT), worked in the Austrian Research Institute for Artificial Intelligence in Vienna, and started and led the Sound and Music Computing Group while teaching at the University of Porto.

Host: Xavier Serra

February, 11th  
 
15:30 h
 
Room 55.309

PhD Research Seminar

Paradigmatic Research Challenges in IoT Systems Engineering 

By  Schahram Dustdar

Abstract

This talk explores the research challenges in the domain of IoT from multiple angles and reflects on the urgently needed collective efforts from various research communities to collaborate on those. Our approach fundamentally challenges the current thinking and understanding of scientific, technological, and political paradigms in tackling the engineering of IoT systems. We discuss technical paradigms and research challenges in the domains of Cloud and Edge Computing as well as the requirements of people in such systems. We will explore how these novel approaches impact application composition utilizing AI and Edge Computing.

Biography

Schahram Dustdar is Professor of Computer Science heading the Distributed Systems Group at the Technical University of Vienna. From 2004-2010 he was also Honorary Professor of Information Systems at the Department of Computing Science at the University of Groningen (RuG), The Netherlands. From 1999 - 2007 he worked as the co-founder and chief scientist of Caramba Labs Software AG in Vienna (acquired by Engineering NetWorld AG), a venture capital co-funded software company focused on software for collaborative processes in teams. Caramba Labs was nominated for several (international and national) awards: World Technology Award in the category of Software (2001); Top-Startup companies in Austria (Cap Gemini Ernst & Young) (2002); MERCUR Innovationspreis der Wirtschaftskammer (2002).

From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January until June 2017 he was a Visiting Professor at UC Berkeley, USA. He is co-Editor-in-Chief of the new ACM Transactions on the Internet of Things as well as Editor-in-Chief of Computing (Springer). He is an Associate Editor of IEEE Transactions on Services Computing, IEEE Transactions on Cloud Computing, ACM Transactions on the Web, and ACM Transactions on Internet Technology, as well as on the editorial board of IEEE Internet Computing and IEEE Computer. Dustdar is recipient of the ACM Distinguished Scientist award (2009), the IBM Faculty Award (2012), an elected member of the Academia Europaea: The Academy of Europe, where he is chairman of the Informatics Section, as well as an IEEE Fellow (2016).

February, 7th  
 
15:30 h
 
Room 55.309

Invited Research Seminar

The forces that drive cells

By Xavier Trepat

Abstract

Cells exert, sense, and respond to physical forces through an astounding diversity of mechanisms. I will discuss some of these mechanisms in the context of tissue growth, migration and division. I will present maps of cell-cell and cell-extracellular matrix (ECM) forces during cell migration and division in a variety of epithelial models, from the expanding MDCK cluster to the regenerating zebrafish epicardium. These maps revealed that migration and division in growing tissues are jointly regulated. I will also present direct measurements of epithelial traction, tension, and luminal pressure in three-dimensional epithelia of controlled size and shape. By examining epithelial tension over time-scales of hours and for nominal strains reaching 1000%, we establish a remarkable degree of tensional homeostasis mediated by superelastic behavior.

Biography

Xavier Trepat received a BSc in Physics in 2000 and a B.Sc in Engineering in 2001. In 2004 he obtained his PhD from the Medical School at the University of Barcelona. He then joined the Program in Molecular and Integrative Physiological Sciences at Harvard University as a postdoctoral researcher. In 2008 he became a Ramon y Cajal researcher at the University of Barcelona and the Institute for Bioengineering of Catalonia (IBEC), and in January 2011 he became an ICREA Research Professor. His research at IBEC focuses on integrative tissue dynamics and cytoskeletal mechanics.

Host Ralph Andrzejak

February, 7th  
 
12:30h
 

Room 55.410

Invited Research Seminar

Integrative machine learning methods for the analysis of heterogeneous data in prospective neurodegeneration studies

By Marco Lorenzi, INRIA Researcher

Abstract

Modeling the relationship among heterogeneous data is essential in clinical studies, where understanding the dynamics of neurodegeneration requires to jointly account for the heterogeneity of demographic, clinical, and imaging data, along with confounders from biology and genetics. While integrative approaches based on machine learning are finding increasing application for the analysis of heterogeneous data, their clinical applications if often frustrated by the lack of interpretability and robustness of the findings. 
 
The aim of this presentation is to illustrate our contribution towards interpretable and robust machine learning approaches for the analysis of data from neurodegeneration studies. In particular, we will focus on approaches for the automatic identification of the joint relationship among high-dimensional biomarkers, such as imaging, genetics and neuropsychological tests. Moreover, we will illustrate our advances in the modelling of the long-term natural history of the pathology from short-term longitudinal observations from clinical trials. We will show how our methods can automatically identify plausible progressions of several disease progression biomarkers, including full resolution medical-images from different modalities.  We will finally show how our methods can be used as statistical reference for automatic staging and prediction in unseen clinical trial data.
 

Machine Learning and Biophysical Modelling: Learning by Heart

By Maxime Sermesant, INRIA Researcher

Abstract

Machine learning and biophysical modelling are very complementary approaches. The recent progress in computing power and available data makes it possible to develop accurate data-driven approaches for healthcare, while biophysical models offer a principled way to introduce physiological constraints. In this talk I will present research where we combined both in different ways in order to leverage on their strengths. Different clinical applications in computational cardiology will be presented.
 

Exploring the heart-brain synergies in a large-population database

By Jaume Banús Cobo, INRIA Researcher
 

Abstract

Cerebrovascular diseases and neurodegeneration have been associated with a variety of heart diseases like heart failure or atrial fibrillation, and share with them several cardiovascular risk factors.These connections suggest a common underlying pathological process linking cardiac function with brain atrophy. Better understanding these synergies would represent a crucial step towards prevention and treatment. 

Current large data collection initiatives such as the UK Biobank provide us with joint cardiac and brain imaging information for thousands of individuals, and represent a unique opportunity to gain insight about the link between heart and brain pathophysiology. 
We explore this connection using cardiovascular indicators, such as ejection fraction and stroke volume, and brain volumetric features extracted from MRI images. Associations are investigated following data-driven approaches, through univariate and multivariate statistical association analysis, as well as model-driven methods. In particular, we propose to explore the influence of the brain features in the estimation of cardiovascular parameters from a 0-D model used to characterize the heart function and the systemic circulation.
January 2019  
January, 24th  
 
11:00h
 

Room 52.119 

PhD Research Seminar

Software development best-practices for reproducible research

By  Alastair Porter

Abstract

In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups. A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time. For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time. In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available.

January, 24th  
 
11:00h
 

Room 52.s29 

Invited Research Seminar

Introduction to computational musicology with hands-on case studies for non-western music traditions

By Barış Bozkurt , Assoc. Prof. of Electrical Engineering at Izmir Democracy University, Turkey.

Abstract

The main goal of this tutorial is to present an overview for computational analysis applied on non-Western music traditions, mostly within the context of the CompMusic project (https://compmusic.upf.edu/). The target audience is researchers and students interested in computational musicology. The tutorial will start by presenting some of the relevant problems and challenges for analysis of non-Western music traditions that have been studied from an MIR perspective. We will present resources created during the CompMusic project, that are openly available to the community and demonstrate accessing non-Western music data and processing these data (focusing on intonation analysis) with publicly available tools. We will consider research corpora from various music traditions: Hindustani (North India), Carnatic (South India) and Turkish-makam (Turkey).  This session would serve as a quick start for students and researchers without prior experience in analysis of non-Western music and will provide them a good entry point for further investigation. 

Biography

Barış Bozkurt is an Assoc. Prof. of Electrical Engineering at Izmir Democracy University, Turkey. He is a collaborator of the Music Technology Group at the Universitat Pompeu Fabra in Barcelona since 2011. He has obtained his PhD degree (on speech analysis) in 2005 from Faculte Polytechnique De Mons, Belgium and also worked in speech industry after his PhD. Since 2007, he has been teaching in Electrical Engineering and Computer Science departments, and carrying research in the fields of audio signal processing and computational musicology.

Host:  Xavier Serra

January, 18th  
 
11:00h
 

Room 55.309

Invited Research Seminar

Fusion of images

By Enric Meinhardt-Llopis, École Normale Supérieure de Paris-Saclay

Abstract

The problem of image fusion consists in producing an ideal image of an object from several images of the object that are incomplete, deformed, blurry, noisy and with strong illumination changes.  This general problem contains as particular cases the problems of image registration, denoising, deblurring and inpainting.  We showcase three applications (1) the virtual periscope, that allows to see through the surface of turbulent water; (2) museum photography, to obtain clean and complete images of artwork from several incomplete and slanted photos; (3) reconstruction of asteroid surfaces, to combine inconsistent 3D models of an asteroid obtained from parallax and from shape-from-shading into a single coherent surface.  The fusion of N images always becomes a trivial problem in the limit when N goes to infinity; however in practice we are interested in the limit when N goes to 1.  We will see that, under rather mild hypotheses, the fusion of a small number of images is still a well-posed problem. 

Biography

Enric Meinhardt-Llopis is an associate professor at the École Normale Supérieure de Paris-Saclay.  After completing his studies in mathematics at the Universitat Politècnica de Catalunya, he obtained his PhD degree from the Universitat Pompeu Fabra in 2011, under the direction of Professor Vicent Caselles.  Now he is working in the image processing group of Professor Jean-Michel Morel, mostly in the analysis and exploitation of optical and radar satellite images. 

Host:  Coloma Ballester

January, 17th  
 
15:30h
 

Room 55.410

PhD Research Seminar

Introduction to Copyright in ICT

By Brisa Burriel Fuster, UPF. 

Abstract

We'll share the most relevant concepts of Copyright Law, and learn from popular cases, so we can have an idea of what is important to consider in our day to day.

Biography

I work as R&D and IT Legal Adviser at the UPF with a strong focus on Technology Transfer from the Public to the Private sector. My aim is to help organizations reaching the highest standards of valorization and exploitation of research results through IPRs awareness activities, as well as designing and implementing effective processes and best practices.

January, 9th  

11:00h

Room 55.309

Invited Research Seminar

Asynchronous Provably-Secure Hidden Services (CT-RSA 2018)

By Philippe Camacho , R&D engineer for Enuma Technologies

Abstract

The client-server architecture is one of the most widely used in the Internet for its simplicity and flexibility. In practice the server is assigned a public address so that its services can be consumed. This makes the server vulnerable to a number of attacks such as Distributed Denial of Service (DDoS), censorship from authoritarian governments or exploitation of software vulnerabilities. In this work we propose an asynchronous protocol for allowing a client to issue requests to a server without revealing any information about the location of the server. In addition, our solution reveals limited information about the network topology, leaking only the distance from the client to the corrupted participants. We also provide a simulation-based security definition capturing the requirement described above. Our protocol is secure in the semi-honest model against any number of colluding participants, and has linear communication complexity. Finally, we extend our solution to handle active adversaries. We show that malicious participants can only trigger a premature termination of the protocol, in which case they are identified. For this solution the communication complexity becomes quadratic. To the best of our knowledge our solution is the first asynchronous protocol that provides strong security guarantees.

Biography

Philippe Camacho got his PhD at the University of Chile and is currently working as a R&D engineer for Enuma Technologies, a blockchain company. His research interests include authenticated data structures, anonymity protocols and cryptocurrencies.

Host: Carla Ràfols 
December
December, 20th  
 
15:30 h
 
Room 55.410

Invited Research Seminar

Convex optimisation and applications

By Victor Valls, Trinity College Dublin

Abstract

Convex optimisation is a subfield of mathematical optimisation that plays a central role in many areas, such as automatic control, finance, or statistical learning. In this talk, I will first give a non-technical introduction to convex optimisation, which will cover the basic concepts, some of its algorithms, and canonical applications in machine learning and image processing. In the second part of the talk, I will focus on recent applications of convex optimisation to the areas of networking and control. In particular, on how to solve max-flow type problems with stochastic constraints while making discrete actions. Some specific applications of the latter include energy minimisation in wireless networks, scheduling in queueing systems, and traffic signal control with constrained decisions. 

Biography

Victor Valls is a research fellow at Trinity College Dublin (Ireland) working in the group of Prof. Iosifidis. He obtained his degree and MSc in engineering from Universitat Pompeu Fabra (Barcelona) in 2011 and 2012 respectively, and PhD in applied mathematics from Trinity College Dublin in 2017. His research interests are in the area of mathematical optimisation, with applications in networks, control and machine learning. He has been recently awarded an MSCA global fellowship (FANC; 795244) with Yale University (USA) and Trinity College Dublin, which he will start in 2019. 

Host: Boris Bellalta

December, 13
 
15:30 h
 
Room 55.309

PhD Research Seminar

Reproducibility in research.

By Aurelio Ruiz

Abstract

We will use excerpts of the talk by Victoria Stodden at the María de Maeztu Strategic Research Program (available at https://www.upf.edu/web/mdm-dtic/reproducibility-in-research ) to discuss one of the objectives of this program, which is “to increase the impact of our research by increasing the impact of the publications, datasets and software tools, and take advantage of this impact to establish and consolidate partnerships”. We will discuss ways to promote that the research results, datasets and tools are discoverable, interpretable and reusable, including the publication of the data and software together with the publications. During this session, we will discuss some of the topics linked to "reproducible research", including also the increasing external requirements in making datasets and computer code available by funding agencies, publishers and potential mechanisms to promote it in our organisation.

Suggested reading
 

-Reproducible Research in Signal Processing - What, why, and how. Vandewalle, Patrick; Kovacevic, Jelena; Vetterli, Martin. IEEE Signal Processing Magazine (ISSN: 1053-5888), vol. 26, num. 3, p. 37-47. Institute of Electrical and Electronics Engineers, 2009

-Ongoing draft document within MdM for good practices for discussion in this link

-For a survey on NIPS participants and motivations (2008): "The Scientific Method in Practice: Reproducibility in the Computational Sciences", Stodden, Victoria. MIT Sloan Research Paper No. 4773-10.

Biography

Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program.

December, 3rd  
 
15:30 h
 
Room 55.410

Invited Research Seminar

Tangible Interaction and Cultural Forms: Supporting Learning in Informal Environments

By Dr. Michael Horn, Northwestern University

Abstract

Designers who create computer-based learning experiences for places like museums, out-of-school programs, and homes face a number of challenges related to the informal nature of such settings. Designs must generally function on their own without the support of teachers or curriculum while at the same time engaging a diverse audience, supporting productive social interaction, and activating appro- priate prior knowledge and skills. In this talk, I present an approach to the design of informal learning experiences based on tangible interaction. The term tangible refers to a variety of human–computer interaction techniques that move beyond computer screens and create opportunities for people to interact with digital systems using their bodies and physical artifacts. I argue that tangible interaction creates unique opportunities for designers to shape objects and situations to evoke cultural forms of literacy, learning, and play. To illustrate these arguments, I describe design cases that colleagues and I have created to support learning in museums and homes.

Biography

Michael Horn is an Associate Professor of Computer Science and Learning Sciences at Northwestern University where he directs the Tangible Interaction Design and Learning (TIDAL) Lab. Michael serves as the Program Coordinator for the Learning Sciences PhD Program at Northwestern and is co-Founder of the new Joint PhD Program in Computer Science and Learning Sciences. Michael's research explores the use of interactive technology in the design of innovative learning experiences. He takes a cautious but optimistic stance towards technology in a process that tightly couples research and design. His work has been exhibited at museums around the world including the California Academy of Sciences (San Francisco), the Museum of Science (Boston), the Field Museum (Chicago), and the Computer History Museum (Silicon Valley). Michael's research on tangible programming has contributed to the commercial products: Osmo Coding (https://www.playosmo.com/en/coding/) and Kibo Robotics (http://kinderlabrobotics.com/kibo/). Michael earned his Ph.D. in Computer Science at Tufts University working in the Human-Computer Interaction Lab and the Developmental Technologies research group. He received his undergraduate degree in Computer Science from Brown University and has worked as a software engineer for several companies including Classroom Connect and iRobot Corporation.

Host: Narcís Parés

November  
November 29th
 
15:30 h
 
Room 54.003

PhD Research Seminar

UPF- Library for PhD students 

By Gemma Alvarez

Host:Aurelio Ruiz

November 29th
 
15:30 h
 
Room 55.309

Invited Research Seminar

How do people explore virtual environments?  

By Belén Masía, Universidad de Zaragoza

Abstract

Virtual reality (VR) systems provide a new medium that has the potential to have a significant impact on our society. The experiences offered by these emerging systems are inherently different from radio, television, or theater, opening new directions in research areas such as cinematic VR capture, interaction, or content gener ation and editing. However, the behavior of users who visually explore immersive VR environments is not well understood, nor do statistical models exist to predict this behavior. Yet, with unprecedented capabilities for creating synthetic immersive environments, many important questions arise. How do we design 3D scenes or place cuts in VR videos? How do we drive user attention in virtual environments? Can we predict visual exploration patterns? How can we efficiently compress cinematic VR content?

To address these and other questions from first principles, it is crucial to understand how users explore virtual environments. In this talk, I will go through our work on analyzing user behavior in cinematic VR scenarios.

Biography

Dr. Belen Masia is an Assistant Professor in the Computer Science Department at Universidad de Zaragoza, and a member of the Graphics & Imaging Lab of the I3A Institute. Prior to that, she was a postdoctoral researcher at MPI Informatik, and a member of the Max Planck Center for Visual Computing and Communication.

Her research interests span Computational Photography, Computational Displays and Applied Perception. Including: perception of appearance, stereo and multiview displays, light field editing, scene understanding and (simple/low-cost) light source and appearance acquisition and editing.

Host: Marcelo Bertalmio

November 26th
 
15:30 h
 
Room 55.309

PhD Research Seminar

"How do agile practice support organizing a PhD"  

By Eva-Maria Schön
 
Abstract
Working on a PhD is an iterative process. In the beginning, the outcome is not clearly defined and results are delivered in an incremental manner. The characteristics of research work are comparable to the ones of Agile Software Development (ASD). Both domains focus on knowledge work instead of repetitive production activities. Agile methodologies like Scrum, Kanban or Extreme Programming (XP) are composed of best practices known as agile practices and address specific aspects of organizing work with the aim of continuous improvement. This correlation between ASD and research work motivated me to use agile practices for organizing my PhD, since I am a passionate practitioner of the agile movement. The talk reflects my experience as a PhD student and discuss how agile practices were applied for organizing my research work.
 
Biography
Eva-Maria Schön has many years of practical experience in the development of digital products by means of agile product development. She supports teams in continuously improving themselves and reflecting their own working methods. She received the PhD degree in computer science from the University of Seville (Spain) in 2017.
November 23rd  
 
15:30 h
 
Room 55.309

Invited Research Seminar

Automatic Assessment of Student Music Performances

By Alexander Lerch, Georgia Institute of Technology


Abstract

While there is large interest in Music Information Retrieval tasks focusing on extracting score-like information such as pitches, chords, and rhythmic properties, less attention is being paid to performance information such as (micro-)tempo, intonation, and dynamics.
This presentation will look at Music Performance Analysis from the perspective of assessing student music performances. The possibilities and limitations of current data-driven approaches to the assessment of middle and high school students will be discussed based on real-world results on a large dataset of graded student recordings.

Biography

Alexander Lerch is Assistant Professor at the Georgia Tech Center for Music Technology, where he leads the music informatics group. He is working on new artificially intelligent technologies for accessing, producing, and listening to music. His main research field is called Music Information Retrieval (MIR), an emerging interdisciplinary field. He is Co-Founder of the company zplane.development, a research-driven technology provider for the music industry. His book “An Introduction to Audio Content Analysis,” published by Wiley/IEEE Press, is used as course text book in multiple institutions.

More: https://www.alexanderlerch.com/

November 22th  
 
15:30 h
 
Room 55.309

PhD Research Seminar

Introduction to ethical issues in research

By Josep Blat and Marta Rodríguez (CIREP).
 
Abstract

The Institutional Commission for Ethical Review of Projects (CIREP-UPF) established in December 2014 wants to contribute to the improvement within the UPF community, of ethical standards and personal data protection in research activities and academic practices related to human beings.  Among other CIREP is in charge of evaluating research projects subject to ethics review and give its approval by issuing mandatory favourable reports.  The seminar will provide an overview on the key aspects to take into account to guarantee that the research conducted at the department meets the highest international ethical standards.

November 15th  
 
15:30 h
 
Room 55.410

PhD Research Seminar

Computational Cluster at DTIC

November 14th  
 
11:00 h
 
Room 55.003

Invited Research Seminar

General-purpose audio tagging using deep learning approaches  

by Il-Young Jeong, Cochlear.ai
 
Abstract
In this talk, I will explain the techniques and models applied to the submission of Cochlear.ai team for DCASE 2018 task 2: General-purpose audio tagging of Freesound content with AudioSet labels. We mainly focused on how to train deep learning models efficiently against strong augmentation and label noise. First, we conducted a single-block DenseNet architecture and multi-head softmax classifier for efficient learning with mixup augmentation. For the label noise, we applied the batch-wise loss masking to eliminate the loss of outliers in a mini-batch. We also tried an ensemble of various models, trained by using different sampling rate or audio representation.
 
Biography 
Il-Young Jeong is a co-founder and research scientist at Cochlear.ai. He holds a B.S. degree in Electrical Engineering and received M.E. from Intelligent Information Processing laboratory, Sogang University. His primary interest was digital signal processing for speech recognition systems. During his PhD study at the Music and Audio Research Group, Seoul National University, he sought to expand his research area into general audio signals such as music and sound events.

November 13th

16:00h 

Room 55.003

Invited Research Seminar

From biomechanics to sound: status and challenges in the numerical simulation of voice 

by Oriol Guasch, GTM Grup de recerca en Tecnologies Mèdia

 

Abstract

Muscle activations position the articulators, which define a vocal tract geometry and posture the vocal folds. Air emanating from the lungs induces self-oscillations of the vocal folds, which result in aeroacoustic sources and the subsequent propagation of acoustic waves inside the vocal tract. There, many things could happen. For instance, the air could resonate to generate vowels, or, at constrictions, airflow may be accelerated to create turbulent sounds such as fricatives. The vocal tract walls are flexible and react to the inner acoustic pressure. Also, articulators can change the vocal tract geometry to generate vowel-vowel utterances or syllables. Sound is finally radiated from the mouth. Numerical methods have revealed as a very powerful tool for the realistic simulation of all those complex phenomena. However, attempting unified 3D numerical simulations of all the above processes, which involve coupling of a biomechanical model and the mechanical, fluid and acoustic field interactions, may seem unwise. Unified approaches have been shunned for their daunting complexity and high-performance parallel computation requirements. This situation now seems to be changing. In this talk, we briefly review recent approaches towards 3D realistic voice simulation that unify, at least to some extent, some of the involved physical fields. Remaining challenges will be highlighted. 

 

Biography

Oriol Guasch holds a five-year degree in Physics from the University of Barcelona and a PhD in Computational Mechanics and Applied Mathematics from the Polytechnic University of Catalonia. He worked for several years in industry but definitely moved to academics in 2007. He is currently a full professor at the Department of Engineering, La Salle, University Ramon Llull, where he heads the research on acoustics within the GTM (Grup de recerca en Tecnologies Mèdia). His research lines involve computational acoustics and aeroacoustics with special emphasis on numerical voice production, graph theory applied to mid and high frequency vibroacoustics, theoretical and experimental transmission path analysis, parametric array technology to generate audible sound from ultrasonic collimated beams and acoustic black holes in beams, plates and ducts. He has authored a significant number of papers in first rank international scientific journals and conferences, where he has organized and chaired many special sessions. He has also participated and been the principal investigator of several national and international projects, and recently led the scientific coordination of the EUNISON (Extensive Unified-Domain Simulation of the Human Voice) project, EU-FET no 308874.

November  9th

12:00 h

Room 52.213

Invited Research Seminar

On Deep Learning and Music

by Kyle McDonald 

Abstract

The last five years have seen incredible results from machine learning using modern neural networks, also called Deep Learning. Some of this research has presented completely new ways of working with digital media including sound and images. I will provide an informal survey of new approaches to music composition and sound synthesis based on neural networks, including some of my own work in this direction.

Biography

Kyle McDonald is an artist working with code. He is a contributor to open source arts-engineering toolkits like openFrameworks, and builds tools that allow artists to use new algorithms in creative ways. He has a habit of sharing ideas and projects in public before they're completed. He creatively subverts networked communication and computation, explores glitch and systemic bias, and extends these concepts to reversal of everything from identity to relationships. Kyle has been an adjunct professor at NYU's ITP, and a member of F.A.T. Lab, community manager for openFrameworks, and artist in residence at STUDIO for Creative Inquiry at Carnegie Mellon, as well as YCAM in Japan. His work is commissioned by and shown at exhibitions and festivals around the world, including: NTT ICC, Ars Electronica, Sonar/OFFF, Eyebeam, Anyang Public Art Project, Cinekid, CLICK Festival, NODE Festival, and many others. He frequently leads workshops exploring computer vision and interaction.

November 9th

 9:30 h

 Auditorium

Campus Poblenou

Jornada:  Innovació tecnològica a les ciutats

Jornada destinada al debat i exposició sobre tecnologies emergents i el seu impacte en les ciutats i el ciutadà. La jornada consta de dues taules rodones i una xerrada inspiracional on investigadors, empreses, emprenedors, centres tecnològics i l'administració pública adreçaran el tema des de diversos angles i iniciatives.

Organitza: UPF, Escola d'Enginyeria, Departament de Tecnologies de la Informació i les Comunicacions i UPF Ventures

Incripcions

November  8th

15:30 h

Room 55.410

PhD Research Seminar

Scientist Dating Forum

By Ryan Armstrong & Carla Conejo González

 

Abstract

The Scientists Dating Forum (SciDF) will present to the community in DTIC their approach to promote that researchers are more actively involved in society. We first got to know SciDF during the Falling Walls Lab qualifying round we co-organised in 2017, and their interests to impact on a broad number of topics, ranging from general outreach to science diplomacy, are quite well aligned with several of the priorities of the María de Maeztu transversal actions, that include opening up scientific work and setting the means that guarantee that excellent science also results in positive impacts in society.

Who is SciDF?

Scientists Dating Forum (SciDF) is a science-based association created in 2016 in Barcelona. SciDF aims to strengthen the interactions of scientists with politics, society and economics by fostering dialogue and community building.

We are a multidisciplinary young team integrated by researchers, communication specialists and people from private/public sector that share an interest in science. We are working to give to science a stronger voice in politics and economics, and strengthen its position in society. We contribute on a voluntary basis showing that the scientific community is committed to reinvent this sector and open it up.  

What does SciDF do?

SciDF wants to show how scientists through their own self-initiative try to close gaps between science and other sectors. More than 80 young and dynamic professionals from over 50 entities have been involved in the SciDF, and over 1000 people so far have attended SciDF events. These events consist of round table discussions and debates in bars (SciDF-Bars) and at institutes (SciDF-Talks), social activities for scientists and collaborations with existing institutions and programs.

We have also organized activities with other entities, such as the YoMo festival and the Festa de la Ciencia (Barcelona), and AsBioMad After Science event in Madrid.

SciDF has mobilized the scientific community of Barcelona by organizing the March for Science Barcelona 2017. We gave also a voice to science in the elections of 2017 in Catalonia: first, debating on how the independence scenario could affect research and scientists, and next, by asking all political parties to present their position on 10 different scientific policy topics, elaborating an exclusive summary for science-based vote.

SciDF opens science!

We believe that a scientific community that motivates society and politicians to participate in science, through dialogue and constructive discussions, makes more critical citizens and politicians.

 

Biography

Ryan Armstrong is a researcher in the field of management and organizations. His research interests lie primarily in two areas. First, in exploring, describing, and developing methodology for addressing complex challenges in the applied social sciences (and sometimes the natural ones). Second, in employing these methods to contribute to robust, actionable theory to help navigate the challenges brought on by the 4th Industrial Revolution: Increased technological, social, and ecological change, automation, Big Data, and uncertainty. He has published and presented on the topics of strategic management, applied philosophy, and interdisciplinarity. He is the outgoing PhD Representative for the University of Barcelona Business PhD program and for the British Academy of Management, Performance Management group. Since 2012 Ryan has worked as a consultant for organizations in Europe and the USA to support himself during his graduate education, working in strategic management, analysis, information systems, and the use of visual methods for managing complexity. Since July 2018 he has served as Treasurer for Scientists Dating Forum.

 

Carla Conejo González is the Vice-president of Scientist Dating Forum. She works at Fundació Catalunya La Pedrera, where she is the Science Projects Leader of the Area of Knowledge, Education & Research. BS in Human Biology and MS in Pharmaceutical and Biotechnological Industry at Universitat Pompeu Fabra with a degree specialization in neurobiology and research internships in the Center for Genomic Regulation in Barcelona and in the Dipartamento di Scienze Biomediche e Neuromotorie at the Università di Bologna in Italy. Scientific advisor, content researcher and creator of the TV program Quèquicom of the Canal33 (TV3). In the field of science advocacy, she is also a board member of WhatIf – Passionately Courious and has volunteered at MAGMA – Association for Promoting Youth Research, both initiatives aimed at promoting science education and dissemination by connecting science to society and facilitating access to research. Carla is also one of the founders of Associació Babu, a non-governmental humanitarian organization aimed at developing programs of health and psychological assistance worldwide.

 
Hosted by Aurelio Ruiz
 

November  8th

11:00 h

Room 52.019

Invited Research Seminar

An introduction to colour management and workflow from set to post-production

By Ariana Bonavia, DIT and Dailies Colourist

Abstract

The purpose of a colour Management workflow, is to provide colour consistency throughout the entire workflow. From set to postproduction and final deliveries. Ideally on any production we would like to maintain colour accuracy regardless of the cameras, hardware and software we use. The process will need to be standardized and capable to communicate with different systems and users. In order to translate correctly the director´s vision to the final screen.

Biography

Accomplished imaging professional with over 15 years of experience. Working on set and in post production in multi-disciplinary teams in Spain, Germany and the UK for over 80 productions.
Established and managed a DIT company, providing DIT equipment and training young industry professionals.
Extensive experience creating and supervising workflows for feature film, managing data, creating dailies with a non destructive workflow (using CDL and 3DLUTs) and interacting with the Visual Effects department providing data and metadata exchange. Experience in online editing and color grading. Detailed knowledge of color space theory.
 
About her on IMBd
October  
October 29th  
 
15.30 h
 
Room 55.410

Invited Research Seminar

Optimal Real-Time Coding of Markov Sources 

By Dr. Tamás Linder
 
Abstract
The traditional information theory of data compression allows asymptotically large coding delays, but in many applications the real-time operation is essential and even moderate delays may not be tolerated. In this talk we focus on optimal real-time (zero-delay) coding of Markov sources. After a review of some fundamental classical structural results, we give a stochastic control formulation of the optimal coding problem for a general class of real valued Markov sources. The resulting controlled Markov process facilitates the study of the existence and structure of optimal codes, but it poses subtle technical challenges due to its abstract state and action spaces. For the technically simpler case of irreducible and aperiodic discrete Markov sources we demonstrate the optimality of deterministic and stationary Markov coding policies and quantify the finite block length (time horizon) performance of such
codes. Finally, we review what is known regarding the connection of the optimal performance of zero delay codes and the so-called causal information-theoretic rate distortion function.
 
Bio
Tamás Linder received the M.Sc. degree in electrical engineering from the Technical University of Budapest in 1988, and the Ph.D degree from the Hungarian Academy of Sciences in electrical engineering in 1992. He was a post-doctoral fellow at the University of Hawaii in 1992, and a Visiting Fulbright Scholar at the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign in 1993-94. From 1994 to 1998 he was a faculty member of the Technical University of Budapest in the Department of Computer Science and Information Theory. He was a visiting research scholar in the Department of Electrical and Computer Engineering, University of California, San Diego from 1996 to 1998. In 1998 he joined Queen's University where he is now a Professor of Mathematics and Engineering in the Department of Mathematics and Statistics. His research interests include communications and information theory, source coding and vector quantization, machine learning, and statistical pattern recognition.

Dr. Linder is a Fellow of the IEEE. He received Premier's Research Excellence Award of the Province of Ontario in 2002 and the Chancellor's Research Award of Queen's University in 2003. He was an Associate Editor for Source Coding of the IEEE Transactions on Information Theory in 2003-2004.
October 26th  
 
12:00 h
 
Room 55.410

Invited Research Seminar

In silico trials: how modeling and simulation and a changing regulation combined can accelerate the development and approval of new drugs and medical devices. 

By  Luca Emili, Fundador y CEO de In Silico Trials Technologies.
 
Abstract
In the past years, FDA has started to promote significantly the use of Modeling and simulation to reduce the cost and time of development and approval of new medical devices and drugs. The significant advantages, regulatory changes and the experiences from other industries are creating and consolidating this new approach. European and US approaches will be discussed with the support of the specific application in the industry. A particular focus will be on the technology transfer for models developed in Academia that Industry wants to use.
 
Bio
Luca Emili is founder and CEO of Insilicotrials Technologies, the first global platform that allows pharmaceutical and medical devices companies to accelerate research and development through models and simulations. He is member of the Cloud Security Consultative Group in EMA and responsible for the collaboration activity with FDA. With a strong passion for technology, he is focused on the development of the company for the definition of partnership with Research centers, hospitals and pharma and medical devices companies and the development of new innovative technology and services. Prior to founding Insilicotrials Technologies he worked in M&A and acted as an investor in some SME companies. From 2001 to 2010 was CEO of Emaze, an IT Security Company backed by Alice Venture, Venture Capital with funds from Mediobanca, Generali, Pirelli, Bracco, Dompè and other Italian firms. As a journalist, he published more than 40 articles on IT security Journals. Before Emaze, he was a professor of IT at the MIB School of Management of Trieste, as well as an entrepreneur in the internet services business. He has a degree in Economy and Business from the University of Trieste 

October 25th  

 
15:30 h
 
Room 55.309

PhD Research Seminar

Gender and Science: the importance of intersectional feminism in academia

By Irene Torres , Adrián Ponce and Elisa Ruiz 
 
Abstract
Women in Science, Technology, Engineering and Mathematics (STEM) fields remain severely underrepresented. For instance, in Spain, women represent about 15% of full (catedras) professorships. Moreover, women are judged to be less competent, receive less payment and research facilities, and are less likely to be awarded research grants compared with male scientists. The different mechanisms leading to this disparity have been investigated and more is brought to light by ongoing research. In this talk we will explain the different challenges faced by women in STEM careers, the reasons and the mechanisms through which they emerge, and changes (big and small) that we can all do to improve the current dire scenario. We will also show how gender, race, class, and sexual identity discriminations are entangled and contribute to leaving out minorities from academia.
 
Host

Aurelio Ruiz 

October 18th  
 
15:30 h
 
Room 55.309

PhD Research Seminar

Introduction to PhD Seminars 

By Aurelio Ruiz, PhD Seminars Coordinator
 
Abstract
The PhD seminars aim at creating reflection on PhD students about non-technical skills and management processes required to conduct research projects and work in international teams (such as the capability to present objectives and results to specialised and layman audiences; anticipate the ethical implications of own research; basic project and self-management skills, especially those linked to networking, team working and collaboration or understand the critical aspects linked to Intellectual Property Rights and related legal aspects), facilitate the the optimal use of all tools available at UPF and the PhD program to conduct the PhD Project (such as library services or the computational cluster) and increase the knowledge of the research conducted in the broad range of ICT areas covered by the research groups involved in the program and their collaborators
 
Bio

Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program ( https://www.upf.edu/mdm-dtic )

October 11th  
 
15:30 h
 
Room Sala Aranyó del Campus Poblenou  (55s200)
PhD Research Seminar
 

The second Science and beers at the Department will take place! Following the success of the first Science and Beers, this informal meeting place consolidates as a meeting place to get to know research conducted at the department and interact with their colleagues, with a special focus on the integration of 1st year students (this Science & Beers will be the opening lecture of the PhD Seminars of the 2018-19 course).

Science and beers are organised by Adrià Arbués, Xavier Favory and Patricia Vitoria,and will have three talks by Beatriz Cabrero, Philip Tovstogan and Rasoul Nikbakht.

Don't miss it!

September
September 21st  
 
15:00 h 
 
Room 55.309

Invited Research Seminar

 
1) 15.00: Daniel Rueckert, Imperial College London, UK  
 

"Deep learning for medical image reconstruction, super-resolution, classification and segmentation "

 
Biography
Professor Daniel Rueckert is Head of the Department of Computing at Imperial College London. He joined the Department of Computing as a lecturer in 1999 and became senior lecturer in 2003. Since 2005 he is Professor of Visual Information Processing and leads the Biomedical Image Analysis group. He received a Diploma in Computer Science (equiv to M.Sc.) from the Technical University Berlin and a Ph.D. in Computer Science from Imperial College London. Before moving to Imperial College, he has worked as a post-doctoral research fellow in the Division of Radiological Sciences and Medical Engineering, King’s College London where he has worked on the development of non-rigid registration algorithms for the compensation of tissue motion and deformation. The developed registration techniques have been successfully used for the non-rigid registration of various anatomical structures, including in the breast, liver, heart and brain and are currently commercialized by IXICO, an Imperial College spin-out company. During his doctoral and post-doctoral research he has published more than 300 journal and conference articles. Professor Rueckert is an associate editor of IEEE Transactions on Medical Imaging, a member of the editorial board of Medical Image Analysis, Image & Vision Computing and a referee for a number of international medical imaging journals and conferences. He has served as a member of organising and programme committees at numerous conferences. In 2014, he has been elected as a Fellow of the MICCAI society and in 2015 he was elected as a Fellow of the Royal Academy of Engineering and as fellow of the IEEE. 
 
2) 15:50: Yoshito Otake,  Nara Institute of Science and Technology, Japan  
 

"Patient-specific modeling of muscle fiber arrangement by registration of high fidelity cadaver data"
 

 
3) 16:30:  Julia Schnabel, King's College London, UK 
 

"Deep learning for image quality control and data labelling using attention maps"

 
Biography
Julia Schnabel has joined King's College London in July 2015 as Chair in Computational Imaging at the Division of Imaging Sciences & Biomedical Engineering, taking over the Directorship of the EPSRC Centre for Doctoral Training in Medical Imaging, which is jointly run by King’s College London and Imperial College London. She is currently the Head of the Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London.
Julia's current research interests are in machine/deep learning, nonlinear motion modelling, multi-modality imaging, dynamic imaging and quantitative imaging for applications in cancer imaging, cardiovascular imaging, perinatal imaging and neurosciences. Her focus is on developing mathematically principled methods for correcting complex types of motion, such as sliding organs, fetal movements, as well as motion artefacts in dynamic imaging. She also has an interest in early disease detection, characterisation and prediction of response to treatment, with the aim of rapid translation into clinical practice for patient stratification and improved treatment outcome. 
ulia has co-/authored over 150 peer-reviewed publications, is an Associate Editor of IEEE Transactions on Medical Imaging and IEEE Transactions on Biomedical Engineering, a member of the Editorial Board of Medical Image Analysis, and has served on the programme committees of a number of international medical imaging conferences. She is a Director of the International Medical Imaging Summer School (MISS) exploring the interface between medical imaging, computer vision and machine/deep learning 
September 14th  
 
11:00 h
 
Room 55.309

Invited Research Seminar

Patch-based MRI Analysis:From voxel to knowledge

By Pierrick Coupé , CNRS researcher at the Laboratoire Bordelais de Recherche en Informatique

 

Abstract
This talk will presents our work on patch-based MRI analysis dedicated quantitative MR analysis, computer-aided diagnosis and brain monitoring. First, I will introduce the principle of our patch-based segmentation method and their extensions. Second, I will show how we have extended our patch-based segmentation framework to patch-based grading of brain structures. Then, the performance of our patch-based grading method to achieve Alzheimer’s disease diagnosis and prognosis will be presented. Afterwards, I will describe the tools that we developed to perform brain monitoring. Finally, the developed open access volBrain platform will be described.
 
Bio

I received the M. Eng degree in Biomedical engineering from University of Technology of Compiègne, France in 2003 and the M.Sc in Image and Signal processing degree from University of Rennes I, France in 2004. I obtained the Ph. D degree in Image processing from University of Rennes I, France in 2008 under the supervision of Dr Christian Barillot and Dr Pierre Hellier. For my Ph. D, I received the prize of the best thesis (innovation prize) from the Section France of IEEE - Chapter EMBS - SFGBM - and AGBM. Then, I worked as postdoctoral researcher at Brain Imaging Center of Montreal Neurological Institute from 2008 to 2011 under the supervision of Prof. D. Louis Collins. For this work, I was awarded a CECR postodocral fellowship. 

Now, I am working as CNRS researcher at the Laboratoire Bordelais de Recherche en Informatique http://www.labri.fr/  at the Bordeaux University. Since 2013 I am the leader of a new research group dedicated to patch-based image processing called PICTURA.

My research on medical image processing covers different fields, from preprocessing to automatic detection of diseases. My work mainly focuses on four topics:  Deep learning for medical imaging, BigData for medical image analysis, quantitative MR analysis, computer-aided diagnosis and image enhancement.

Host: Gemma Piella

2017-2018

September 14th  
 
11:00 h
 
Room 55.309

Invited Research Seminar

Patch-based MRI Analysis:From voxel to knowledge

By Pierrick Coupé , CNRS researcher at the Laboratoire Bordelais de Recherche en Informatique

 

Abstract
This talk will presents our work on patch-based MRI analysis dedicated quantitative MR analysis, computer-aided diagnosis and brain monitoring. First, I will introduce the principle of our patch-based segmentation method and their extensions. Second, I will show how we have extended our patch-based segmentation framework to patch-based grading of brain structures. Then, the performance of our patch-based grading method to achieve Alzheimer’s disease diagnosis and prognosis will be presented. Afterwards, I will describe the tools that we developed to perform brain monitoring. Finally, the developed open access volBrain platform will be described.
 
Bio

I received the M. Eng degree in Biomedical engineering from University of Technology of Compiègne, France in 2003 and the M.Sc in Image and Signal processing degree from University of Rennes I, France in 2004. I obtained the Ph. D degree in Image processing from University of Rennes I, France in 2008 under the supervision of Dr Christian Barillot and Dr Pierre Hellier. For my Ph. D, I received the prize of the best thesis (innovation prize) from the Section France of IEEE - Chapter EMBS - SFGBM - and AGBM. Then, I worked as postdoctoral researcher at Brain Imaging Center of Montreal Neurological Institute from 2008 to 2011 under the supervision of Prof. D. Louis Collins. For this work, I was awarded a CECR postodocral fellowship. 

Now, I am working as CNRS researcher at the Laboratoire Bordelais de Recherche en Informatique http://www.labri.fr/  at the Bordeaux University. Since 2013 I am the leader of a new research group dedicated to patch-based image processing called PICTURA.

My research on medical image processing covers different fields, from preprocessing to automatic detection of diseases. My work mainly focuses on four topics:  Deep learning for medical imaging, BigData for medical image analysis, quantitative MR analysis, computer-aided diagnosis and image enhancement.

Host: Gema Piella

July 11
 
12:00 h
 
Room 55.003

Invited Research Seminar

Legal text processing within the MIREL project and beyond

 
By Cristian Cardellino and Laura Alonso Aleman
 
Abstract
In this talk, we will be presenting the MIREL project, that aims to formalize and reason over normative text. Within this project, our team has focussed on the automatic extraction of information from judgments of the European Court of Human Rights, namely Named Entities and Argument Components. We will present our approaches and some results on these two areas, focusing on problematic aspects and how we redefined our goals to circumvent difficult problems. We will also describe some planned applications for our work: facilitating information access and retrieval, and reading aids. We will also present preliminary work on Spanish legal text processing, with a prototype application to Argentinean Law. 
 
Further details and biography: https://www.cs.famaf.unc.edu.ar/~laura/

 July 4

16:00h

55.003

Invited Research Seminar

Identifying Idiomatic Language with Distributional Semantic Models

 

By Aline Villavicencio
 
Abstract:
Precise natural language understanding requires adequate treatments both of single words and of larger units. However, expressions like compound nouns may display idiomaticity, and while a police car is a car used by the police, a loan shark is not a fish that can be borrowed. Therefore it is important to identify which expressions are idiomatic, and which are not, as the latter can be interpreted from a combination of the meanings of their component words while the former cannot. In this talk I discuss the ability of distributional semantic models (DSMs) to capture idiomaticity in compounds, by means of a large-scale multilingual evaluation of DSMs in French, Portuguese and English. The results obtained show a high correlation with human judgments about compound idiomaticity  (Spearman’s ρ=.82 in one dataset), indicating that these models are able to successfully detect idiomaticity.
 
Biography:
Aline Villavicencio is a Lecturer/Reader in Computer Science affiliated to the Federal University of Rio Grande do Sul (Brazil) and to the University of Essex (UK). Her research interests include lexical semantics, multilinguality, and cognitively motivated NLP. She received her PhD from the University of Cambridge (UK) in 2001, and held postdoc positions at the University of Cambridge and University of Essex (UK). During 2011-2012 and 2014-2015, she was on sabbatical at the Massachusetts Institute of Technology (USA). She is a current member of the editorial board of the Journal of Natural Language Engineering, the Transactions of the Association for Computational Linguistics, among others, and is Area Chair for NAACL 2018, for COLING 2018 and for IBERAMIA 2018, and the Chair for the International Conference on Computational Processing of Portuguese (PROPOR 2018). She is also a regular member of the program committee for the various ACL conferences, and has co-chaired numerous *ACL workshops on Cognitive Aspects of Computational Language Acquisition and on Multiword Expressions. She has co-edited special issues and books dedicated to these topics.

July 3

11.00 h

Room 51.100

Invited Research Seminar

"TumbleBit: An Untrusted Bitcoin-Compatible Anonymous Payment Hub"

 
By Alessandra Scafuro
 
Abstract

Bitcoin was initially conceived as a way for people to exchange money anonymously. Lately, however, it was discovered that it is possible to track Bitcoin transactions and identify the parties involved.  
In this talk, I will present TumbleBit, a cryptographic protocol that allows parties to make anonymous Bitcoin payments via an untrusted server, called Tumbler.  No-one, not even the Tumbler, can tell which payer paid which payee during a TumbleBit epoch. TumbleBit consists of two interleaved fair-exchange protocols that prevent theft of bitcoins by cheating users or a malicious Tumbler. TumbleBit combines fast cryptographic computations (performed off the blockchain) with standard bitcoin scripting functionalities (on the blockchain) that realize smart contracts.

Join work with: Ethan Heilman , Leen AlShenibr , Foteini Baldimtsi,  and Sharon Goldberg
Available at: https://eprint.iacr.org/2016/575.pdf
 
 
Biography
 
Alessandra Scafuro is an assistant professor in the Computer Science Department at NCState. Her research focuses on the foundations and applications of Cryptography. Prior to joining NCState she held a joint postdoctoral position at Boston University and Northeastern University, and at UCLA. She received her PhD from University of Salerno in 2013.
Her recent work revolves around secure two-party computation protocols and protocols to enhance anonymity on blockchain.

July 3

12:30 h

Room 51.100

Invited Research Seminar

"Post-quantum cryptography from supersingular isogeny problems?" 

By Christophe Petit 

Abstract

We review existing cryptographic schemes based on the hardness of computing isogenies between supersingular isogenies, and present some attacks against them. In particular, we present techniques to accelerate the resolution of isogeny problems when the action of the isogeny on a large torsion subgroup is known, and we discuss the impact of these techniques on the supersingular key exchange protocol of Jao-de Feo. 

Biography

Christophe Petit is a Lecturer in Computer Security in the University of Birmingham's School of Computer Science, and a member of the Security and Privacy research group. Previously he was a Research Fellow at the University of Oxford's Mathematical Institute, where he helped founding the Cryptography group,and prior to that he worked at Université catholique de Louvain's Department of Electrical Engineering and at University College London's Computer Science Department.

June 14

15:30 h

Room 51.100

PhD Research Seminar

Design of Experiment - decreasing the time of a study by increasing its reliability

By Simone Tassani

 
Abstract
This second part of seminars on statistical analysis is focused over use of ANOVA theory, previously introduced, in order to design campaigns of experiments or of simulations. During the course will be introduced Complete Factorial and Fractional Factorial analysis along with Latin squares and Taguchi methods.
The meaning of confounded effects will be introduced along with the generation of analysis blocks.
The course will close presenting the Response Surface Methodology

June 13

15:30 h

Room 51.100

PhD Research Seminar

Design of Experiment - decreasing the time of a study by increasing its reliability

By Simone Tassani

Abstract
This second part of seminars on statistical analysis is focused over use of ANOVA theory, previously introduced, in order to design campaigns of experiments or of simulations. During the course will be introduced Complete Factorial and Fractional Factorial analysis along with Latin squares and Taguchi methods.
The meaning of confounded effects will be introduced along with the generation of analysis blocks.
The course will close presenting the Response Surface Methodology

June 8

15:30 h

Room 55.309

Invited Research Seminar 

Designing expressive engagement with electronic and hyper instruments

By Hans Leeuw

Abstract
Hans Leeuw is the designer of the Electrumpet, a hyper instrument that was first designed in 2008. In his talk he will discuss the recent improvements on the instruments in relation to a persona model for instrument design that is based on values-led design. Beside the talk Hans Leeuw will also play as a demonstration of his instrument.
video link: https://youtu.be/4-IOGCF93A0
 
Host: Sergi Jordà

June 7

15:30 h

Room 55.309

Invited Research Seminar

Reflecting on the PELARS project and Multimodal Learning Analytics

By Daniel Spikol, PhD

Associate Professor, Faculty of Technology and Society, Department of Computer Science and Media Technology, Malmö University, Sweden

Abstract

The talk presents key results and lessons learnt from the Practice-based Experiential Learning Analytics Research and Support (PELARS) project. PELARS was a three-year project that developed a learning analytics system to investigate small group learning for open-ended engineering tasks. The aim is to share the results and challenges of the project to further the dialogue about how to increase progress for multimodal learning analytics (MMLA). The theories and different methods of the project will be discussed that include the different sensors used to capture, record, and analyse students physical interactions and how we used this data to create models to understand aspects of collaboration. To investigate the multimodal data, we started with a simple grading of the student's final products and progressed to a richer framework for assessing student non-verbal collaboration with different machine learning strategies. Some of the results illustrate that body location and movement are strong features for further investigating collaboration. However, challenges remain across the sustainability and ethics of how this data can be used to support the learners and teachers in creative, open-ended activities.

Biography

Scientist, educator, and creative technologist investigating how people learn and play. Spikol works for Malmö University and is a group leader in the Internet of Things and People Research Center. He previously worked for Linnæus University and  Interactive Institute (RISE Swedish Research Institute). Spikol's passion is to design and develop digital experiences to provoke people's curiosity to explore the physical and digital world around them. Spikol combines a background in design, digital art, and computer science to investigate how people learn and play. He has over 60 scientific publications and digital art installations. He has worked for various companies, founded several companies, and actively works to integrate design, science, industry, and culture. His current research looks at understanding how people to collaborate to solve open-ended design tasks with physical computing with the aim to inspire learners for computational tinkering and thinking.

June 6

15:30 h

Room 52.S27

PhD Research Seminar

Design of Experiment - decreasing the time of a study by increasing its reliability,

By Simone Tassani

 
Abstract
This second part of seminars on statistical analysis is focused over use of ANOVA theory, previously introduced, in order to design campaigns of experiments or of simulations. During the course will be introduced Complete Factorial and Fractional Factorial analysis along with Latin squares and Taguchi methods.
The meaning of confounded effects will be introduced along with the generation of analysis blocks.
The course will close presenting the Response Surface Methodology

May 24

15:30h

Room 55.309

PhD Seminars

How to do good experiments online / Good practices for online experiments

By:

 

  • Xavier Favory - Freesound Datasets https://datasets.freesound.org/
  • Maria Rauschenberger - Lessons learned from conducting a medium-scale online experiment to distinguish a person with and without dyslexia. https://mariarauschenberger.com/projects/
  • Davinia Hernández-Leo / Patricia Santos - Integrated Learning Design Environment  http://ilde2.upf.edu/

 

Abstract

User experiments can be crucial for researchers who need to evaluate methods involving humans, or gather human-generated data. The Web has created an alternative to expensive lab experiments: online and crowdsourcing experiments are valuable resources for research which can bring many advantages. However, online experiments introduce different challenges which need to be addressed carefully in order to be accurately performed. This seminar aims at sharing good practices when performing online-based experiments as well as crowdsourcing research. First this talk will give an overview of the ways in which online experiments can be used. Then, the following researchers from the department will present their work and share valuable advices:

 

  • Xavier Favory will present Freesound Datasets, a collaborative platform for the creation of open audio datasets.
  • Maria Rauschenberger will draw your attention to  possible pitfalls and lessons learned from conducting a online experiment for children at the age of 7 till 12 for different languages with a web-game.
  • Davinia Hernández-Leo will present the Integrated Learning Design Environment 2 (ILDE2), a community platform for learning design.

Background material

Making better use of the crowd. NIPS 2016, ACL 2017, and KDD 2017

Instructor: Jenn Wortman Vaughan

http://www.jennwv.com/projects/crowdtutorial.html  

May 10

15:30 h

Room 55.309

PhD Research Seminar

The experience by PhD students (2)

By:

- Adrià Arbués, Image Processing Group

Data Science in Sports and experience during the 1st year in the PhD program

- Merljin Blaauw, Music Technology Group

Singing synthesis and his motivation for doing a phd after years of industrial research projects, spinoff, etc

- Olga Slizovskaia, Music Technology Group and Image Processing Grou

Multimodal video analysis for music information retrieval. You can read part of her experience over the past 2 years in the blog of the MdM program

May 8

15:30 h

Room 55.309

Invited Research Seminar

Learning Deep Networks from ranked data

By Joost van de Weijer 

Abstract

In the second part of the talk I will discuss two applications of the decomposition of fully connected layers into several layers.  Deep Neural Networks trained on large datasets can be easily transferred to new domains with far fewer labeled examples by a process called fine-tuning. However, networks designed to be optimal for the source task are often prohibitively large for the target task. We show how layer decomposition can be used to effectively compress the network. In addition, we will show how layer decomposition can be used for the task of learning without forgetting where the task is to learn new tasks without forgetting previously learned tasks. We will show how this can be used to improve the diagonal assumption underlying the Fisher information matrix for the Elastic Weight Consolidation algorithm. The work in this talk is presented at ICCV 2017 and CVPR 2018.

Biography

Joost van de Weijer is  the leader of the Learning and Machine Perception Team (LAMP) and a senior researcher at the Computer Vision Center (Universitat Autònoma de Barcelona). His main research interest is in applying color imaging theory to the field of computer vision: color constancy, color naming, object recognition, recoloring algorithms, color feature detection and color feature extraction.

May 7

15:30 h

Room 55.309

Invited Research Seminar

Efficient Sound Synthesis By Recursive Digital Filters In Parallel Form: Virtual Musical Instruments And Artificial Reverberation

By Esteban Maestre

Computational Acoustic Modeling Laboratory, McGill University

Abstract

Recursive digital filters in parallel form offer a number of advantages. Besides their suitability for parallel implementation, improved numerical precision and parametric control are some of their attractive features. This talk will cover some recent progress in using frequency-domain optimization techniques to design high-order recursive parallel filters suited for the efficient simulation musical instruments and reverberation via modal synthesis.  

The presentation will first introduce novel methods to render musical instrument sound by combining the digital waveguide and modal synthesis frameworks. Through a modal analysis technique based on constrained optimization of parallel filter coefficients, measured resonator immitances are faithfully reproduced via an efficient modal formulation that allows their realization as lumped elements within a digital waveguide model. Sound examples will be provided for wind and string instruments.

Then, the problem of designing a modal reverberator to match a measured room impulse response will be considered. The modal reverberator architecture expresses a room impulse response as a parallel combination of resonant filters, with the pole locations determined by the room resonances and decay rates, and the zeros by the source and listener positions. The method first estimates the pole positions in an iterative process involving a series of constrained pole position optimizations in overlapping frequency bands. With the pole locations in hand, the zeros are fit to the measured impulse response using least squares. Example models for a medium sized room will be provided.

 

Host: Dr.Xavier Serra

April 26

15:30 h

Room 55.309

PhD Research Seminar

Experiences by PhD students

By:

  • Ahmed Eladly (BERG) : New technology to restore movement in paralysis
  • Irene Vigué Guix  (MRG):  A mnemonic system based on stimulation-free neuroimaging.
  • Èric Lluch (Physense):  Meshless method for cardiac mechanics modelling
  • Alp Öktem (TALN):  Generating punctuation in Transcribed Speech: Combining lexical and prosodic features using parallel recurrent neural networks 

April, 6

12:30 h

Room 24.009 (Ciutadella Campus)

Invited Research Seminar

Neural Mechanisms for Perceiving Object Motion During Self-Motion

By Greg DeAngelis

Abstract

Many organisms have highly evolved neural circuits for processing visual motion cues. However, most laboratory studies of visual motion perception are performed under highly simplified conditions in which there is no self-motion such that object motion in the world directly maps onto retinal image motion. Under many natural conditions, however, we must judge object motion during self-motion, which greatly complicates the problem. Thus, the brain needs to parse the complex pattern of retinal image motion into components that correspond to object motion and self-motion. In addition, to compute object motion in world coordinates, the brain must estimate self-motion and factor it into computations of object motion.  I will describe two studies that make important progress into understanding the visual and multi-sensory mechanisms by which the brain computes object motion during self-motion.  I will show that neural activity in macaque area MT reflects the operation of a “flow parsing” mechanism (which has been previously established in human psychophysics) that discounts global optic flow resulting from self-motion.  I will also show that neural activity in area VIP reflects flexible computation of object motion in either world- or head-centered coordinates.  Together, these studies begin to reveal critical neural processes that are involved in perceiving object motion under more natural conditions in which self-motion also occurs.

April, 5

15:30 h

Room 52.219

PhD Research Seminar

Introduction to Software Licensing 

By Malcolm Bain, idLaw partners

Abstract

When using and developing open source software, there are a number of considerations to take into account that go beyond the pure technical aspects. Malcolm Bain will introduce and review the legal aspects of using and developing open source software, with a focus on licensing, license choice and license compliance obligations with distributing products that are or embed open source components.  

Biography

Malcolm Bain is an English solicitor and Spanish lawyer, specialising in Information Technology and Intellectual Property law, and co-founder of id law partners (now part of BGMA, a Barcelona based law firm). He has a wide experience representing clients on both sides of IT transactions, and advises on licensing, software contracts, technology transfer, copyright, privacy and trademark issues. He has participated in various R+D projects and written and lectured on many aspects of IT law, e-commerce and internet regulation.

April, 3

15:00 h

Room 55.410

Invited Research Seminar

One size doesn't fit all: towards adaptive and personalized text simplification

By Joachim Bingel

Abstract

Most previous research in text simplification has aimed to develop generic, broad-scale solutions that assume very homogeneous target audiences. However, this assumption does not hold, as attested by evidence that different groups (such as dyslexics, language learners or beginner readers), but also individuals within these groups, differ strongly with respect to their simplification needs.
 
This talk proposes methods that take us closer to personalized and adaptive text simplification systems. Using online learning techniques, these systems collect explicit and implicit feedback from users to continuously learn to model their individual simplification needs. We further show that multitask learning can be used to effectively transfer knowledge about simplification needs between different user groups as well as individuals.

Biography

Joachim Bingel is a final-year PhD student at the University of Copenhagen, supervised by Anders Søgaard. His primary research interests include adaptive models for text simplification and multitask learning, as well as the combination of these. Joachim has further published papers in corpus linguistics and the usage of cognitive data to improve NLP models. He has a Master's degree from the University of Heidelberg and has previously worked as a researcher at the Institute for the German Language in Mannheim.

Host

Monika Dominguez

March, 27th

15:30 h

Room 55.309

Invited Research Seminar

Conditional Risk Minimization for Stochastic Processes

By Alexander Zimin

Abstract

We study the learnability of stochastic processes with respect to the conditional risk, i.e. the existence of a learning algorithm that improves its next-step performance with the amount of observed data. We introduce a notion of pairwise discrepancy between conditional distributions at different times steps and show how certain properties of these discrepancies can be used to construct a successful learning algorithm. In addition to theoretical results that establish criteria for learnability for many classes of stochastic processes, we provide a practical algorithm that can be efficiently implemented and applied to real data.

Biography

Alexander is a PhD student at IST Austria working in the group of Christoph Lampert. He obtained his Master degree from Central European University in 2013 under supervision of Laszlo Gyorfi and Gergely Neu. His research is focused on various machine learning scenarios, which involve dependent data. Previously he has also worked on online learning and reinforcement learning.

Host

Gergely Neu

March, 19

10:00

55.410

Invited Research Seminar

The influence of cellists' postural movements on their musical expressivity

By Joselyn Roze, Université Aix-Marseille

Abstract

The musician's body is often deeply forgotten in the traditional instrumental pedagogy. In the case of bowed-string instrumentalists, the attention is required to be paid on the fingers' dexterity at the left hand or the bow accuracy at the right hand, like preliminary and mandatory conditions for musical expressivity. However, just by observing the play of great violinists or cellists, we can realize that they use postural movements more or less consciously, which are far away from their purely instrumental gestures involved in the sound production. What would be thus the function of these corporeal movements ? If they visually contribute to make a performance more lively, we actually don't know their influence on the perceived expressive acoustical features, such as the musical phrasing or the sound quality.


In my thesis, we try to bring some response elements by investigating the cellists' ancillary movements and their influence on the musical expressivity. On the gesture side, we focus on the chest and head displacements, which are the most salient visually but also the most essential for the cellist's motor planning. On the acoustical side, we focus on the two principal means of producing musical expressivity : the rhythmic and the timbre. This investigation takes place within various areas implying different perspective levels : Instrumental pedagogy, musician's posture, cellist's physiology, and more globally musical embodiment. The influence of postural movements on the musical expressivity is assessed by the means of four postural conditions affecting the cellists' sensorimotor mechanisms : A standard playing condition and three gradual immobilization constraints (mental, physically immobilized by the chest, and finally by the chest and the head). Within each postural session, the bow playing mode (short détaché or large legato) has been chosen as a studying factor of the crossed relationships between sound and motion.
The first part of the thesis highlights the relationships between the cellist's postural movements and their rhythmical expressivity. It appears that the coordination between posture and movement of a cellist is optimal with a good postural-kinetic capacity, which allows to keep the balance by resisting to bow expansions. The natural symbiosis between the musician and his cello also turns out to be a key factor for the metric and rhythmic cohesion between trunk ancillary gestures and instrumental bowing. The rhythmical unbalance caused by the absence of postural movements is particularly repeatable during passages requiring a good motor coordination between the two arms. The
discomfort felt is assessed stronger in the bowing mode détaché, which coincides with a bigger uniformity in speed modulations and inter-note timbre colors. The second part of the thesis is dedicated to the detailed exploration of the timbre for a note frequently increased in harshness within the postural constraint by chest and head. This acoustical degradation is generally linked with a weaker bow speed and a narrower gesture of the instrumental right arm. By tracing back to the central body parts, we highlighted the importance of the spine torsion and the right shoulder opening for the sound quality. The whole of these works support flexibility in the postural movement freedom for producing a balanced and expressive play.

Biography

Graduated from the french engineer school in Electronic and Informatics (EFREI), Jocelyn Rozé worked eight years as a consultant for an information-technology service company (ALTEN). Around the end of this period, he discovered the cello and developed a passion for playing this instrument. Jocelyn then tried to redirect and choose a professional career likely to merge his technical skills to his instrumental passion. He found this opportunity by starting a PhD thesis at the Laboratory of Mechanic and Acoustic (LMA) of Marseille on the topic entitled : « The influence of cellists’ postural movements on their musical expressivity ». He obtained his doctorate degree in 2017 and now he continues a post-doctoral research on the same context to refine and promote his thesis results.

March, 14

12:30

Auditorium

PhD Research Seminar
 
The statistical foundations of learning to control
 
By Ben Recht
 
Abstract
Given the dramatic successes in machine learning and reinforcement learning over the past half decade, there has been a resurgence of interest in applying these techniques to continuous control problems in robotics, self-driving cars, and unmanned aerial vehicles.  Though such control applications appear to be straightforward generalizations of standard reinforcement learning, few fundamental baselines have been established prescribing how well one must know a system in order to control it.  In this talk, I will discuss how one might merge techniques from statistical learning theory with robust control to derive such baselines for such continuous control.  I will explore several examples that balance parameter identification against controller design and demonstrate finite sample tradeoffs between estimation fidelity and desired control performance.  I will describe how these simple baselines give us insights into shortcomings of existing reinforcement learning methodology.  I will close by listing several exciting open problems that must be solved before we can build robust, safe learning systems that interact with an uncertain physical environment.
 
Biography
Benjamin Recht is an Associate Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. Ben's research group studies the theory and practice of optimization algorithms with a focus on applications in machine learning and data analysis. They are particularly interested in busting machine learning myths and establishing baselines for data analysis. Ben is the recipient of a Presidential Early Career Awards for Scientists and Engineers, an Alfred P. Sloan Research Fellowship, the 2012 SIAM/MOS Lagrange Prize in Continuous Optimization, the 2014 Jamon Prize, the 2015 William O. Baker Award for Initiatives in Research, and the NIPS Test of Time Award.

March, 12

15:30

Room 55.410

Invited Research Seminar
 
Music Technology for STEAM Education
 
By   Dr. Aggelos Gkiokas, Postdoctoral Research Associate.
&
Kosmas Kritsis, Research Associate.
Institute for Language and Speech Processing (ILSP), 
Athena Research and Innovation Center


Abstract
 
The educational movement of STEAM is about bringing Arts at the heart of the academic curriculum in order to cultivate creative skills of young people, alongside with the knowledge and skills they acquire in STEM fields (i.e. Science, Technology, Engineering and Mathematics). As a STEAM-oriented solution, the iMuSciCA project (Interactive Music Science Collaborative Activities) presents an interdisciplinary pedagogy framework that connects different disciplines with each other on an inquiry and collaborative manner. It directly addresses the current requirements in education and learning for new pedagogical methodologies and innovative educational technology tools by supporting active, discovery-based, personalized and more engaging learning, while providing students and teachers with opportunities for collaboration, co-creation and collective knowledge building. iMuSciCA offers a suite of software tools and services mostly related to music which are built on top of new enabling technologies, and are integrated on a web-based platform that delivers interactive music activities to secondary school students with the aim to support mastery of core academic content on STEM subjects (Physics, Geometry, Mathematics, and Technology). Enabling technologies, including interactive pen on touchpad, 3D object design and printing, as well as new multimodal interfaces that combine advanced music generation and processing, are deployed in order to implement a web-based workbench aiming at STEAM learning. The contribution of the Institute for Language and Speech Processing in the iMuSciCA project involves the development of methods for interacting with virtual music instruments using camera sensors, the development of advanced real-time visualization tools for music analysis, the deployment of algorithmic composition methods for enhancing music creativity as well as applying conventional Music Information Retrieval techniques in the context of a STEAM education platform.

Biography

Dr. Aggelos Gkiokas is a Postdoctoral Research Associate at the Institute for Language and Speech Processing of Athena Research and Innovation Center (ILSP/ATHENA RIC). He holds a PhD Degree in Music Information Retrieval and his main research interests are automatic music rhythm analysis, music similarity, audio visualization. 

Kosmas Kritsis is a Research Associate at the Institute for Language and Speech Processing of Athena Research and Innovation Center (ILSP/ATHENA RIC). He is a PhD Candidate at the department of Informatics of the University of Piraeus (UniPi) and holds a MSc in Sound & Music Computing from Pompeu Fabra University of Barcelona (UPF). His academic experience and research interest includes scientific areas, such as Human-Computer Interaction, Audio Signal Processing, Computer Vision and Machine Learning.

March, 8

15:30

Room 55.309

PhD Research Seminar

The power of ordinary people in the Web - Studying quality and inequalities in User Generated Content

By  Diego Sáez-Trumper

Host: Aurelio Ruiz

Abstract

Internet utopia came with the promise of democratize the access to knowledge, and allows to create, share and receive free information. But after 26 years of the releasing of the first Web Browser, how is people producing, receiving, and propagating information in the Internet? In this talk, I will introduce my work on the usage of massive data processing (a.k.a Data Science) for studying digital prints of human behavior, as well as discuss how Machine Learning and Artificial Intelligence can be used to empower people on the digital era, specially in  the context of a free knowledge community, where we want to use those techniques not to replace, but to support human judgment. 

Biography

Diego Sáez-Trumper is a Research Scientist at Wikimedia Foundation. Before, he was a post-doctoral researcher at Yahoo! Labs (Barcelona) and Research Scientist at Eurecat , Data Scientist at NTENT, and part time lecturer at UPF. He holds a diploma on Acoustic Engineering (Universidad Austral de Chile, 2006) and  obtained his Phd in Information Technology from Universitat Pompeu Fabra (2013) under the supervision of Dr. Ricardo Baeza-Yates. During his PhD he interned at Qatar Computing Research Institute, University of Cambridge  and Universidade Federal de Minas Gerais in Brazil. 

March, 7

15:30

Room 55.410

Phd Research Seminar

Extended Minds and Machines 

By Karina Vold 

 

Abstract

Traditional cognitive science subscribes to the computational theory of mind, which says that our thoughts are realized by neural computations, or symbol manipulations, carried out by our brains. Philosophers Clark and Chalmers (1998) roughly accept the computational theory of mind but argue that when we use tools, such as smartphones and tablets, they can become seamlessly integrated into our cognitive processes such that computations in the tools are just as essential to our cognition as computations in our brain: smartphones extend our cognition. The ‘extended mind thesis’ is an increasingly popular view in philosophy of mind and cognition. It maintains not only that technologies can compensate for biological deficiencies, but also that technologies can augment our minds and enhance our biologically bound cognitive capacities, making us smarter and more capable agents (e.g. Sutton 2007; Menary 2007).

 Given our cognitive reliance on technology, recent advancements in artificial intelligence may be cause for concern. The outcomes of algorithms can have adverse effects on human-decision making: take the case of biased risk-assessment algorithms used to predict recidivism rates and inform judges in parole decisions. Furthermore, machines now have goals, or desired outcomes, of their own and depending on what these goals are, humans might be a good means to achieve those outcomes. The more we build machines to have human-like general intelligence the more likely it seems that machines may move beyond their intended, or original, hardware base to make use of tools to complete their tasks, just as we have. This might not be a bad thing, but one concern is whether us humans will be their tools of choice. Thus, we might need to protect humans from being used, nudged, or manipulated by machines.

Biography

 Karina Vold is a Research Associate at the Leverhulme Centre for the Future of Intelligence and Research Fellow in the Faculty of Philosophy at the University of Cambridge where she works on the Agency and Personhood Project. She specializes in philosophy of mind and cognitive science and is currently interested in cognitive extension, machine agency, and consciousness.

March, 1st 

13:30

Room 52.223

Phd Seminar : Software development best-practices for reproducible research

By  Alastair Porter

Abstract

In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups. A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time. For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time. In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available.

March, 1st

15:30

Room 55.309

Invited Research Seminar

Cyber-physical resilient systems

By Joaquin García-Alfaro

Abstract

Cyber-physical systems consist of upgraded infrastructures in which physical, network and software components interact with each other, in a continuous and dynamic way. This upgrade introduces new threats to the resilience of traditional infrastructures. Known incidents include the sabotage of critical energy facilities, disruption of hospitals and financial services, and successful hacking of navigation systems. The problem is drawing a great deal of attention, since it can have serious effects to businesses, governments and society at large. During this talk, we will focus on disruptive attacks hidden as unintentional component malfunction. Such attacks must be handled by jointly addressing protection at both cyber and physical domains. We will argue about the necessity of novel solutions expanding results from research communities including information security, control theory and automation engineering. Application domains will include industrial scenarios, autonomous vehicles, ambient intelligence and Internet-of-Things.

Biography

Full Professor at Institut Mines-Telecom (Telecom SudParis & Université Paris-Saclay). Double Ph.D.degree in Computer Science from Universitat Autonoma de Barcelona (UAB) & Université de Rennes. Research Habilitation from Université Pierre et Marie-Curie (Paris Sorbonne VI). He holds two engineering awards from UAB, a doctoral fellowship award and a graduate award from the "la Caixa” savings bank foundation. His research interests are situated in several domains of network & system security, with a special emphasis on areas related to the management of formal policies, analysis of threats, enforcement of mitigation and evaluation of countermeasures.   

February,22nd 

15:30

Room 55.309

Phd Research Seminar

Ethical issues and data protection, CIREP-UPF.

By  Silvia Losa & Josep Blat
 

Abstract

CIREP-UPF (Internal Committee for the Ethical Review of Projects) aims at improving ethical standards and personal data protection in research and academic practices related to human beings, within the UPF community. The first review of a research project by CIREP took place about two years ago.

During this session the basic concepts on both issues, ethics and personal data protection, will be introduced through practical examples. Moreover, it will be discussed how to submit project(s) (proposals) to CIREP for ethics evaluation and approval. The session can be considered as a preparation to submit a proposal on the PhD research and/or acting as a reviewer of such a proposal.

February,22nd 

10:30-12:30

Room 55.309

Course (6 hours: 9th, 15th and 22nd of February)

Phd Seminar : Statistical course and Design of Experiments

By Simone Tassani

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.

Monofactorial and multifactorial analysis will be presented, together with the definition of Type I and Type II error, multiple comparison errors and tests for multiple comparison.

In the case of multifactorial analysis, the concept of interaction among the factors will also be presented and how to use interaction as estimator of the error in absence of repetitions.

This will lead to the presentation of some examples of Design of Experiment (Latin and Greek-Latin squares) for the reduction of the number of experiments.

February,15th 

15:30

Room 55.410

Phd Research Seminar

Scientific Dissemination, Online Repositories, and Author's Rights

By  Ana Baiges
 

Abstract

The purpose of the meeting is to explain the services that the Library offers to UPF researchers and graduate students in the preparation of scientific publications, and the aspects to take into account in their dissemination. A particular emphasis will be placed on intellectual property issues on the compliance with European and Spanish policies on open access (Horizon 2020, Plan Estatal ICTI) and an overview on author profiles and affiliation.

February,15th 

10:30 - 12:30

Room 55.309

Course (6 hours: 9th, 15th and 22nd of February)

Phd Seminar: Statistical course and Design of Experiments

By Simone Tassani

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.

The first part of the course will introduce General Linear Modelling and its most common applications:

Linear regression

T-test

F-test

Analysis of Variance (ANOVA)

February,9th 

10:30 - 12:30

Room 55.309

Course (6 hours: 9th, 15th and 22nd of February) 

Phd Seminar: Statistical course and Design of Experiments

By Simone Tassani

The course of statistics aims to introduce a number of tools for master/Ph.D. students and post docs. The presented tools will play a role in planning many kind of studies, properly analyse the results and understand if data analysed by other researchers are or not reliable.

The course will start with a brief digression over the several implications that bad statistics have today over the scientific society and why every researcher should know the basic concepts behind a statistical analysis.

February,8th 

15:30

Room 55.410

Phd Research Seminar

Adapting research capabilities to industry

By Aleix Ruiz de Villa.
 
Abstract
Going from academy to industry is not a trivial path. Quite often personal and social expectations do not match entirely. We will share some experiencies about personal and social motivations. We will talk about the relevance of understanding the context before taking decisions. We will introduce how research capabalities may be a key ingredient in industry and finally highlight some fallacies we will possibly find during the process. 
 
Biography
Aleix Ruiz de Villa has a PhD in mathematics and MSc in mathematical finance. He's worked in gaming, traffic software simulation, journalism and retail. He is currently Chief Data Scientist at Onna, a company developing software for documents and knowledge management. He is also cofounder of the Barcelona R Users Group and founder of the Barcelona Grup d'estudi de machine learning meetups.

February,8th 

15:00

Room 55.309

Invited  Research Seminar

Sound Source Localization in Wireless Acoustic Sensor Networks

By Maximo Cobos

Host: Emilia Gómez

Abstract

With the rapid evolution in the design and manufacture of electronic circuits, wireless nodes that integrate sensors and communication interfaces of different types have become economic resources for the design and deployment of innovative monitoring systems. In this context, wireless sensor networks (WSNs) have spread in fields as diverse as security, industry and systems oriented to care and well-being. When nodes incorporate acoustic transducers and the processing involves the manipulation of acoustic signals, such networks are commonly known as wireless acoustic sensor networks (WASNs). Inference of location information has always been an attractive research problem, where traditional (wired) microphone arrays have been employed to identify the number and location of active sound sources. However, practical limiations such as limited processing power, lack of synchronization and battery life of the nodes restrict the direct application of classical approaches within a WASNs framework. The seminar will cover a brief introduction to this research field, as well as an overview of recent approaches to tackle this problem.

Biography

Maximo Cobos received the Ph.D. degree in telecommunications from Universitat Politècnica de València in 2009. His Ph.D. dissertation was awarded with the Ericsson Best Thesis Award on Multimedia Environments from the Spanish National Telecommunications Engineering Association (COIT). He completed with honors his Ph.D studies under the University Faculty Training program (FPU) and was awarded with a "Campus of Excellence" post-doctoral fellowship to work at the Institute of Telecommunications and Multimedia Applications (iTEAM). Since 2011 he has been with the Computer Science Department of the Universitat de València, where he is now an Associate Professor. His work is focused on the area of digital signal processing for audio and multimedia applications, where he has published more than 90 technical papers in international journals and conferences. Dr. Cobos is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), a Full Member of the Acoustical Society of America (ASA) and a member of the Audio Signal Processing Technical Committee of the European Acoustics Association (EAA).

February,8th 

14:30

Room 55.309

Invited  Research Seminar

Multidimensional and multi-level learning of music structure for machine improvisation

by Emmanuel Vicent

Host:Emilia Gómez

Abstract

Current musical improvisation systems generate unidimensional musical sequences by recombining their musical contents. However, considering several dimensions (melody, harmony...) and several temporal levels are difficult issues. In this talk, I will summarize the work of my PhD student Ken Déguernel on the combination of probabilistic approaches with formal language theory in order to address those issues. First, I will present a system able to follow the contextual logic of an improvisation modelled by a factor oracle whilst enriching its musical discourse with multidimensional knowledge represented by interpolated probabilistic models. Then, this work is extended to create another system using a belief propagation algorithm representing the interaction between several musicians, or between several dimensions, in order to generate multidimensional improvisations. Finally, we propose a system able to improvise on a temporal scenario with multi-level information modelled with a hierarchical grammar. We also propose a learning method for the automatic analysis of hierarchical temporal structures. All systems have been evaluated by professional musicians and improvisers during listening sessions.

Biography

Emmanuel Vincent is a Senior Research Scientist with Inria (Nancy, France). He received the Ph.D. degree in music signal processing from IRCAM (Paris, France) in 2004 and worked as a Research Assistant with the Centre for Digital Music at Queen Mary, University of London (London, U.K.) from 2004 to 2006. His research focuses on statistical machine learning for audio, with application to source localization and separation and noise-robust speech recognition, among others. He is a founder of the series of Signal Separation Evaluation Campaigns (SiSEC) and CHiME Speech Separation and Recognition Challenges.

February,7th 

12:30

Room 55.410

Invited  Research Seminar

The Face of Emotion: A computational model of the production and visual perception of facial expression of emotion

By  Aleix M. Martinez

Host: Xavier Binefa

Abstract

We now have computer vision algorithms that can successfully detect low-level image features (such as, edges), recover the 3D structure and motion of objects, and provide a semantic label for them (e.g., a face, or John’s face). But how about higher level, abstract concepts like emotions? This talk will introduce the first algorithms to successfully identify the emotion categories people regularly use to communicate emotion. I will first summarize our research uncovering the image features used by the human visual system to recognize emotion in faces. I will then explain how these results can be used to define computer vision systems that can work “in the wild” (i.e., outside controlled, in-lab conditions). In doing so, I will show the novel finding that people regularly use more than 35 distinct facial expressions (not the six propound by Darwin). We will see that the major problem in computer vision is that of landmark detection, not recognition, as is typical of most modern systems.

Biography

Aleix M. Martinez is a Professor in the Department of Electrical and Computer Engineering at The Ohio State University (OSU), where he is the founder and director of the the Computational Biology and Cognitive Science Lab. He is also affiliated with the Department of Biomedical Engineering and to the Center for Cognitive Science where he is a member of the executive committee. Prior to joining OSU, he was affiliated with the Electrical and Computer Engineering Department at Purdue University and with the Sony Computer Science Lab. He has served as an associate editor of IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transaction on Affective Computing, Computer Vision and Image Understanding, and Image and Vision Computing. He has been an area chair for many top conferences and was Program Chair for CVPR 2014 in his hometown, Columbus, OH. He is also a member of the Cognition and Perception study section at NIH and has served as reviewer for numerous NSF, NIH as well as other national and international funding agencies.

February, 1st 

15:30 

Room 55.309

Phd Research Seminar

Communication skills in science: the research in 4 minutes competition

By Aurelio Ruiz
 

Abstract

UPF has launched the "Research in 4 minutes" competition, with the purpose of underscoring the importance of communication skills in the dissemination of science. During this seminar, we will discuss some approaches to maximise the possibilities to succeed in this competition, as well as in any other context with limited time to present your work to non-experts. Suggested reading: Communication: Two minutes to impress.
February, 1st 
12:00
Room 55.410

Invited Research Seminar

Scale-invariant unconstrained online learning

By Wojciech Kotłowski

Abstract

We consider a variant of online convex optimization in which both the instances (input vectors) and the comparator (weight vector) are unconstrained. We exploit a natural scale invariance symmetry in our unconstrained setting: the predictions of the optimal comparator are invariant under any linear transformation of the instances. Our goal is to design online algorithms which also enjoy this property, i.e. are scale-invariant. We start with the case of coordinate-wise invariance, in which the individual coordinates (features) can be arbitrarily rescaled. We give an algorithm, which achieves essentially optimal regret bound in this setup, expressed by means of a coordinate-wise scale-invariant norm of the comparator. We then study general invariance with respect to arbitrary linear transformations. We first give a negative result, showing that no algorithm can achieve a meaningful bound in terms of scale-invariant norm of the comparator in the worst case. Next, we compliment this result with a positive one, providing an algorithm which "almost" achieves the desired bound, incurring only a logarithmic overhead in terms of the norm of the instances.

Biography

Wojciech Kotłowski is an assistant professor at Poznan University of Technology, Poland. From 2009 to 2012, he was a post-doctoral researcher in Centrum Wiskunde & Informatica (Amsterdam, Netherlands) in the group of Peter Grünwald. He obtained his Ph.D. degree in Computer Science from Poznan University of Technology in 2009 under supervision of Roman Słowiński. His main research interests are in the theory of machine learning, particularly in the online learning withadversarial data.

February, 1st 

10:30

Room 55.309

Research Seminar

Towards Green Web Search

By Ana Freire

Abstract

Web search engines have to deal with a rapid increase of information, demanded by high incoming query traffic. This situation has driven companies to build geographically distributed data centres housing thousands of computers, consuming enormous amounts of electricity and requiring a huge infrastructure around. Google reported the use of 4,400 GWh of electricity (equivalent to the amount of energy consumed by 367 US households). At this scale, even minor efficiency improvements result in large financial savings.

This seminar will introduce the concept of Green Web Search, by first exploring several (still few) approaches for developing sustainable search engines data centres. In the second part of the talk I will focus on a machine-learning-based model for click prediction to reduce the energy consumed while processing queries. Models like this are environmentally and economically beneficial, as they reduce pollution and lead to cost savings.

January 25th

15:30 

Room 55.410

 
Phd Research Seminar
 
Sharing your data and software on Zenodo
 
By Lars Holm Nielsen
 
Abstract
To fully understand and reproduce research performed by others, it is necessary to have all the details. In the digital age, that means all the digital artefacts, which are all welcomed in Zenodo. To be an effective catch-all repository, that eliminates barriers to adopting data sharing practices, Zenodo does not impose any requirements on format, size, access restrictions or licence. Quite literally we wish there to be no reason for researchers not to share! Data, software and other artefacts in support of publications may be the core, but equally welcome are the materials associated with the conferences, projects or the institutions themselves, all of which are necessary to understand the scholarly process.
 
Biography
Lars Holm Nielsen works in the CERN IT Department for the past 6 years where he is Service Manager for Zenodo, a multidisciplinary research data repository for the world, build and operated by CERN. He is also Product Manager for Invenio, the underlying digital repository platform upon which Zenodo is based and has extensive experience in building and managing large scale digital repositories. He previously worked for 10 years at ESO, the European Southern Observatory, working on public outreach information management and science visualization.

January 25th

10:00

Room 55.309

Research Seminar

Learning, inference and control in complex systems

By Vicenç Gómez

Machine Learning is the study of data-driven methods capable of mimicking, understanding and aiding complex information processing tasks. In the first part of this seminar, I will review some of my contributions to this field in two basic research areas: probabilistic graphical models and reinforcement learning. In particular, I will first focus on efficient approximate inference algorithms for estimating the partition function of a graphical model, and second, on the equivalence between probabilistic inference and optimal control computation through the class of linearly-solvable Markov decision processes.

In the second part of this seminar, I will talk about applied research. I will first explain how we can design practical algorithms for robot control using the previous principles. Then, I will show how we can improve brain-computer interfaces using reinforcement learning, and, finally, I will describe how we can better understand online human activity using data-driven methods applied to complex social networks.

Since this research seminar is included in the ML tenure-track evaluation position, I will end up with a brief statement about my future research/academic plans.

January 24th

15:30 

Room 55. 309

PhD Research Seminar

Building Machine Learning Models to Value Heterogeneous Transactions in a Multi-Dimensional Customer-Vendor Relationship

by Gabriel Silberman

Abstract

Customer data​ gathered​ by enterprises is on the rise and being used to understand customer journeys for many purposes.  ​At Cerebri AI we created an approach for using this data, in addition to demographics and other factors, events and transactions, to build supervised and  ​unsupervised machine learning models to ​assess how a customer values a vendor, its products and services ​, at any point in time​ ​.​ The result is something we call Cerebri Values, and they provide a view of the vendor from a customer's perspective.
 
The methodology used to create Cerebri Values enables a proportionate attribution of transactions to events in a customer journey, normalized by the amount of actual purchases and expressed as a monetary value. This allows the detailed design of cost-effective, one-to-one marketing campaigns.
 
The talk will describe the rationale behind Cerebri Values, how they are built and how they are being used in understanding customers in the automotive space. If time allows we will also discuss how a similar approach may be used to detect bias in machine learning models built to support decision making.

January, 18th 

15:30

Room 55.410

PhD Research Seminar

Reproducibility in research.

By Aurelio Ruiz

Abstract

We will use excerpts of the talk by Victoria Stodden at the María de Maeztu Strategic Research Program (available at https://www.upf.edu/web/mdm-dtic/reproducibility-in-research ) to discuss one of the objectives of this program, which is “to increase the impact of our research by increasing the impact of the publications, datasets and software tools, and take advantage of this impact to establish and consolidate partnerships”. We will discuss ways to promote that the research results, datasets and tools are discoverable, interpretable and reusable, including the publication of the data and software together with the publications. During this session, we will discuss some of the topics linked to "reproducible research", including also the increasing external requirements in making datasets and computer code available by funding agencies, publishers and potential mechanisms to promote it in our organisation.

Suggested reading
 

-Reproducible Research in Signal Processing - What, why, and how. Vandewalle, Patrick; Kovacevic, Jelena; Vetterli, Martin. IEEE Signal Processing Magazine (ISSN: 1053-5888), vol. 26, num. 3, p. 37-47. Institute of Electrical and Electronics Engineers, 2009

-Ongoing draft document within MdM for good practices for discussion in this link

-For a survey on NIPS participants and motivations (2008): "The Scientific Method in Practice: Reproducibility in the Computational Sciences", Stodden, Victoria. MIT Sloan Research Paper No. 4773-10.

Biography

Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program.

January, 18th 

10:00

Room 55.309

Research Seminar

Practical Spectral Learning Algorithms for Compositional Latent State Models

By Ariadna Quattoni

The main topic of this talk will center around the problem of learning compositional latent state models. Many problems in natural language understanding (NLU) can be framed as learning compositional functions over structured input/output domains, for example: language modeling, sequence tagging, parsing, relation extraction, etc. More specifically, I will focus on learning non-deterministic weighted automaton (WFAs) and grammars for these problems.

Spectral learning algorithms for WFAs are based on using a non-parametric representation and exploit a link between recurrence relations satisfied by a function and low-rank constraints on certain matrices constructed from function outputs. They have nice theoretical and algorithmic properties but despite this it has been challenging to obtain competitive results in real language modeling tasks. This is mainly because the classical spectral algorithms have practical limitations that make it hard to scale them to the requirements of real applications. In the first part of the talk I will describe recent work on overcoming some of these limitations that results in significant improvements.

The second part of the talk will be about future research directions. I will touch on another critical aspect of making learning compositional latent state models practical for NLU applications: namely the need for robust active learning algorithms specifically designed for structured domains. Most NLU applications have unique information needs, and obtaining the large collections of annotated data necessary to achieve good performance under the supervised approach might be too expensive for many use-case scenarios. Therefore, we need a collaborative machine learning paradigm that breaks the distinction between annotation and training so that models can be built with a minimal amount of supervision. A key idea that we can borrow from spectral learning is that the problem of active learning of compositional latent state models can be reduced to a form of active low-rank matrix completion.

January, 11th 

15:30

Room 55.309

PhD Research Seminar

"How to prepare a good abstract"

By Bart Bijnens

December,14th 

11:30

Room: 52.321

Phd Research Seminar

IEEE Author's Workshop

By Ana Baiges, Federico Peña and Jean Gardy Germain

Services and resources that the UPF Library puts at your disposal for scientific publishing.

Registration Form

December,14th 

11:00

Room 55.410

Invited Research Seminar

Rational data processing in complex networks.

By Santiago Mazuelas

Host: Xavier Binefa

Abstract

Data has been shown to be an extremely useful resource in many fields including communications, information technology, weather forecasting, and economics. Data processing techniques developed under paradigms such as machine learning, data science, and Bayesian inference are enabling many critical applications. In each specific application, data can reduce the uncertainty on the consequences of possible actions and hence improve decision making. For instance, certain key words in an email reduce the uncertainty regarding email usefulness and, hence, improve spam filtering.

Rational decision making that is consistent with preferences among consequences requires a probabilistic processing of data.  Such probabilistic framework for data processing encounters several technical difficulties including 1) modeling of complex data, 2) approximation of intractable computations, and 3) efficiency in high dimensions. In this talk, I will provide an overview of such probabilistic framework and describe techniques to overcome the above-mentioned difficulties. In addition, I will show the practical benefits of the techniques presented through the case study of network localization and navigation.

Keywords: probabilistic processing, machine learning, positioning, distributed processing, information coupling, graphical models, belief propagation, density estimation, Kalman filters, Particle filters, Belief condensation filters

Biography

Santiago Mazuelas has been a Staff Engineer at Qualcomm Corporate Research and Development since Mar 2014. Prior to joining Qualcomm, he was a Postdoctoral Fellow and Associate in the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT) from Sep 2009 to Mar 2014 . He previously worked from 2006 to 2009 as a researcher and project manager in a Spanish technological center as well as a junior lecturer in the University of Valladolid. His general research interest is the application of mathematics to solve engineering problems, currently his work is primarily focused on statistical signal processing, machine learning, and data science.

Dr. Mazuelas is Associate Editor for the IEEE Communications Letters, and has served as Co-chair for the Symposiums on Wireless Communications at the 2014 IEEE Global Communications Conference (Globecom) and at the 2015 IEEE International Conference on Communications (ICC). He has been a member of the Technical Program Committee (TPC) for numerous conferences including the IEEE Globecom in 2010-2017, IEEE ICC in 2013-2017, IEEE VTC in 2012 and 2015, and ICUWB in 2011, and 2013-2017. He received the Best Student Prize in Telecommunications Technical Engineering from University of Valladolid in 2006, the Best Doctorate Thesis Award from University of Valladolid in 2011, and the Young Scientist Prize from the Union Radio-Scientifique Internationale (URSI) Symposium in 2007. His papers received the IEEE Communications Society Fred W. Ellersick Prize in 2012, and Best Paper Awards from the IEEE ICC in 2013, the IEEE ICUWB in 2011, and the IEEE Globecom in 2011.

December,12th 

15:30

Room 55.309

Invited Research Seminar

Creating music at Jukedeck

By Katerina Kosta

Host: Emilia Gómez

Abstract

This presentation starts with an introduction about Jukedeck, an Artificial Intelligence music generation system, its products and aims. Then it focuses on the challenges a music AI system faces in order to create plausible music excerpts; from gathering and cleaning data, learning musical structure, and evaluating the outcome to synthesising audio.

Biography

Katerina Kosta is a machine learning researcher at Jukedeck, working as part of the composition team, whose aim is to develop machine learning systems for music generation. She pursued her PhD at the Centre for Digital Music, Queen Mary University of London, conducting research on modelling dynamic variations in expressive music performance. She received degrees from University of Athens (Mathematics) and Filippos Nakas Conservatory, Athens (Piano), and a Sound and Music Computing Masters from the Music Technology Group, UPF, Barcelona.

November,30th 

15:30

Room 55.309

Invited Research Seminar

Competition policy and consumer outcomes - Assessing the impact of mobile consolidation on innovation and quality

By Xavier Pedrós  

Host: Miquel Oliver

Abstract

Competition authorities are required to assess mergers by looking at the likely effects of these on consumer outcomes. These include a range of characteristics that are important to consumers, such as price, quality and innovation. In practice, however, significant emphasis is put on (often short-term) prices, using tests that can easily trigger competition concerns in investment-intensive industries. Meanwhile, dynamic efficiencies and their possible effects on the quality of mobile services have often faced a strong burden of proof.

This seminar presents the relationship between market structure and consumer outcomes, focusing on the mechanisms by which a more concentrated market can deliver better quality and innovation outcomes. This seminar particularly presents an ex-post assessment of the impact of the 2012 Hutchison/Orange merger on innovation and quality. Using data on 4G networks rollout, download and upload speeds, this work shows that mobile mergers can induce significant dynamic efficiencies and realise direct benefits to consumers. This has relevant implications for competition policy and how quality aspects and efficiencies are taken into account.

Biography

Xavier Pedrós is Economist at GSMA Intelligence. GSMA Intelligence is the analysis and research arm of GSMA, an international organization of mobile operators. Xavier has carried out research in the area of competition and regulatory economics, with a focus on the impact of market structure and competition in mobile markets. He has co-authored a recently published assessment of the impact of mobile mergers on quality and innovation. He has also produced research in the areas of fiscal policy in mobile markets and assessments of the economic impact of mobile telecommunications. Xavier holds a bachelor degree in Political Science at Pompeu Fabra University and a Master´s degree on Economics, with a focus on Industrial Organization and Finance, at Université Catholique de Louvain-la-Neuve.

November,29th 

15:30

Room 55.309

PhD Research Seminar

A brief 18 year career in music understanding

By Brian Whitman (formerly co-founder of The Echo Nest, Principal Scientist of Spotify)

Host: Xavier Serra

Abstract

In 1999 I put a somewhat stalled electronic music career on hold to investigate how people were discovering new artists. I was especially interested in how very independent and niche music was getting noticed. Could the new methods of digital distribution at the time allow for greater scale and reach of all types of styles and genres of music? Could natural language processing, signal processing and machine learning play a role in understanding music? Two graduate degrees, a few stints in research labs, a startup, seventy employees, fifty customers, a large acquisition, 150 million active users of our technology and eighteen years later, I've left Spotify to focus on something new. I'm giving a brief talk to discuss what I've learned about the field, how big academic ideas translated into the marketplace, and what could be next. This will be a very informal group discussion.

November,28th 

15:30

Room 55.309

Invited Research Seminar

Analyzing and Exploiting User-generated Listening Data for Listener Modeling and Music Recommendation

By Markus Schedl (Department of Computational Perception, Johannes Kepler University, Linz )

Host: Xavier Serra 

Abstract

Nowadays, music aficionados generate millions of listening events every day and share them via platforms such as Spotify, Last.fm, or Twitter. In 2016, the LFM-1b dataset (http://www.cp.jku.at/datasets/LFM-1b) containing more than 1 billion listening events of about 120,000 Last.fm users has been released to the research community and interested public. Since then, we performed various data analysis and machine learning tasks on these large amounts of user and listening data. The gained insights helped to develop new listener models and integrate them into music recommender systems, in an effort to increase personalization of the recommendations.
In this talk, I will report on our experiments with the LFM-1b dataset, focusing on the following topics:
- analyzing music taste around the world and clustering on the country level
- quantifying listener and country mainstreaminess
- music recommendation tailored to listener characteristics
- predicting user characteristics from music listening habits
- predicting country-specific genre preferences from cultural and socio-economic factors

November,16th 

15:30

Room 55.309

PhD Research Seminar

Gender and Science Journal Club

By Irene Torres , Adrián Ponce and Elisa Ruiz 

Host: Aurelio Ruiz

Abstract

Women in Science, Technology, Engineering and Mathematics (STEM) fields remain severely underrepresented. For instance, in Spain, women represent about 15% of full (catedras) professorships. Moreover, women are judged to be less competent, receive less payment and research facilities, and are less likely to be awarded research grants compared with male scientists. The different mechanisms leading to this disparity have been investigated and more is brought to light by ongoing research. In this talk we will explain the different challenges faced by women in STEM careers, the reasons and the mechanisms through which they emerge, and changes (big and small) that we can all do to improve the current dire scenario. We will also show how gender, race, class, and sexual identity discriminations are entangled and contribute to leaving out minorities from academia.

November,16th 

15:30

Room 52.s29

Invited Research Seminar

Challenges in Uncertainty Quantification in Medical Image Registration

By Hervé Delingette (INRIA in Sophia Antipolis, Francia)

Host: Miguel Angel Gonzalez Ballester

Abstract

Medical Image Registration is the key ingredient in  many aspects of computer-aided decision medical support systems. For instance it is a standard processing step in many pipelines for medical imaging, abd computer assisted surgery. As such registration would benefit from the development of principled strategies to analyze its output and quantify its uncertainty. In this talk, a generic Bayesian method for non rigid image registration will be presented leading towards an estimation of registration uncertainty. The accuracy of this uncertainty is then evaluated with  an (asymptotically) exact inference scheme based on reversible jump Markov Chain Monte Carlo (MCMC) sampling. Challenges for a tractable uncertainty estimation will be reported at this occasion.

November,15th 

15:30

Room 55.410

Invited Research Seminar

The Bioengineering Initiative at Children’s National Health System: Device Development for the Pediatric Environment

By Kevin Cleary (Children's National Medical Centre, Washington DC)

Host: Miguel Angel Gonzalez Ballester

Abstract

This talk will give an overview of work done in the first five years in the Bioengineering Initiative in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Medical Center, Washington, DC,
USA. The mission of the Bioengineering Initiative is to serve as an engineering research for the hospital and work with clinical partners to develop technology for minimally invasive interventions. The institute includes scientists, radiologists, and surgeons that are dedicated to improving the precision and decreasing the invasiveness of pediatric procedures.

November,14th 

15:30

Room 55.309

Invited Research Seminar

Parsing and Grammatical Inference as Constraint Solving

By Dr. Veronica Dahl

Host: Horacio Saggion

Abstract

We describe devised a new, linguistically motivated model of parsing and grammatical inference- the Womb Grammar Model (WGM)-, which allows the application of resources and tools of one language to another, making it possible to study under-resourced languages and dialects, or specialized uses of a same language, e.g., tweeter or SMS (short message service). Our model can particularly help linguists keep up with the rate of grammar discovery needed in our Babel-ish world: just as human wombs can generate any race from an appropriately fertilized egg, our linguistic "womb" can generate, from a language’s known grammar (or from a more abstract, “universal” grammar), the grammar of a different language, given only a set of positive, correct, and representative input sentences of that language, plus its associated lexicon. Our model has received peer validation as a model of parsing and of syntax inference with good semantics integration possibilities. Several experimental implementations  have supported applications to efficient, failure-based parsing, second language tutoring, and language acquisition. Visualization interactions were also studied. A strong proof-of-concept was provided through my student Ife Adebara’s thesis on inferring the grammar of a subset of Yoru`ba ́ noun phrases from that of an English noun phrase grammar. This work demonstrates that the WGM works well even with source languages not closely related to the target.

Biography

Verónica Dahl is an Argentine/Canadian computer scientist who is recognized as one of the 15 founders of the field of logic programming. She has contributed over 100 scientific publications in the fields of computational linguistics, deductive knowledge bases, computational molecular biology and web based virtual worlds. She has received numerous scientific awards-  such as the Calouste Gulbenkian Award for Science and Technology-, and a few literary awards as well. Her greatest ambition is to help bridge the gap between the formal and the humanistic sciences, in the hopes that this will be conducive to an overall more balanced world. She is presently Professor Emeritus at Simon Fraser University. Her research is supported by NSERC.

November,13th 

15:30

Room 55.309

PhD Research Seminar

Women in AI, Engineering and Computer Science  

By Dr. Veronica Dahl

Host: Aurelio Ruiz

Abstract

Women constitute a majority in the present world, yet are grossly underrepresented in many science. We discuss the societal causes of this curious phenomenon focusing of female underrepresentation in Engineering and in Computing Science -in particular in AI-, from a multicultural perspective. We contrast the specific cases of Argentina, Spain and Canada, trying to shed light upon the causes of female underrepresentation. As well, we discuss possible actions that could heal these causes and could help the integration of women into these fields.

Biography

Verónica Dahl is an Argentine/Canadian computer scientist who is recognized as one of the 15 founders of the field of logic programming. She has contributed over 100 scientific publications in the fields of computational linguistics, deductive knowledge bases, computational molecular biology and web based virtual worlds. She has received numerous scientific awards-  such as the Calouste Gulbenkian Award for Science and Technology-, and a few literary awards as well. Her greatest ambition is to help bridge the gap between the formal and the humanistic sciences, in the hopes that this will be conducive to an overall more balanced world. She is presently Professor Emeritus at Simon Fraser University. Her research is supported by NSERC.

November, 9th 

15:30

Room 54.006

PhD Research Seminar

Mendeley reference manager and research network

By Gemma Álvarez

Host:  Aurelio Ruiz

Abstract

During the presentation we will talk about:

Mendeley as a reference manager:

​- How to import your documents and references into your ​own library

​- How to generate citations and bibliographies with MS Word and LibreOffice Plug-ins

Mendeley as a research network:

- Connect and collaborate with researchers

- Your professional researcher profile

IMPORTANT: Previous tasks to do before the session (we recommend you to bring your on laptop. Please fill this form if you plan to attend):

1. Create your Mendeley account.

2. Access the upgraded Mendeley Institutional Edition (MIE) as a UPF's member to get the advantages.

3. Download the Mendeley Desktop version into your device.

November, 9th 

12:30

Auditorium

DTIC-MdM Research Seminar

Open Debate Machine Learning and Human Behaviour

Within the context of the HUMAINT project and the World Science Day for Peace and Development (November 10th), we will have the opportunity to start an open discussion about aspects linked to the relations between technological development and human behaviour, related to  some of the research carried out at our ICT Department.

Program:

  • Introduction by Emilia Gómez and the new JRC project HUMAINT:"machine learning and human behaviour"
  • Vladimir Estivill - Ethical decision making in robots
  • Carlos Castillo - algorithmic bias in machine learning, related to the project awarded by Data Transparency Lab
  • Xavier Serra, cultural bias in computational models, linked to the work at the ERC project CompMusic
  • Open discussion.

Followed by some snacks at the hall of the auditorium to continue discussions (to make an estimation of attendants, please leave your name and surname in this doodle)

October,26th 

15:30

Room 55.410

PhD-MdM Research Seminar

DKPro Core - With Reusable and Interoperable Components Towards Reproducible Experiments

By Dr. Richard Eckart de Castilho

Host: Jens Grivolla

Abstract

Vast amounts of information are stored in unstructured formats such  as audio, video, or plain text. The field of Natural Language Processing (NLP) addresses   this by providing not only methods but also many ready made tools to analyze  text and to structure it in many ways ranginge from simple segmentation to complex  semantic analysis. However, it is often difficult to incorporate these tools into new experimental setups because the complexities of installation, configuration,  data transformation and interoperability in general are often underestimated.  This negatively affects the reproducibility of such experiments.  This talk will give an introduction to doing NLP with DKPro Core and the DKPro   eco-system with a focus on the approaches employed to promote and facilitate   reproducible experiments and the development of NLP-based applications.

Biography

About the speaker: Dr. Richard Eckart de Castilho is a senior research and technical lead at the Ubiquitous Knowledge Processing Lab, TU Darmstadt, the lead developer of DKPro Core,   member of the Apache UIMA project, and maintainer of the Apache uimaFIT library [1].  [1] https://www.ukp.tu-darmstadt.de/people/senior-staff/richard-eckart-de-castilho/

October,25th 

16:30

Room 55.309

Invited Research Seminar

Decoding Neural Drive for New Generation of Neurorehabilitation Systems

By Ivan Vujaklija 

Host: Laura Becerra-Fajardo

Abstract

The generation of a movement is the combination of discrete events (action potentials) generated in the brain, spinal cord, nerves, and muscles. These discrete events, discharged in the various parts of the neuromuscular system, constitute the neural code for movements. Recording and interpretation of this code provides the means for decoding the motor system. Currently we are able to detect and process the available information content only partially and this limitation impedes us to establish widely applicable man-machine interface systems. I will present the developments done within the ERC funded project “DEMOVE”, and recently at the Bioengineering Department at Imperial College London on advanced electrode systems for in-vivo electrophysiological recordings in humans and new computational methods/models for extracting functionally significant information on human movement. The focus of these developments is on providing the link between the cellular mechanisms and the behaviour of the whole motor system in order to establish clinically viable and effective neurorehabilitation technologies.

Biography

Ivan Vujaklija received the engineering degree in Electrical Engineering and Computer Science from the University of Belgrade, Serbia, in 2011, and the M.Sc. degree in Biomedical Engineering from the University of Lübeck, Germany in 2013. He obtained his PhD degree in human medical sciences at the University of Göttingen, Germany in 2016 while working as a research assistant at the Institute of Neurorehabilitation Systems at the University Medical Center Göttingen, Georg-August University, Germany. From 2012 until 2014 he worked for Ottobock Healthcare GmbH, Duderstadt, Germany, one of the world leading prosthetic manufacturers. In 2014 and 2015 he was a research fellow at Arizona State University and Medical University of Vienna respectively. In 2017 he moved to the Department of Bioengineering at the Imperial College London to work as a research associate. His research interests include bio-signal processing, advanced control algorithms, robotics, translational neurorehabilitation and neural control of movement.

October,19th 

15:30

Room 55.309

PhD Research Seminar

Introduction to PhD Seminars

By Aurelio Ruiz Garcia 

September,14th 

15:30

Room 55.309

Invited Research Seminar

Large Research Infrastructures and managing enormous amounts of data: The TOMCAT experience at the Swiss Synchrotron

By Anne Bonnin on behalf of the TOMCAT team

Host Bart Bijnens

 

Abstract

Nowadays, Tomographic Microscopy is a well-known technique used to visualize and study in 3D internal structure and material properties of a variety of samples. Thanks to the photon density reached by third generation synchrotron radiation large-scale facilities, the high-brilliance and high–coherence of synchrotron light enables the detection of micron-sized details in millimetre-sized samples and within few minutes.

The TOMCAT (TOmographic Microscopy and Coherent rAdiology experiments) Beamline of the Swiss Light Source offers such unique opportunity, thus providing routinely fast, non-destructive, high resolution, quantitative investigations on a broad kind of materials. With the recent advanced technologies, 3D datasets can even be acquired within seconds involving the acquisition of hundreds of data to cover cm-sized samples. Indeed, the acquisition rate can reach up to 8GB per second of image data. Therefore, the task of collecting, transferring, storing, sharing and analysing such amount of tomographic big data leads to the need of new robust solutions. Within the context of a selected big scale projects, we will present in this talk the current status of the data management from acquisition to storage and the future challenges that X-PCI implies.

 

Biography

Anne Bonnin studied physics and material science at the University Lyon 1. Graduated of a master in theoretical physics and a master in applied physics, she then received her PhD in Physics from the National Institute of Applied Sciences of Lyon (INSA-Lyon, France).

During her PhD, she studied the physical properties of materials in order to discriminate them by means of dual-energy tomography, diffraction and Compton scattering. After graduating with the highest honors, she spent four years in the X-ray imaging group at the European Synchrotron Radiation Facility (Grenoble, France), first in collaboration with the CEA-Cadarache on a project to developed diffraction tomography (XRD-CT) at the ID22Ni beamline (now ID16b) and then on projects in paleontology and material science at the ID19 beamline. In April 2014, she joined the X-ray tomography group at the TOMCAT Beamline (Villigen, Switzerland) to be in charge of the TOMCAT nanoscope development. As local contact, she collaborates with international researchers in material sciences, paleontology and biomedical applications.

Specialized in X-ray imaging (micro and nano-tomography, single-distance phase-retrieval) and powder diffraction (XRD-CT), her research interests focus on the development of new imaging methods to characterize materials and understand their behavior. Finally, she leads the Heart Imaging Project at PSI, which is part of an international collaboration aiming at better describing and understanding the cardiac remodelling processes in rat and human hearts.

September,13th 

15:00

Room 55.309

Invited Research Seminar

Machine Listening in Urban/Bio-Acoustic Environments & tools for sustainable MIR research
 

By Justin Salamon

Host Emilia Gomez

Abstract

Internet of Things (IoT) sensor networks, and particularly acoustic sensor networks, open up new opportunities in large-scale, data-driven analyses of acoustic environments. Examples include (but are not limited to) monitoring noise sources in urban environments or monitoring the migration of bird species based on their vocalizations. In both cases, it is necessary to identify and classify specific sound events in an audio signal based on their source, be it jackhammers and car honks or different species of migrating warblers. In this talk I'll present our work on machine listening algorithms for source identification in acoustic environments as part of the Sounds of New York City (SONYC) and BirdVox projects. Finally, I will also give a brief overview of the tools/resources we have been developing for sustainable MIR research including JAMS, mir_eval, Scaper and Massage.

 

Biography

Justin Salamon is a Senior Research Scientist at New York University's Music and Audio Research Lab (MARL) and Center for Urban Science and Progress (CUSP). He obtained a B.A. (Hons.) in Computer Science from the University of Cambridge, UK, in 2007, and an M.Sc. (2008) and Ph.D. (2013) in Computer Science from the Music Technology Group (MTG) of Pompeu Fabra University (UPF), Barcelona, Spain, specializing in sound and music computing. He was a visiting researcher at the Sound Analysis-Synthesis research team of the Institut de Recherche et Coordination Acoustique/Musique (IRCAM), Paris, France. His research interests include digital signal processing, machine learning and data mining, with applications to machine listening, music information retrieval, bioacoustics and environmental sound analysis. For further information and a full list of publications please see: www.justinsalamon.com

September,7th 

15:00

Room 55.309

Invited Research Seminar

Language Modelling for Automatic Music Transcription

By Andrew McLeod

Host Sergio Oramas

Abstract

Abstract: Automatic music transcription (AMT) is defined as the process of converting an acoustic music signal into some form of human- or machine-readable musical notation. Advances in automatic music transcription performance have been disappointingly slow, with accuracy still falling well below that of human experts at the task. In this presentation, I argue that this problem cannot be sufficiently solved without the use of some sort of music language model, trained on symbolic music data. To that end, I first present an HMM-based voice separation model which works on symbolic music data, both quantized and performed, and also show results of integrating it with an acoustic pitch-detection model for a cappella voice separation from an audio signal. I also discuss work on metrical structure (time signature) detection based on rhythmic analysis using a lexicalized PCFG, arguing that such a grammar can capture the long-range dependencies of musical rhythms. Finally, in future work, I look ahead to the integration of models such as these into a full AMT system with an acoustic model.

 

Biography

Andrew McLeod is a PhD student under the advisement of Mark Steedman at the University of Edinburgh, School of Informatics, Institute for Language, Cognition and Computation (ILCC), set to graduate in early 2018. He received a Bachelors and Masters in Mathematics and Computer Science from Emory University in the USA in 2013. His PhD subject is automatic music transcription, specifically working with symbolic music data to create a music language model based on music theory for the task.

2016-2017

Historical, by A. Faridi (Research Seminar Academic coordinator)

 

 

Title,  Speaker  and host

Abstract

 

Biography

Invited Research Seminar

July 21st
12:00 hours

Room 55.309 

"Multi-pitch detection and voice assignment for a cappella recordings of multiple singers"

By Rodrigo Schramm

Host: Emilia Gómez

This research focuses on a multi-pitch detection and voice assignment method applied to audio recordings containing a cappella performance with multiple singers. A novel approach combining an acoustic model for multi-pitch detection and a music language model for voice separation and assignment is proposed. The acoustic model is a spectrogram factorization process based on Probabilistic Latent Component Analysis (PLCA), driven by a 6-dimensional dictionary with pre-learned spectral templates. The voice separation component is based on hidden Markov models that use musicological assumptions. By integrating the models, the system can detect multiple concurrent pitches in vocal music and assign each detected pitch to a specific voice corresponding to a voice type such as soprano, alto, tenor or bass (SATB).

 

Rodrigo Schramm received his PhD in Computer Science from the Federal University of Rio Grande do Sul (UFRGS)/Brazil in 2015, where he is currently a faculty member. Between 2013 and 2014, he was visiting fellow at ICCMR - Interdisciplinary Centre for Computer Music Research - Plymouth University/UK. In 2016, he was awarded by the Royal Academy of Engineering/UK with the Newton Research Collaboration Programme Award. Currently, he is conducting research at the C4DM (QMUL) in London, focusing his activities on the development of techniques for automatic transcription of audio recordings containing multiple singers.  

professor.ufrgs.br/rschramm

 

Invited Research Seminar

 

June, 22nd 2017

16:00

Auditorium

 

Intrinsic Coupling Modes and Cognition

by Prof. Dr. Andreas K. Engel

Hosted by: Gustavo Deco

Intrinsic coupling constitutes a key feature of ongoing brain activity, which exhibits rich spatiotemporal patterning and contains information that influences cognitive processing. I will discuss evidence for two distinct types of intrinsic coupling modes which seem to reflect the operation of different coupling mechanisms. One type arises from phase coupling of band-limited oscillatory signals, whereas the other results from coupled aperiodic fluctuations of signal envelopes. The two coupling modes differ in their dynamics, their origins, their putative functions and with respect to their alteration in neuropsychiatric disorders. I will propose that the concept of intrinsic coupling modes can provide a framework for capturing the dynamics of intrinsically generated neuronal interactions at multiple spatial and temporal scales.

Andreas K. Engel studied medicine and philosophy at Saarland University, Homburg, at the Technical University of Munich, and at the Goethe University Frankfurt in Germany. Having completed his medical exams, he obtained his doctorate (Dr. med.) from the Technical University Munich in 1987. Between 1987-1995 he worked as a post-doctoral fellow with Wolf Singer at the Max Planck Institute for Brain Research, Frankfurt, Germany. From 1996-2000, Engel headed a research group at the Max Planck Institute for Brain Research which was funded by the Heisenberg Program of the German Research Foundation (DFG). Between fall 1997 and summer 1998, he also was affiliated as a Daimler-Benz Fellow to the Berlin Institute for Advanced Study. From 2000-2002, he worked at the Jülich Research Centre as head of the Cellular Neurobiology Group at the Institute for Medicine. In 2002, he was appointed to the Chair of Neurophysiology at the University Medical Center Hamburg-Eppendorf. Engel is a member of the Academy of Sciences and Humanities in Hamburg. Since 2011, he is the coordinator of Collaborative Research Centre SFB 936 „Multi-Site Communication in the Brain“ (with C. Gerloff, Dept. of Neurology, UKE). In 2011, Engel received an ERC Advanced Grant (with P. König, University of Osnabrück, Germany).

Phd Seminar

June, 20th 2017

11:00- 55.309

Statistical course and Design of Experiments

by Simone Tassani

The course (6 hours: 30 of May, 6 and 20 of June, 11h - 13h) will cover General Linear Models, Management of Error and introduction to Design of Experiment. Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group  

Invited Research Seminar

June, 19th 2017

12:00

55.410

Computational modeling of musculoskeletal functional anatomy from medical images and cadaver data

by Yoshinobu Sato

Hosted by: Miguel A. González Ballester

Due to increasing interest to healthy life expectancy, the significance of the musculoskeletal system is recognized more than before. In addition to medicine, musculoskeletal anatomy is related to sports science, art, computer graphics and so on. In this talk, computational modeling of functional anatomy of the musculoskeletal system is presented, which is under development in the “Multidisciplinary Computational Anatomy” project conducted by multi-institutional collaboration in Japan. The models consist of mathematical and statistical models on bone-muscle relations, muscle fibers, bone orientations at the standing position, articular motions, and bone micro-structure from the aspect of function, as well as deformations due to osteoarthritis from the aspect of pathology. This model is constructed from clinical CT data and other modality data, including micro-CT, histology, X-ray, ultrasound images, in addition to 3D measurement data obtained from cadaver experiments. Fundamental technologies for representation and construction of the model are presented and its applications to segmentation, muscle fiber modeling, and computer-aided diagnosis and therapy are overviewed. Yoshinobu Sato received his B.S., M.S. and Ph.D degrees in Information and Computer Sciences from Osaka University, Japan in 1982, 1984, 1988, respectively. From 1988 to 1992, he was working at the NTT Human Interface Laboratories. In 1992, he joined Osaka University Medical School. From 1996 to 1997, he was a Research Fellow at the Surgical Planning Laboratory, Harvard Medical School and Brigham and Women's Hospital. From 2014, he is a Professor of Information Science at Nara Institute of Science and Technology (NAIST), Japan. Dr. Sato was Program Chair of MICCAI 2013. He is an editorial board member of Medical Image Analysis journal and International Journal of Computer Assisted Radiology and Surgery.

PhD  Research Seminar

June, 15th 2017

12:30 h

55.410

Ethical issues and data protection, session 2 CIREP-UPF

Speaker: Silvia Losa & Josep Blat

Host: Aurelio Ruiz

CIREP-UPF (Internal Committee for the Ethical Review of Projects) aims at improving ethical standards and personal data protection in research and academic practices related to human beings, within the UPF community. The first review of a research project by CIREP took place about a year ago.

During this session, we will review the ethical process and the information provided already by stsudents, analysing their content

 

Invited Research Seminar

June, 15th 2017

12:30 h

55.410

Generative Models of Drawing and Sound

Speaker: Douglas Eck

Hosted by: Xavier Serra

I'll give an overview talk about Magenta, a project investigating music and art generation using deep learning and reinforcement learning. I'll discuss some of the goals of Magenta and how it fits into the general trend of AI moving into our daily lives. I'll talk about two specific recent projects. First I'll discuss our research on Teaching Machines to Draw with SketchRNN, a LSTM recurrent neural network able to construct stroke-based drawings of common objects. SketchRNN is trained on thousands of crude human-drawn images representing hundreds of classes. Second I'll talk about NSynth, a deep neural network that learns to make new musical instruments via a WaveNet-style temporal autoencoder. Trained on hundreds of thousands of musical notes, the model learns to generalize in the space of musical timbres, allowing musicians to explore new sonic spaces such as sounds that exist somewhere between a bass guitar and a flute. This will be a high-level overview talk with no need for prior knowledge of machine learning models such as LSTM or WaveNet. Doug is a Research Scientist at Google leading Magenta, a Google Brain project working to generate music, video, image and text using deep learning and reinforcement learning. A main goal of Magenta is to better understanding how AI can enable artists and musicians to express themselves in innovative new ways. Before Magenta, Doug led the Google Play Music search and recommendation team. From 2003 to 2010 Doug was an Associate Professor in Computer Science at the University of Montreal's MILA Machine Learning lab, where he worked on expressive music performance and automatic tagging of music audio.

Invited Research Seminar

June, 8th 2017

15:30 h

55.309

Neural mechanisms of sensor

Speaker: Tatiana Pasternak, Ph.D.  

Host: Rubén Moreno Bote

To perform a ubiquitous task of comparing sensory stimuli across time and/or space, subjects must identify these stimuli, retain them in memory and retrieve them at the time of comparison. Thus, the neuronal circuitry underlying such tasks must involve cortical regions sub-serving sensory processing, maintenance, attention and decision-making. In our work, we have been examining the neural substrates of memory-guided comparisons of visual motion, with the focus on two reciprocally interconnected regions, the lateral prefrontal cortex (LPFC) and the motion processing area MT. We have characterized the activity in both areas during motion comparison tasks, identifying signals in the LPFC likely to represent bottom-up motion information supplied by MT and signals in area MT likely to represent the top-down influences from the LPFC. I will discuss the evidence that the content of task-related activity in MT and LPFC is a product of continuous interactions between neurons in the two areas during which they process and exchange signals generated during all stages of memory-guided sensory comparisons.

My current research at the Department of Neuroscience of the University of Rochester is focused on the mechanisms underlying processing and storage of visual motion information in primate cortex. In our studies we combine single cell recordings, microstimulation, reversible inactivation with psychophysical measures of visual performance. We have shown that neurons in visual cortical area MT, strongly associated with processing of visual motion, also participate in the storage and the retrieval/comparison operations required by working memory tasks.

 

Phd Seminar

June, 6th 2017

11:00 - 55.309

Statistical course and Design of Experiments

by Simone Tassani

The course (6 hours: 30 of May, 6 and 20 of June, 11h - 13h) will cover General Linear Models, Management of Error and introduction to Design of Experiment. Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group  

Invited Research Seminar

June, 1st

15:30 h

55.309

The portability of Learning Analytics applications and learning designs

By Dai Griffiths

Hosted by: Davinia Hernández-Leo

The desire to leverage the data generated during educational activities is observable in most areas of education, and in many countries. Much of the most interesting work along this line goes under the banner of ‘learning analytics’. However, this work is often carried out in isolation, in individual institutions, or, sometimes, in individual ministries of education. There are many potential benefits to sharing this work, so that the infrastructure for learning analytics, and learning designs which it makes possible, can be deployed in different place. But this is more complex than it might appear. In this seminar I will explore three aspects of this problem.

1) Technical issues. There is substantial activity around technical specifications for representing learning activities, focused around Caliper (from IMS), and xAPI (from ADL). Nevertheless, a lot of work remains to be done. I will report briefly on work being done by Jisc in the UK to create an open learning analytics platform, and to develop data collection methods for UK higher education institutions.

2) A clash of approaches to ethics and privacy. Learning Analytics can be seen from the perspectives of both operations research and academic research. The two traditions have contrasting approaches to ethics and data governance, with differing resolutions in different places.

3) A number of wider policies regarding educational content, management and finance have an impact on the success or failure of learning analytics in different contexts.

I propose that unless we pay attention to the social and regulatory aspects of learning analytics, we may misunderstand the reasons why applications are successful or not, and are unlikely to be successful in transferring applications from one context to another. 

Dai Griffiths is a professor in the School of Education and Psychology at the University of Bolton. His background is in the arts and in education, and he has taught at many levels including primary and secondary education, higher education and continuing education, and in industry. From the early 1990s he worked on a wide range of aspects of technology and education, as a developer, researcher and project manager, before taking on his current role. He has published extensively on the design of learning activities and their technological support, and on adaptive learning with IMS Learning Design. This led to his current engagement with learning analytics, through Cetis, leadership of the Bolton contribution to the LACE project, and work on the Jisc xAPI profiles.

Phd Seminar

May, 30th 2017

11:00

55.309

Statistical course and Design of Experiments

by Simone Tassani

The course (6 hours: 30 of May, 6 and 20 of June, 11h - 13h) will cover General Linear Models, Management of Error and introduction to Design of Experiment.  Dr. Simone Tassani is senior researcher of the Multiscale and Computational Biomechanics and Mechanobiology (MBIOMM) team in the SIMBiosys group

Invited Research Seminar

May 29th, 2017

16:00

55.309

Basis models of musical expression for creating and explaining music performances

by Maarten Grachten
Hosted by: Emília Gómez
Expression in music performance is an important aspect of score-based music traditions such as Western classical music: Music performed by skilled musicians can be captivating as much as an improper performance can put listeners off.  Computational modeling of expression in music performance is a challenging and ongoing effort, aiming both at a better understanding of the underlying principles, and at novel applications in music technology. In this talk, we will present a recently proposed modeling framework for musical expression, utilizing basis-function representations of score information. We show how it can be used for predictive modeling---to generate an expressive performance of a musical score---as well as for explanatory purposes. We illustrate this framework both in the context of solo piano music and in classical symphonic music. Maarten Grachten holds a Ph.D. degree in computer science and digital communication (2006, Pompeu Fabra University, Spain). He is a former member of the Artificial Intelligence Research Institute (IIIA, Spain), the Music Technology Group (MTG, Spain), the Institute for Psychoacoustics and Electronic Music (Belgium), and the Austrian Research Institute for Artificial Intelligence (OFAI, Austria). Currently, he is a senior researcher at the Department of Computational Perception (Johannes Kepler University, Austria). Grachten has published in and reviewed for numerous international journals and conferences, on topics related to machine learning, music information retrieval, affective computing, music cognition, and computational musicology. His current research focuses on computational modeling of musical expectation and expressive performance.

Invited Research Seminar

May 29th, 2017

15:30

55.309

Movement Sound Interaction: from creative applications to rehabilitation

by Frederic Bevilacqua
 
Hosted by: Emília Gómez
I will present an overview of the research we have been conducting at IRCAM on gesture capture and analysis. We have been collaborating with various composers, performers, which allows us to develop important concept and paradigms for the development of musical interactive systems. For examples, we have developed various augmented instruments by adding motion-capture systems to acoustic instruments such the violin. This allows us to study instrumental gestures and develop software for following/recognising gestures. We have also developed specific tangible interfaces such as the MO - Modular Musical Objects, or more recently the RIoT that allows for interacting with digital sound environments. Finally, we will present some recent studies and applications related to sensori-motor learning and embodied music cognition.
Frédéric Bevilacqua is the head of the Sound Music Movement Interaction team at IRCAM in Paris His research concerns the modeling and the design of interaction between movement and sound, and the development of gesture-based interactive systems.

Invited Research Seminar 

May 26th, 2017

16:00

55.410

What makes hue special?

by Ivar Farup

Hosted by: Marcelo Bertalmio

When Riemann presented his non-Euclidean geometry in 1854, he suggested that 'the only simple notions whose specializations form a multiply extended manifoldness are the positions of perceived objects and colours'. For more than a century following his discovery, various non-Euclidean colour geometries were developed by Helmholtz, Schrödinger, MacAdam, Silberstein, Stiles and others, mainly for the accurate computation of perceptual colour metrics. From a colour order perspective, it was observed by Judd in the 1940-ies that the human visual system is more sensitive to changes in colour hue than to changes in lightness and chroma – a phenomenon he denoted 'hue super-importance'. This indicates a negative curvature of colour space. Resnikoff demonstrated from an axiomatic point of view in 1974 that the colour space must be either Euclidean or hyperbolic, i.e., negatively curved. Despite these indications from diametrically opposite approaches, Euclidean colour spaces have been of almost unique and undisputed use in colour image processing for the last decades. For applications such as gamut mapping and HDR image rendering, artificial tricks have been introduced in the algorithms in order to prevent unacceptable hue changes. In this talk, I will discuss this issue, and propose a direction for a different way to deal with the hue in colour image processing.

Ivar Farup is a professor of computer science and study program leader for bachelor in engineering – computer science at NTNU in Gjøvik. He holds a MsC in theoretical physics form NTH (Norway) in 1994, and a PhD in mathematics from University of Oslo in 2000. His research interests lie are colour science and image processing.

Invited Research Seminar

May 23rd, 2017

15:30

Room 55.309

Microscopic crowd modeling and simulation: an holistic approach

Speaker: Julien Pettre 

Host: Josep Blat

Crowd simulation allows to reproduce, predict or understand collective human motions. It has application in various field, such as architecture, urban design or computer animation. Many simulation algorithms were proposed to simulate crowds. How do they work? How they were designed? In this talk, we will describe our efforts in the observation of human crowds to understand how individuals behave in such a context, as well as the basic principles of crowd simulation. More especially, we will describe velocity-based simulation models, and some of their variants.  Julien Pettré is research scientist at Inria in Rennes, member of the Lagadic team. He obtained a Ph.D. in robotics in 2003 from the University of Toulouse, he spent a postdoctoral stay at EPFL, before joining Inria in 2006. His research interests include robotics, computer animation, virtual reality, crowd simulation, motion planning, and human motion simulation. 
May

Integrative Research Seminar

Wed
April 26th, 2017
12:30
Auditorium

Synthesizing consciousness: science, technology and society

by Paul F.M.J. Verschure

Understanding the nature of consciousness is one of the grand outstanding scientific challenges of great importance both to understand who we are and of significant practical value. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The Distributed Adaptive Control theory of consciousness (DACtoc) proposes answers to these three challenges that will be presented in this talk. I will highlight some of the functional and mechanistic aspects of DACtoc showing how DACtoc has informed our understanding of core brain mechanisms of perception, cognition and action and given rise to one of the most effective neurorehabilitation method available today. An important consequence of DACtoc is that if we aim to build socially capable machines they must become conscious raising further important questions on how we can co-exist with them.

I will also give a short overview of the history of SPECS at DTIC covering 2006-2017 and explain why we are now planning a move to IBEC.

References:

1.         Verschure, P.F.M.J., Synthetic consciousness: the distributed adaptive control perspective. Philosophical Transactions of the Royal Society B: Biological Sciences, 2016.371.                              

Paul F.M.J. Verschure

PhD Research Seminar

April 25th

10:30

Room 55.309

Design for creative play (Thanks to U.S. Consulate General in Barcelona, in the context of the cooperation for the American Space)

Speaker: Eric Rosenbaum
Hosted by: Aurelio Ruiz

Eric Rosenbaum will describe some of the works he has been working on recently, including live demos for some of them, and will establish a discussion with PhD students around the challenges in achieving sustainable social impact from research activities.

 

   

Scratch Team at MIT Media Lab. Co-inventor of Makey Makey.

I design for creative play. My tools are all about bringing your imagination to life by helping you make things you care about. I love to see how using my tools can transform people's sense of what they can make and who they can become.

I am currently working with the Scratch Team at MIT Media Lab. I have also recently worked with Google Creative Lab and NYU Music Experience Design Lab. In 2015, I completed my PhD at MIT Media Lab in the Lifelong Kindergarten group with a dissertation entitled "Explorations in Musical Tinkering." Before my time at the Media Lab, I worked at MIT Teacher Education Program, creating learning games; Concord Consortium, creating molecular dynamics simulations for kids; and Six Red Marbles, creating animations for music education. I hold a Master's in Technology in Education from Harvard Graduate School of Education, and a Bachelor's in Psychology and Mind/Brain/Behavior from Harvard College. 

I enjoy playing the trombone with the Opposite People.  

Invited Research Seminar

April 20th

15:30

Room 55.309

Considerations about space in acousmatic music. Expanding ideas into multichannel formats

Speaker: Daniel Schachter
Hosted by: Andres Lewin

The relation between sound and space has always been a central concern for composers of acousmatic music and spatial distribution is undoubtedly a part of the conception of musical works. In this way, composers have at their disposal the possibility of defining which will be the final concert format for each of their compositions.  On the other hand technological advances allow the listener to access and choose more than one way of listening to music and in recent years the installation of multichannel audio home systems has become more and more usual, while the concert venues have incorporated multichannel options as a standard for the concert.

However, stereo remains as the most widely used format for CD distribution as well as for radio broadcasting.  This situation is undoubtedly decisive for the composer’s perspective. In fact, composers in some cases think their music in stereo and afterwards need to extended their thought into 6 or 8 channels for the concert, or on the contrary they may originally think their sound discourse in multiple channels with the concert in mind, and after that are forced to think on a stereo reduction for recording and broadcasting.  This talk will propose some compositional strategies, considering that the multichannel expansion of an original stereo can have similar textural characteristics that the orchestration in traditional instrumental music, and that the stereo reduction of a multichannel original may also be compared with the piano reduction of orchestral pieces.  This approach does not rule out the use of computer applications, but takes more into account the textural characteristics of musical works in order to face expansion and/or reduction. 

Later on Concert in Sala Polivalente at 19:30

http://phonos.upf.edu

Composer and researcher, born in Buenos Aires in 1953. Professor at the National University of Lanús (UNLa, Argentina) where he is also director of the UNLa’s Research Centre for Sonic and Audiovisual Arts (CEPSA). He taught electroacoustic composition at the Julian Aguirre Conservatory in Buenos Aires for almost 20 years and established the conservatory’s Electroacoustic Studio. He is a founder and Board Member of the RedASLA (Network for Latinamerican Sonic Arts) created in Santiago, Chile (2005). 

 

PhD Research Seminar

April 6th

15:30

Room 55.309

Communication skills in science: the research in 4 minutes competition


Speaker: Aurelio Ruiz

UPF has launched the "Research in 4 minutes" competition, with the purpose of underscoring the importance of communication skills in the dissemination of science. During this seminar, we will discuss some approaches to maximise the possibilities to succeed in this competition, as well as in any other context with limited time to present your work to non-experts. Suggested reading: Communication: Two minutes to impress .Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, having worked at the Computational Imaging and Simulation Technologies in Biomedicine Research Group, within the UPF Research Services as the Promotion Officer of the Department of Information and Communication Technologies and the associated Polytechnic School and currently, in the coordination of the María de Maeztu Research Program.
April

Integrative  Research Seminar

March 30th

12:30

Auditorium

Technology-enhanced music learning, health and well-being 

Speaker: Rafael Ramirez

 

Learning to play a musical instrument has been showed to provide several benefits for acquiring non-musical skills. However, there is a lack of generalised access to music education, and musical instrument learning is mostly based on the master-apprentice model in which the student’s interaction and socialization is often restricted to short and punctual contact with the teacher followed by long periods of self-study resulting in high abandonment rates. In such scenario, modern technologies are rarely employed and almost never go beyond audio and video recording. Our research aims to study how we learn musical instruments from a pedagogical and scientific perspective in order to create new interactive, assistive, self-learning, augmented-feedback, and social-aware systems complementary to traditional teaching. The aim is to allow more people to have access to music education, including people with motor disabilities, and reduce abandonment rates among music students. In this seminar, I will take the opportunity to present some of the research carried out in our research lab on areas such as technology-enhanced music learning, expressive performance modelling, accessible music interfaces, as well as some applications to health and well-being.

Dr. Rafael Ramirez is a Tenured Associate Professor and Leader of the Music and Machine Learning Lab at the Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona. He obtained his BSc in Mathematics form the National Autonomous University of Mexico, and his MSc in Artificial Intelligence and PhD in Computer Science from the University of Bristol, UK. For five years, Rafael was a Lecturer in the Department of Computer Science at the School of Computing of the National University of Singapore. He is currently principal investigator in the H2020 Research and Innovation TELMI (Technology-Enhanced Learning of Music Instruments) project. His research interests include music technology, machine learning, data mining, and their application to cognition, creative processes, accessible and brain-computer Interfaces, and health and well-being. He has published more than 100 research articles in peer-reviewed international Journals and Conferences, and acted as guest-editor of several special issues focused on machine learning and music. He currently acts as chair and program committee member for several machine learning and music technology conferences.

PhD Research Seminar

March 30th

15:30

Room 54.003

Mendeley reference manager and research network

Speaker: Gemma Álvarez

Host:  Aurelio Ruiz

During the presentation we will talk about:

Mendeley as a reference manager:

​- How to import your documents and references into your ​own library

​- How to generate citations and bibliographies with MS Word and LibreOffice Plug-ins

Mendeley as a research network: 

- Connect and collaborate with researchers

- Your professional researcher profile

IMPORTANT: Previous tasks to do before the session (we recommend you to bring your on laptop. Please fill this form if you plan to attend):

1. Create your Mendeley account.

2. Access the upgraded Mendeley Institutional Edition (MIE) as a UPF's member to get the advantages.

3. Download the Mendeley Desktop version into your device.

UPF Library

Invited Research Seminar

March 29th

11:00

Room 55.410

Style aware tone retargeting

Speaker: Rèmi Cozot 

Host:  Marcelo Bertalmío

The last trend in displays and TV is High Dynamic Range technologies, which provide high range of contrast. On the one hand, the vast majority of video content existing today is in Standard Dynamic Range (SDR) format and there is a strong interest in upscaling this content for High Dynamic Range (HDR) displays. This retargeting processing is called Tone Expansion (or Inverse Tone Mapping). On the other hand, HDR content must be downscaled to SDR format in order to be displayed on SDR displays. This processing is called Tone Mapping.  After a short introduction that presents the key elements related to lighting styles or aesthetics, we show that current Tone Expansion and Tone Mapping operators do not perform as well when dealing with content of various lighting styles/aesthetics. Then we propose a Tone Expansion method that adapts to the style of the video and ensure the lighting style fidelity.  Concerning Tone Mapping operators, many solutions have been designed for still images over the last decade; only few of them can cope with video sequences. Indeed, these operators tone map each frame of a video sequence separately, which results in the lost of the lighting style of the HDR content. We propose a method that aims at preserving lighting style (more especially temporal brightness coherency) when tone mapping video sequences.
 
Rémi Cozot (born 1968, France) is associate professor at the University of Rennes 1 and member of the IRISA Laboratory. He received his Ph.D and Habilitation to conduct researches respectively in 1996 and 2014. His main research topic concerns the preservation of a user’s intent when editing real or computer generated contents. This topic involves many scientific skills such as visual human perception, image and video analysis, computer graphics. He has been involved in HDR imagery since 2007 and participated in many French and European projects on HDR imaging. He is co-author of the chapter “video tone mapping” of the book entitled “High Dynamic Range Video - From Acquisition, to Display and Applications”.

Invited Research Seminar

March 28th

15:30

Room 55.309

Towards perceptually realistic visual experience

Speaker: Rafal Mantiuk

Host:  Marcelo Bertalmío

Today's computer graphics techniques make it possible to create imagery that is hardly distinguishable from photographs. However, a photograph is clearly no match to an actual real-world scene. I argue that the next big challenge is to achieve perceptual realism by creating artificial imagery that would be hard to distinguish from reality. This requires profound changes in the entire imaging pipeline, from acquisition and rendering to display, with the strong focus on visual perception.
 
The technical limitations of display technologies make it very hard to deliver perceptually realistic images. However, we can get much closer to that goal by a technique that involves optimization of perceptual match between real-world visual content and the rendition of that content on a display. Given the limitations of a display and a model of visual system, we can render images which are the closest match to the real-world experience. I will demonstrate such an approach on an example modeling night vision, in which we can simulate night vision or compensate for its limitations. The method can be used in games, driving simulators, or as a compensation for displays used under varying ambient light levels.
 
Rafal K. Mantiuk is a senior lecturer at the Computer Laboratory, University of Cambridge (UK). He received PhD from the Max-Planck-Institute for Computer Science (Germany). His recent interests focus on designing imaging algorithms that adapt to human visual performance and viewing conditions in order to deliver the best images given limited resources, such as computation time, bandwidth or dynamic range. He contributed to early work on high dynamic range imaging, including quality metrics (HDR-VDP), video compression and tone-mapping. More on his research can be found at: http://www.cl.cam.ac.uk/~rkm38/.

Invited Research Seminar

March 17th

15:30

Room 55.309

Spectral Learning of Natural Language Structure

Speaker: Xavier Carreras

Compositional structures abound in natural language, ranging from dependency relations between words, to entities in context, to sequences and trees that encode the linguistic structure of textual content.  The focus of this talk is in latent-variable compositional models of natural language structure that: (1) induce a latent n-dimensional representation for each element of the structure; and (2) learn operators for composing such elements into structures.
 
I will present the framework of spectral learning, that reduces the problem of learning compositional models to low-rank matrix learning.  I will then present some of my contributions on using spectral learning for various NLP problems. First, I will show that low-rank learning of compositional models benefits generalization to unseen structures, and I will present experiments on named entity extraction and syntactic parsing. Then I will move to the problem of learning weighted automata and grammars. In this setting, the key ingredient for spectral learning are Hankel matrices, which are matrices that capture the recurrence relations behind compositional models of language. I will show how various objectives can be formulated, including unsupervised learning of context-free grammars from strings of the language alone.
Xavier Carreras is a research scientist at Xerox Research Centre Europe since 2014. Xavier has a degree in Computer Science (2000) and a Ph.D. (2005) from the Technical University of Catalonia (UPC). From 2006 to 2009 he was a postdoc at MIT. From 2009 to 2014 he was research scientist at the UPC under the Ramon y Cajal program. 
 
His research interests are in the areas of Natural Language Processing and Machine Learning, with special interests in structured prediction problems in NLP, parsing methods, information extraction, machine translation, and dialogue systems. More recently he became interested in spectral learning methods for weighted automata and grammars, and their application to NLP problems. Xavier has published in the top-tier conferences and journals of the area, including ACL, TACL, EMNLP, CoNLL, COLING on the NLP side, and JMLR, ML, ICML, ECML, NIPS and AISTATS on the Machine Learning side. He got the best paper awards at CoNLL 2008 and EACL 2012.
 
Xavier was program co-chair of EMNLP 2016 and CoNLL 2009, and over the last 10+ years he has served regularly in the program committees of all major conferences. From 2011 to 2016, he was officer of SIGNLL, the special interest group of the ACL that organizes CoNLL. He has been invited lecturer at all the editions of the Lisbon Machine Learning Summer School (LxMLS), from 2011 to 2017. At UPC, he led the research team of the EU project XLike, on cross-lingual knowledge extraction. At Xerox Research, he has been involved in developing robust NLP tools for dialogue systems, focusing on quick adaptation to new tasks and textual domains.

Invited Research Seminar

March 16th

15:30

Room 55.410

Cardiac Modelling and Imaging Biomarkers

Speaker: Pablo Lamata

This talk presents specific steps in the journey towards the paradigm of an in-silico medicine, where healthcare is informed by computational models that (1) formulate our knowledge of cardiac physiology and physics, and that (2) integrate all the clinical data available of a patient into a cohesive picture. I will focus on the provision of a better management of cardiovascular diseases based on the interpretation of clinical data through the lenses of a computational model. The overarching hypothesis is that the process of model personalization reveals biomarkers with additional diagnostic and prognostic value. I will present examples of how models can better stratify anatomical remodelling, extract non-invasive central blood pressure, or characterise diastolic performance. I will finally discuss the opportunities in the mismatch between data and models, the potential synergies between mechanistic and statistical approaches, and the management of expectations towards the clinical translation. Dr. Pablo Lamata – Lecturer and Sir Henry Dale Fellow. http://cmib.website

PhD Research Seminar

March 16th

12:30

Room: 52.427

Software development best-practices for research reproduceability 

Speaker: Alastair Porter

Host:  Aurelio Ruiz

In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups.
A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time.
For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time.
In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available.
Alastair Porter received his Masters in Music Technology from McGill University in 2013. Since then he has been a researcher and developer in the Music Technology Group at the Universitat Pompeu Fabra. He is an active member of a number of open source communities, including the MusicBrainz project, an open database of information about music and musicians, both as a data contributor and a developer. As part of the CompMusic project he developed a software infrastructure for use by all of the researchers involved in the CompMusic project, as well as a web application used by thousands of users. In 2014 he helped to launch the AcousticBrainz project, which consists of a large software application built by many developers spread around the world, and used by thousands of other contributors.

Invited Research Seminar

March 15th

15:30

Room 55.309

Big Crisis Data - Social Media in Disasters and Time-Critical Situations

Speaker: Carlos Castillo

Social media is an invaluable source of time-critical information during a crisis. However, emergency response and humanitarian relief organizations that would like to use this information struggle with an avalanche of social media messages that exceeds human capacity to process. This talk focuses on the context, the methods, and the systems that are  used for processing social media messages under time-critical constraints. Carlos Castillo is Director of Research for Data Science at Eurecat. He is a web miner with a background on information retrieval, and has been influential in the areas of web content quality and credibility, and adversarial web search. He is a prolific researcher with more than 75 publications in top-tier international conferences and journals, receiving 9300+ citations. His works include a recent book on Big Crisis Data (http://bigcrisisdata.org/), as well as monographs on Information and Influence Propagation, and Adversarial Web Search.

Invited Research Seminar

March 10th

12:00

Room 55.309

Some Advances in Electrical Impedance Tomography and in Transcranial Electrical Stimulation

Speaker: Mariano Fernández-Corazza

Host: Federico Sukno

Using electrical impedance tomography (EIT) it is possible to estimate the electrical conductivity of the head tissues. In EIT, an electric current is injected on the boundary (the scalp) and the resulting electric potential is measured with an electrode array. There are two typical uses of EIT, either to reconstruct the conductivity distribution or map (reconstruction EIT), or to estimate a few conductivity values (parametric EIT). The parametric EIT or bounded EIT can be used to estimate the electrical conductivity values of the head tissues. In this line, and using parametric EIT from real measurements in humans, I’ll show that the there is an overestimation of the typical skull conductivity reported and widely-used in the literature. Reconstruction EIT can be used as a diagnostic tool, for example, to detect and map an acute stroke within a few hours from the stroke onset. In this line, we proposed the use of spatial filter techniques. I’ll show successful tests in phantoms and the results of ongoing tests in animals. Transcranial electrical stimulation (TES), including transcranial direct current stimulation (tDCS), is a set of therapeutic techniques that can modify cortical excitability as well as brain rhythms and networks by applying an electric current on the scalp. Its potential applications include the treatment of epilepsy, dementia, anxiety, and stroke rehabilitation. Its main advantage is that the electric current can be redirected to a particular region of interest (ROI) of the brain without affecting the whole brain as psychoactive drugs do. We work in the mathematical problem of determining current injection patterns given a ROI and safety constraints. In particular, I’ll show the optimal solutions based on the reciprocity principle. Mariano Fernández-Corazza is a Professor at the Universidad Nacional de La Plata, Argentina, where he received his Eng. (2007) and PhD (2015) degrees. He holds a post-doctoral fellowship of the Argentinian Research Council (CONICET). His doctoral and postdoctoral experiences include research visits to the NeuroInformatcis Center at the University of Oregon and the Electrical Geodesics Inc. Company, both located in Eugene, Oregon, US (2014, 2015, 2016). His research interests include statistical signal processing, adaptive spatial filters and electrical modeling of the human head applied to the forward and inverse problems in Electrical Impedance Tomography (EIT), transcranial Direct current Stimulation (tDCS), and Electroencephalography (EEG).

PhD Research Seminar

March 9th

15:30

Room 55.309

Tech transfer in the context of Open Science

Speaker: Xavier Serra

Host:  Aurelio Ruiz

Discussion about the new roles that technology transfer at universities is creating in the context of Open Science, and of specific initiatives driven by the MTG group, such as Essentia (technology licensing), Music Muni (Spin-off) and the Freesound API (Saas) Xavier Serra. Music Technology Group and Scientific Director of the MdM Strategic Research Program.

PhD Research Seminar

3rd, March

12:30 hours

52.s29

SpectralEdge: from science to startup.

Speaker: Roberto Montagna

Host:  Javier Vazquez Corral

Spectral Edge is both the name of a theorem and the name of a UK-based startup company. This talk will give a brief overview of the Spectral Edge core technology, which revolves around the theorem, and then will try to give an account of the challenges that Spectral Edge (the company) has faced and is facing in growing out of the academic environment.

Roberto Montagna is Principal R&D Engineer for Spectral Edge Ltd. He studied computer science in Verona (Italy), where he was awarded a MSc degree in 2007, and went on to enrol in a doctorate programme at the University of East Anglia (Norwich, UK) under the supervision of Prof Graham Finlayson. During this time he worked on various aspects of colour image processing. He was awarded a PhD degree in 2011, and started working for Spectral Edge Ltd immediately after.

Invited Research Seminar

2nd, March

15:30 hours

55.309

 

 

Creativity, deep symbolic learning, and the information dynamics of thinking

Speaker: Geraint A. Wiggins

Host: Xavier Serra

I present a hypothetical theory of cognition which is based on the principle that mind/brains are information processors and compressors, that are sensitive to certain measures of information content, as defined by Shannon (1948). The model is intended to help explicate processes of anticipatory and creative reasoning in humans and other higher animals. The model is motivated by the evolutionary value of prediction in information processing in an information-overloaded world.


The Information Dynamics of Thinking (IDyOT) model brings together symbolic and non-symbolic cognitive architectures, by combining sequential modelling with hierarchical symbolic memory, in which symbols are grounded by reference to their perceptual correlates. This is achieved by a process of chunking, based on boundary entropy, in which each segment of an input signal is broken into chunks, each of which corresponds with a single symbol in a higher level model. Each chunk corresponds with a temporal trajectory in the complex Hilbert space given by a spectral transformation of its signal; each symbol above each chunk corresponds with a point in a higher space which is in turn a spectral representation of the lower space. Norms in the spaces admit measures of similarity, which allow grouping of categories of symbol, so that similar chunks are associated with the same symbol. This chunking process recurses “up” IDyOT’s memory, so that representations become more and more abstract.

It is possible to construct a Markov Model along a layer of this model, or up or down between layers. Thus, predictions may be made from any part of the structure, more or less abstract, and it is in this capacity that IDyOT is claimed to model creativity, at multiple levels, from the construction of sentences in everyday speech to the improvisation of musical melodies.

IDyOT’s learning process is a kind of deep learning, but it differs from the more familiar neural network formulation because it includes symbols that are explicitly grounded in the learned input, and its answers will therefore be explicable in these terms.

In this talk, I will explain and motivate the design of IDyOT with reference to various different aspects of music, language and speech processing, and to animal behaviour.

Computational Creativity Lab

Queen Mary University of London

February

PhD Research Seminar

16th February

15:30 hours  

Room 52.s29

Session 1/2 : How to prepare a good scientific poster.

Session 2/2: Preparing your scientific poster.

Speaker: Antonios Lioutas

Host:  Aurelio Ruiz

During this seminar we will discuss the power of a scientific poster as a vehicle to pass along scientific knowledge, achievements and hypotheses.

  • The purpose of scientific posters
  • Elements of a poster
  • Common pitfalls and golden rules
  • How to prepare and present your poster

Antonios Lioutas is currently a postdoc researcher at the CRG. He is a biologist with a PhD in Biomedicine from the UPF (CRG). Alongside his research in the laboratory at the CRG he has formed a science communication agency together with 4 more researchers, www.biocomunicat.com. Apart from being passionate about his main work in the lab, cancer research, he has organized numerous interactive workshops and science dissemination events.

PhD Research Seminar

23rd February

15:30 hours  

Room 52.s29

AIn the second session, we will analyse the structure of scientific posters in light of what we have learned during the first session. We will discuss on how to ameliorate your poster in order to create a scientific poster with a great impact.

 

 

23rd February

12:30 hours  

AUDITORIUM

 

Overwhelmed by Information? Summarization, Simplification and information extraction at your fingertips. 

Speaker: Horacio Saggion

On-line news, social networks’ posts, e-mails, Wikipedia pages, .... the amount of  information available on-line is growing at unprecedented rates. In this context of information overload, automatic text summarization and information extraction are key Natural Language Processing (NLP) techniques  for  extracting the most salient information from a document in order to populate knowledge repositories or provide users with brief stand-alone document surrogates.

Besides the amount of text we have to deal with daily, there is a further problem:  certain types of texts such as news, which are produced for a general audience,  may be too difficult to read and understand by some people, because these texts have a  complex vocabulary and grammar. In this context, automatic text simplification is another NLP  technique which  aims at transforming a text into an equivalent which, using a simpler vocabulary or syntax, would be easier to read and understand.  

Over the past years, we have been working on two lines of research; on the one hand, we have investigated ways to extract and condense the essential  information from massive scientific literature and, on the other hand, we have carried out research to produce multilingual, adaptable,  text simplification solutions for digital inclusion.    In this seminar,  I will take the opportunity to present the work carried out on our research lab on these two distinctive, exciting, and relevant topics in the information society

Horacio is Profesor Agregado  at our Department since 2015 (previously Ramón y Cajal Fellow). He holds a Ph.D. in Computer Science from Université de Montréal. He works on automatic text summarization, text simplification,  information extraction, text processing in social media,  sentiment analysis and related topics. Before joining Universitat Pompeu Fabra, he worked  at the University of Sheffield for a number of UK and European research projects  developing competitive human language technology. He was also an invited researcher at Johns Hopkins University in 2001. He is principal investigator in the EU projects Dr Inventor (scientific summarization and extraction) and Able-to-Include (text simplification).  Horacio has published over 100 works in leading scientific journals, conferences, and books in the field of human language technology.  He is co-editor of a book on multilingual, multisource information extraction and summarization published by Springer  (2012).   Horacio has developed the freely available SUMMA summarization software distributed by UPF. He has received awards from institutions such as Fundación Antorchas, Vodafone Innovation, and Cátedra Telefónica/Universidad de Alicante.

Invited Research Seminar

14th February

15:30 hours  

Room 55.309

Human Computation and Crowdsourcing - Questions and Challenges

Speaker: Alessandro Checco

Host: Boris Bellalta

Over the last decades, we have witnessed an explosion in the use of hybrid systems combining humans and machine learning, and in the outsourcing of jobs to a crowd of workers performing micro-tasks. This trend introduces novel problems, due to the nature of human processing: from technical problems like quality assessment, spam avoidance and consensus building to more social ones like engagement, motivation and fairness for the worker. We present an overview on the challenges in these fields and a brief discussion of the state of the art.

https://www.scss.tcd.ie/Doug.Leith/checcoa/

Mathematical engineer, particularly interested in graph theory, Markov chains, stochastic processes and randomised optmisation algorithms. Currently working on privacy issues in recommender systems. Also interested in high performance parallel computing and big data analysis.

PhD Training Seminar

16th February

12:30 hours  

Room 52.427

Short Introduction to Research Methods

Speaker: Julián Urbano

Host:  Aurelio Ruiz

This three-day seminar will cover the basic concepts, methods and tools to critically assess someone else’s published research and carry out one’s own research. The seminar will go about the validity of a body of research (how well it allows us to answer the question under study) and its reliability (how much confidence we can have in its conclusions). In particular, we will cover material on concepts like variables, measurement, sampling, fallacies, biases, and a brief overview of experimental design and statistical analysis.

In January of 2007, I received a degree in Bilingual Computer Engineering from the University Carlos III of Madrid. My thesis, Modeling and Indexing Musical Files to Allow Music Reuse, was graded as excellent cum laude. Meanwhile, I collaborated with the Department of Computer Science and obtained a small scholarship with the Department of Telematics. I also obtained an Erasmus scholarship to study at the Åland Polytechnic (Finland), from January to July of 2006.

Since January of 2007, I was a PhD student in Computer Science at Virginia Tech (USA). As part of my Graduate Research Assistantship, I worked for the Research Methods Consortium in the National Capital Region. In June of 2008 I went back to the University Carlos III of Madrid with a small scholarship, and received a Masters Degree in Computer Science and Technology. Since January of 2009 I was a Graduate Teaching Assistant in the Department of Computer Science, while working on my PhD dissertation.

In October of 2013 I finished my PhD with a dissertation titled Evaluation in Audio Music Similarity, which was graded as excellent cum laude. Right after, I spent two years as a postdoctoral researcher in the Universitat Pompeu Fabra, Barcelona, with an A4U Postdoctoral Research Fellowship. In October of 2015 I received a Juan de la Cierva postdoctoral fellowship from the Spanish Government to continue my research.

PhD Research Seminar

10th February

12:00 hours  

Room 55.309

More than words: Machine learning applied to Marketing

Speaker: Cristina Aranda Gutiérrez.

Host:  Aurelio Ruiz

PhD Cristina Aranda will talk about the relevance of semantics and pragmatics in technology (Internet of things, Machine Learning, speech technologies, etc.). Through several examples of the processing of linguistic data with impact in both business and social innovation, she will show the relevant role that language processing has in the digital economy.

Cristina Aranda Gutiérrez, Chief Marketing Officer en Intelygenz and Co-founder and Director of MujeresTech

Cristina Aranda is Chief Marketing Officer in Intelygenz, a software development company using agile and scrum technologies, with offices in Madrid, San Francisco (California) and Austin (Texas). Cristina has over 16 years of professional experience in marketing, the startups ecosystem and digital transformation. She has collaborated with several IBEX35 and Top500 companies. 

She also co-founded Mujeres Tech, a non-profit association which has the target to promote actions that increase the number of female working in the digital economy and, at the same time, establish links with the men willing to generate equal opportunities for women. Aranda is Social Innovation Fellow  from the Meridian International Center and the USA Embassy in Madrid.

Cristina holds a PhD in Linguistics (UAM and Instituto Universitario de Investigación Ortega y Gasset), BSc in Hispanic Filology (UAM) and MSc in Internet Business (ISDI).

Twitter https://twitter.com/cris_aranda_

LinkedIn https://www.linkedin.com/in/cristinaaranda/

 

Short Introduction to Research Methods

Speaker: Julián Urbano

Host:  Aurelio Ruiz

This two-day seminar will cover the basic concepts, methods and tools to critically assess someone else’s published research and carry out one’s own research. The seminar will go about the validity of a body of research (how well it allows us to answer the question under study) and its reliability (how much confidence we can have in its conclusions). In particular, we will cover material on concepts like variables, measurement, sampling, fallacies, biases, and a brief overview of experimental design and statistical analysis.

In January of 2007, I received a degree in Bilingual Computer Engineering from the University Carlos III of Madrid. My thesis, Modeling and Indexing Musical Files to Allow Music Reuse, was graded as excellent cum laude. Meanwhile, I collaborated with the Department of Computer Science and obtained a small scholarship with the Department of Telematics. I also obtained an Erasmus scholarship to study at the Åland Polytechnic (Finland), from January to July of 2006.

Since January of 2007, I was a PhD student in Computer Science at Virginia Tech (USA). As part of my Graduate Research Assistantship, I worked for the Research Methods Consortium in the National Capital Region. In June of 2008 I went back to the University Carlos III of Madrid with a small scholarship, and received a Masters Degree in Computer Science and Technology. Since January of 2009 I was a Graduate Teaching Assistant in the Department of Computer Science, while working on my PhD dissertation.

In October of 2013 I finished my PhD with a dissertation titled Evaluation in Audio Music Similarity, which was graded as excellent cum laude. Right after, I spent two years as a postdoctoral researcher in the Universitat Pompeu Fabra, Barcelona, with an A4U Postdoctoral Research Fellowship. In October of 2015 I received a Juan de la Cierva postdoctoral fellowship from the Spanish Government to continue my research.

9th February

12:30h -13:30h   

Room 52.427

9th February

15:30 hours  

Room 55.309

The Revenge of the Indians on European Music and Other Art Genres

Later on Concert in Sala Polivalente at 19:30

http://phonos.upf.edu

Speaker: Arthur Clay

Host:  Andres Lewin

The lecture references a comment made by the German playright Heimer Mueller about the music of John Cage. The topic of "randomness" is the starting point in creating the stage for the birth of sound art and how it has reshaped music composition and performance by shifting focus from harmonically organized structures to those that make use of other forms of structuring and expand the pallette of sounds, the approach to making them, and redefine the stage. Light is shed on each of the works presented in the program. How the works came about, how they are constructued, how they are perforned, what notations were used to preserved in the form of a score, and how they figure into the histories of sound are an integral part of the lecture. However, although the lecture acknoeldeges the undeniable relevance of the theories of Duchamp as put into practice by Cage, it also poses the questions as it is possible to acknoweldge such influence, explore it and follow in a direction which was hinted at rather than taken.

I am an arts professional who is celebrated both as an media artist and and as a curator for innovation in arts. As an artists. I have specialized in the use of intermedia creating works using new technologies in wide range of genres.  My works have appeared in galleries, theaters, museums, festivals, as well as on radio and television in Europe, North America, and Asia. Most recent work focuses on media based works using mobile devices in virtuale space. As a curator, I have focused two areas: Creativiely connecting art and science by producing and plaforming research based artworks with the founding and directing of the Digital Art Weeks Festival,  and exploring the potentials of virtual art, exploring its presentation form in public space through the founding and  directing of the Virtuale Switzerland. 

26th January

15:30 hours 

Room 55.410

Ethical issues and data protection, session 1. CIREP-UPF,

Speaker: Silvia Losa & Josep Blat

Host:  Aurelio Ruiz

CIREP-UPF (Internal Committee for the Ethical Review of Projects) aims at improving ethical standards and personal data protection in research and academic practices related to human beings, within the UPF community. The first review of a research project by CIREP took place about a year ago.


During this session the basic concepts on both issues, ethics and personal data protection, will be introduced through practical examples. Moreover, it will be discussed how to submit project(s) (proposals) to CIREP for ethics evaluation and approval. The session can be considered as a preparation to submit a proposal on the PhD research and/or acting as a reviewer of such a proposal.

 

26th January

12:30 hours 

Auditorium

Ontogenesis of rational thinking

Speaker: Luca Bonatti

Infants possess several mechanisms to solve domain-specific problems. However, little is know about infants' abilities to reason beyond these limited domains. I will present evidence that suggests that infants have a early sense of rationality. Furthermore, when they witness a scene not previously experienced, infants reason about it by applying basic logical principles. I will argue that such inferences are used to build strategies to inspect the scenes and make inferences to enrich knowledge. I will present data about the behavioral correlates of this inferential processes in infants and adults, focusing on the case of disjunctive reasoning. Finally, I will argue that any well-designed system for human-machine interaction has to embody a model of the cognitive state of a human, in her adult and infant state.

Luca Bonatti is an ICREA Research Professor at the Center for Brain and Cognition of our Department.

He received his Ph.D. in Philosophy of Mind at Rutgers University, under the supervision of Jerry Fodor. He has been full professor at the University of Nantes, associate professor at the University of Paris 8, and at SISSA/ISAS, Trieste, and visiting professor at the Universities of Budapest, Illes Balears and New York. He is interested in reasoning, language learning, imagination of physical events and infant cognition.

He has promoted a dual model of language acquisition, giving evidence that lexical learning and grammatical learning recruit different acquisition mechanisms. In infant cognition, his work focuses on early abilities of reasoning about the future, and on how basic categories affect infants' organization of experience. Recently, with his collaborators, he has proposed a novel theory of how infants reason about uncertain events and on how their reasoning is affected by what they experience. He has tried to show that infants have intuitions about the future that are not based on their experience of the past, but on their logical abilities of analyzing current events. 

19th January

15:30 hours 

Room 55.410

 

Today's ETIC Streaming 

Why Reproducibility Matters? A Personal Experience

Speaker: Sertan Sertürk

Host:  Aurelio Ruiz

  • How many times have you got frustrated, because your code from last month refuses to run and your past self didn’t bother to leave you any guidelines?

  • Are you scared that one day a colleague will ask you the data/results of a paper, and you will have to excavate them out of a folder named ‘allDataResultsVersion8bFinalizedRecheckedPleaseEnd’?

  • Are you concerned that your contributions will not have much impact, because people may not be able to access them properly?

If yes, you are in the same shoes with me, when I started my PhD! In this talk, I will present how I embraced reproducibility to avoid some of these common mistakes. I will explain some best practices, simple tricks and habits I have learned throughout my doctoral research, which improved the quality of my research, made it reusable by others (and myself), and hence improved the accessibility and visibility of my work. I will give practical examples in where I failed (and then gradually improved) on organizing, developing, versioning, documenting, licensing and publishing the research material (data, code, experimental setups and results etc.). I will also introduce some of the available software tools and services, which would help you to achieve these goals. I hope that this talk will convince you to consider reproducibility as a major criteria in academic research, and give you a head start on achieving this objective.

Sertan Sentürk is a PhD candidate in the Music Technology Group working in the CompMusic project (http://compmusic.upf.edu/) under the supervision of Prof. Xavier Serra. He has recently submitted my thesis titled "Computational Analysis of Audio Recordings and Music Scores for the Description and Discovery of Ottoman-Turkish Makam Music," where he addresses several shortcomings on the current state of the art methodologies in music information retrieval (MIR) and propose several computational approaches to automatically analyze and describe large corpora belonging to this music tradition. Throughout his PhD, he ha dedicated a fair amount of effort for the openness and reproducibility of his doctoral research.
 
He wants to pursue an academic career in music technology, and specialise in music information retrieval, audio signal processing, machine learning and music perception & cognition with an
emphasis on different music traditions in the world. As a part of his endeavours, he wants to develop computational methodologies to understand and discover the modes of musical creativity, expressivity and interaction."

17th January

17:00h-21:00h

Room 52.023Free event but if you want to join, please register here

Let's fill the Wikipedia gender gap

Speaker: David Laniado

Host:  Aurelio Ruiz

Wikipedia was created on January 15th 2001. We join this anniversary with the aim to overcome one of its bitter-sweet outcomes: the existing gender gap in editors, in articles, in type of descriptions. As a collaboration of  Civic Lab Barcelona , ViquidonesUPF and  DTIC-UPF, we invite you to this event.

 

 

17:00h - 18:00h - Talk: Gender Gap in Collaborative Platforms: Language and emotions in Wikipedia Discussions. (Talk in Spanish, details above). David Laniado (Digital Humanities, Eurecat).

18:00h - 18:30h - Announcement of finalist schools of the Wisibilizalas contest
18:30h - 21:00h - Viquimarató with ViquidonesUPF. Learn how to edit and make your individual contribution to overcome the gender gap! You need to bring your laptop! All details in this link

16th January

16:30 hours

Room 52.s29

Latest research in thoracic image analysis and biomarker quantification 

Speaker: Adrià Pérez-Rovira (Erasmus Medical Center, Rotterdam)

Host:  Miguel Ángel González Ballester

Adria will talk about his latest research in thoracic image analysis and biomarker quantification that is allowing clinicians, and radiologists in particular, to gain a better understanding of disease-induced structural and dynamic changes in the lung. More information: http://perezrovira.net/adria/research

Adria Perez-Rovira got his BSc in Computer Science at the UPF and an MSc on image analysis at the UAB, both in Barcelona. In 2011 he obtained a PhD in retinal image analysis at the University of Dundee (Scotland), where he had focused on non-rigid registration and quantification of retinal vasculature biomarkers. After a brief period working on automated detection and visualisation of stenosis in angiographic full body MRI at Ninewells Hospital (Dundee, Scotland) he moved to Rotterdam (the Netherlands) as a post-doc researcher at the Erasmus MC. In there he developed automated image analysis techniques to quantify and discover image biomarkers related to bronchiectasis and other lung-related diseases in MRI and CT like Pompe or cystic fibrosis.

12th January

15:30 hours 

Room 55.410

 

How to develop an academic career related to ICT. 

Topics to cover: Information and Communications Technologies as an academic field; Needed competences for an academic career; Steps in an academic career; From Master to PhD; From PhD to Postdoc.

Speaker: Xavier Serra

Host:  Aurelio Ruiz

 

 

 

A PhD is a general requirement to make a career in academia, and PhD programs are often designed for that purpose. But the number of new PhD holders each year is significantly higher than the number of available positions in academia. During this talk we will discuss some relevant issues to consider to pursue (or discard) careers in this environment.

Suggested readings:
- The disposable academics - The Economist http://www.economist.com/node/17723223 
- An academic career: Research careers in academia (Univ. Manchester)
http://www.academiccareer.manchester.ac.uk/about/phdandbeyond/phdtopermanent/
- Careers section in Nature (oriented to bio, but with several articles relevant for any area of research)
http://www.nature.com/nature/careers/

Xavier Serra is Associate Professor of the Department of Information and Communication Technologies and Director of the Music Technology Group at the Universitat Pompeu Fabra in Barcelona. After a multidisciplinary academic education he obtained a PhD in Computer Music from Stanford University in 1989 with a dissertation on the spectral processing of musical sounds that is considered a key reference in the field. His research interests cover the computational analysis, description and synthesis of sound and music signals, with a balance between basic and applied research and approaches from both scientific/technological and humanistic/artistic disciplines. Dr. Serra is very active in fields of Audio Signal Processing, Sound and Music Computing, Music Information Retrieval and Computation Musicology at the local and international levels, being involved in the editorial board of a number of journals and conferences and giving lectures on current and future challenges of these fields. He was awarded an Advanced Grant of the European Research Council to carry out the project CompMusic aimed at promoting multicultural approaches in music information research.

21st  December

10- 10:30 hours

55.410

Transferring our knowledge to the society

Speaker: Jordi Arias and Manuel Palacin.

Host:  Aurelio Ruiz

In this talk we will present a new transference programme that accompanies entrepreneurs from the best national universities and research centres in the tedious task of approaching technologies from lab to the market. The programme challenge is to help researchers and technologists to bridge the gap between discovery and commercialisation of their technologies to build marketable products and create high growth science based businesses. To complement the research activities of the investigators, the programme provides a scientific core team led by entrepreneurs in residence that will be in charge of mobilising internal resources as well as external collaborators whenever needed, freeing scientists from the business side and letting them focus on what they do best, research.

Mobile World Capital Barcelona (mVenturesBcn)

 

15th December

16:00 hours

Auditorium Poblenou Campus.

Data -Driven Design of Study Plans

Speaker: Rakesh Agrawal

Host:  Ricardo Baeza

A study plan is the choice of concepts and the organization and sequencing of the concepts to be covered in an educational course. While a good study plan is essential for the success of any course offering, the design of study plans currently remains largely a manual task. We present a novel data-driven method, which given a list of concepts can automatically propose candidate plans to cover all the concepts. Our method uses Wikipedia as an external source of knowledge to both identify which concepts should be studied together and how students should move from one group of concepts to another. For our experimental validation, we synthesize study plan for a course defined by a list of concept names from high school physics. Our user study with domain experts finds that our method is able to produce a study plan of high quality.

Rakesh Agrawal is the President and Founder of the Data Insights Laboratories. He is a member of National Academy of Engineering, a Fellow of ACM, and a Fellow of IEEE. He has been both an IBM Fellow and a Microsoft Fellow. ACM SIGKDD awarded him its inaugural Innovations Award and ACM SIGMOD the Edgar F. Codd Award. He was named to the Scientific American’s First list of top 50 Scientists. Rakesh has been granted 85+ patents and published 200+ papers, including the 1st and 2nd highest cited in databases and data mining. Four of his papers have received “test-of-time” awards. His papers have received more than 100,000 citations and his H-Index is 96. His research formed the nucleus of IBM Intelligent Miner that led the creation of data mining as a new software category. Besides Intelligent Miner, several other commercial products incorporate his work, including IBM DB2 and WebSphere and Microsoft Bing.

15th December

15:30 hours  

New Room 

Auditorium Poblenou Campus.

Research careers in industry

Speaker: Ricardo Baeza

Host:  Aurelio Ruiz

 

 

12th December

15:30 hours  

Room 55.410

 

Multi-objective Local Search algorithms – From theory to real life applications

Speaker: Vitor Nazário Coelho

Host:  Emilia Gómez

 

In this talk, Vitor will introduce some trajectory search algorithms. In order to understand the concept, neighborhood structures and exploration techniques will be explained and discussed. A brief history about metaheuristics algorithms, embedded with local search capabilities, will also be taken into account. Finally, some combinatorial optimization problems will be considered. In particular, he will point out open challenges in the field of Mini/Microgrid systems for Renewable Energy Resources integration, which will be part of the hearth of the future smart cities.

Vitor Nazário Coelho finished his PhD in the area of mini/microgrid systems optimization. 

During his 8 years experience designing and implementing metaheuristics, he has been tackling several different NP-Hard Combinatorial Optimization problems. He already visited more than 40 countries and did part of his studies in 4 different countries (Brazil, Spain, England and Israel). Motivated by the nature and inspired by the evolution of the species, his research group in Brazil are releasing open-source codes, designing novel tools for using metaheuristic algorithms, as well as developing the optimization framework OptFrame.

 

1st December

15:30 hours  

Room 55.410

 

On Crowdlearning: How do People Learn in the Wild?

Speaker: Manuel Gomez Rodriguez

Host:  Vicenç Gómez

 

Learning from the crowd has become increasingly popular in the Web and social media. There is a variety of crowdlearning sites, ranging from wikis and question answering (Q&A) sites to online  communities and blogs, in which users learn from knowledge that other users contribute to the site and knowledge is reviewed and curated by the same users using assessment measures such as upvotes, likes or shares. In this talk, I will present a family of machine learning models and inference methods that leverage the digital traces left by the users of these sites to, on the one hand, shed light on how they learn over time and become experts, and, on the other hand, identify trustworthy knowledge contributions of high value, which systematically help users to increase their expertise.

Manuel Gomez Rodriguez is a tenure-track faculty at Max Planck Institute for Software Systems. Manuel develops machine learning and large-scale data mining methods for the analysis, modeling and control of large real-world networks and processes that take place over them. He is particularly interested in problems arising in the Web and social media and has received several recognitions for his research, including an Outstanding Paper Award at NIPS'13 and a Best Research Paper Honorable Mention at KDD'10. Manuel holds a PhD in Electrical Engineering from Stanford University and a BS in Electrical Engineering from Carlos III University in Madrid (Spain). You can find more about him at http://www.mpi-sws.org/~manuelgr/.

25th November

10:00 hours  

Room 55.309

 

Imaging biomarkers: algorithms, open data and infrastructure for neurological disorders"

Speaker: Christian Barillot 

Host:  Aurelio Ruiz

One of the major challenges in clinical neuroimaging is to detect quantitative signs of pathological evolution as early as possible in order to prevent disease progression, evaluate therapeutic protocols or even better understand and model the normal history of a given neurological pathology. A particular challenge is to find correlations between brain structures at the morphometric, structural, metabolic or functional level through a large set of multimodal images. MRI is the premier means to study the human brain through various acquisition protocols. This presentation will illustrate this challenge through the use of novel cellular or structural MRI protocols able to provide relevant information at the cellular or micro-structural level. Technological perspectives will be also provided about general issues of Medical Imaging as a Service in the context of the emerging open data services and digital infrastructures. After introducing the general context, some examples will be provided of how these new services can be implemented, and applied to neurological diseases, and especially Multiple Sclerosis.

 

24th November

15:30 hours  

Room 55.410

Scientific Dissemination, Online Repositories, and Author's Rights.

Speaker: Ana Baiges

The purpose of the meeting is to explain the services that the Library offers to UPF researchers and graduate students in the preparation of scientific publications, and the aspects to take into account in their dissemination. A particular emphasis will be placed on intellectual property issues on the compliance with European and Spanish policies on open access (Horizon 2020, Plan Estatal ICTI) and an overview on author profiles and affiliation.

 

21st November

15:30 hours  

Room 55.410

Graph-Based Feature Extraction: Trying to understand musical patterns in audio signals outside the time-frequency domain.

Speaker: Dirceu Melo

Host: Emilia Gómez

The feature extraction is a very important step in music audio classification. This task has been performed by renowned descriptors using, in most cases, the time-frequency approach. In this talk we will present a descriptor that extract features of an audio signal by the topological analysis of his respective visibility network. Through the measure of the network’s modularity we will show that the quality and quantity of partitions of each audio-associated network, are directly associated with quality and quantity of the audio local peaks, and more: this feature can provide meaningful information to classify labeled sets and identify different levels of dynamics density among different music genres.

Dirceu Melo is a professor at the Department of Mathematics at the Federal Institute of Education, Science and Technology of Bahia, Brazil. In his master thesis at SENAI CIMATEC - Brazil, he studied patterns in audio signals using Detrended Fluctuation Analysis. He is a PhD student of the Knowledge Dissemination Doctoral Program at the Federal University of Bahia. In the research line Construction of Knowledge: Cognition, Languages and Information, he develops a work involving Music Information Retrieval and Graph Theory.

17th November

15:30 hours  

Room 55.410

Process and effectiveness:biomarkers in music therapy research

Speaker: Prof. Jorg Fachner

Host: Rafael Ramírez

How can we document change as a function of doing music in a therapeutic setting and how does it work? Biomarkers representing the effectiveness and those representing the music therapy process are related to an accumulation of and a focus on important moments in therapy time. Analysing resting state EEG may inform about group effects, while moments of interest in the improvisational process may reveal synchronization of brain processes. In music therapy it may be an important key to understand where and why change in therapy occurs. The presentation will discuss the promises of biomarkers and neurometrics for music therapy, it will draw on results of depression research, on recent work with wireless EEGs and improvisation, music performance, neurofeedback and game applications in psychiatric and neurorehabilitation.

Dr. Fachner, since 2013 Professor for Music, Health and the Brain at Anglia Ruskin University in Cambridge, UK, is interested in translational issues of interdisciplinary research topics between medicine, humanities and music sciences. Starting in Germany 20 years ago, he has been working as a professional in the field of Music Therapy (MT) and brain research, was and is active in EU and Academy of Finland MT research projects and serves on international MT advisory and policy boards. Studying Music Therapy processes, brain responses and treatment of depression, as well as consciousness states and time perception, his scientific output comprises over 100 publications in journals and books across disciplines. Recent projects, collaborations and publications focus on biomarkers, neurodynamics, timing and kairological principles of the MT process and effectiveness

15th November

17:00 hours  

Room 52.321

Rhythm Transcription of Piano Performances Based on Hierarchical. Bayesian Modelling of Repetition and Modification of Musical Note
Patterns

Speaker: Dr. Eita Nakamura 

Host: Rafael Ramírez

We present a method of rhythm transcription (i.e., automatic recognition of note values in music performance signals) based on a Bayesian music language model that describes the repetitive structure of musical notes. Conventionally, music language models for music transcription are trained with a dataset of musical pieces. Because typical musical pieces have repetitions consisting of a limited number of note patterns, better models fitting individual pieces could be obtained by inducing compact grammars. The main challenges are inducing appropriate grammar for a score that is observed indirectly through a performance and capturing incomplete repetitions, which can be represented as repetitions with modifications. We propose a hierarchical Bayesian model in which the generation of a language

model is described with a Dirichlet process and the production of musical notes is described with a hierarchical hidden Markov model (HMM) that incorporates the process of modifying note patterns. We derive an efficient algorithm based on Gibbs sampling for simultaneously inferring from a performance signal the score and the individual language model behind it. Evaluations showed that the proposed model outperformed previously studied HMM-based models.
 

 

Kyoto University, Japan.

10th November

15:30 hours  

Room 55.410

Gender and Science

Speaker: Gender and Science Club: Pallabi Sengupta

Host:  Aurelio Ruiz

Women in Science, Technology, Engineering and Mathematics (STEM) fields remain severely underrepresented. In Spain, women represent about 15% of full (catedras) professorships and, unfortunately, UPF isn't an exception to this general trend. Moreover, women are judged to be less competent, receive less payment and research facilities, and are less likely to be awarded research grants compared with male scientists. The different mechanisms leading to this disparity have been investigated and more is brought to light by ongoing research. In this talk we will explain the different challenges faced by women in STEM careers, the reasons and the mechanisms through which they emerge, and changes (big and small) that we can all do to improve the current dire scenario.

 

9th November

15:30 hours  

Room 55.410

 

Texture synthesis using local Gaussian patch models

Speaker: Lara Raad

Host:  Coloma Ballester

 

Lara Raad received the Ph.D. degree from Ecole Normale Supérieur de Cachan, Université Paris Saclay, in October 2016. Before that she received the graduate degree from Universidad de la Républica, Uruguay, in electrical engineering in 2012, the graduate degree from Telecom Bretagne in engineering in 2011, and he MSc degree in applied mathematics in Ecole normale supérieure de Cachan, France in 2012. She is actually a post-doctoral researcher in Jean-Michel Morel’s group at Ecole Normale Supérieur de Cachan, Université Paris Saclay. Her research interest include image and signal processing, computer vision and computational imaging.

3rd November

15:30 hours  

Room 55.410

Reproducibility in research

Speaker: Aurelio Ruiz

An objective of the María de Maeztu Strategic Research Program is “to increase the impact of our research by increasing the impact of the publications, datasets and software tools, and take advantage of this impact to establish and consolidate partnerships”. It includes actions to promote that the research results, datasets and tools are discoverable, interpretable and reusable, including the publication of the data and software together with the publications. During this session, we will discuss some of the topics linked to "reproducible research", including the increasing requirements in making datasets and computer code available by funding agencies, publishers and potential mechanisms to promote it in our organisation being elaborated in the context of the Maria de Maeztu program.

Suggested reading:

-Reproducible Research in Signal Processing - What, why, and how. Vandewalle, Patrick; Kovacevic, Jelena; Vetterli, Martin. IEEE Signal Processing Magazine (ISSN: 1053-5888), vol. 26, num. 3, p. 37-47. Institute of Electrical and Electronics Engineers, 2009

-Ongoing draft document within MdM for good practices for discussion in this link

-For a survey on NIPS participants and motivations (2008): "The Scientific Method in Practice: Reproducibility in the Computational Sciences", Stodden, Victoria. MIT Sloan Research Paper No. 4773-10.

Aurelio Ruiz has a Telecommunications Engineering Degree (Universidad Carlos III de Madrid) and a Master in Science Management and Leadership (IDEC, UPF). After research and educational traineeships at Technical University Munich, EPFL and CERN, he was responsible for project management in the banking and aeronautical sectors with projects in Europe, Asia and Africa. Since 2006 he is with UPF, currently working in the management of the Maria de Maeztu strategic research program.

25th  October

15:30 hours  

Room 55.410

Dynamics of Phase Oscillators with Generalized Coupling

Speaker: Christian Bick

Host:  Ralph Andrzejak

The emergence of collective behavior is a fascinating feature of interacting oscillatory units in nature and technology. We study systems of phase oscillators which provide an approximation for weakly coupled oscillators. In contrast to the classical Kuramoto equations, where the interaction is determined by the sine of the phase differences, we are interested in symmetrically coupled networks where the interaction can have more than one nontrivial Fourier component. On the one hand, we are interested in the effect generalized coupling has on the dynamics and bifurcations occurring in the system. On the other hand, we investigate how generalized coupling can be exploited in applications, for example to design and potentially control desired localized dynamics.

College of Engineering, Mathematics and Physical Sciences -University of Exeter

Biosketch: I did my PhD work at the Max Planck Institute for Dynamics and Self-Organization, in Göttingen, Germany in applied dynamical systems obtaining a PhD from the University of Göttingen in Mathematics in 2012. I moved to Rice University, Houston, TX for a postdoctoral position with Mike Field working on asynchronous dynamics of networks. I currently hold a Marie Curie Research Fellowship at the University of Exeter to study oscillator networks with generalized coupling. I will be moving to the Mathematical Institute of the University of Oxford in fall.

24th  October

15:30 hours  

Room 52309

Speaker: Angela Dobele

  Deputy Head (Research & Innovation) The School of Economics, Finance & Marketing, RMIT University, Australia

20th  October

15:30 hours  

Room 52.323

Introduction to PhD training seminars series 2016/2017 for 1st year PhD students. 

Speaker: Aurelio Ruiz

   

13th  October

15:30 hours  

Room 55.309

Welcome Session for  PhD Students 

Speakers :Emilia Gomez, Miquel Oliver, Miguel Angel González Ballester, Vanesa Dazam Davinia Hernández-Leo & Aurelio Ruiz

Important information about academic and organizational aspects of the doctoral program and the department. Meet your colleagues

 

19th  October

12:30 hours  

Room 55.410

semantic Representations of Word Senses, Concepts and Entities and their Applications

Speaker: Jose Camacho Collados

 

(Google Doctoral Fellow and PhD student at Sapienza University of Rome)

28th September

12:00 hours  

Room 52.221

Data and Algorithmic Bias in the Web

Speaker: Ricardo Baeza 

Host:  Aurelio Ruiz

 

 The Web is the largest public big data repository that humankind has created. In this overwhelming data ocean, we need to be aware of the quality and, in particular, of the biases that exist in this data. In the Web, biases also come from redundancy and spam, as well as from algorithms that we design to improve the user experience. This problem is further exacerbated by biases that are added by these algorithms, specially in the context of search and recommendation systems. They include selection and presentation bias in many forms, interaction bias, social bias, etc. We give several examples and their relation to sparsity and privacy, stressing the importance of the user context to avoid these biases.

 Ricardo Baeza-Yates areas of expertise are web search and data mining, information retrieval, data science and algorithms. He is CTO of NTENT, a semantic search technology company. Before he was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from January 2006 to February 2016. He also is part time Professor at DTIC of the Universitat Pompeu Fabra, in Barcelona, Spain, as well as at DCC of Universidad de Chile in Santiago. Until 2004 he was Professor and founding director of the Center for Web Research at the later place. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 2011 (2nd ed), that won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the board of governors of the IEEE Computer Society and in 2012 he was elected for the ACM Council. Since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions. 

2015-2016

Sep

Speaker

Host/Group

Remarks

Title

29 
(Tue)

Anders Jonsson, 
DTIC, UPF

AIG

12:30 pm 
Room 55.410

Lifelong Sequential Decision Making

 

Oct

Speaker

Host/Group

Remarks

Title

1

 

---

 

 

---

 

 

---

 

 

---

 

2 
(Fri)

Constantine Butakoff, 
DTIC, UPF

PhySense

12:30 pm 
Room 55.309

Computational techniques for cardiac structure representation and analysis

8

 

---

 

 

---

 

 

---

 

 

---

 

14 
(Wed)

Yasuko Sugito, 
NHK, Japan

Marcelo Bertalmio (IP4EC)

12:30 pm 
Room 52.s25

HEVC/H.265 Codec System and Transmission Experiments aimed at 8K Broadcasting

Julian O’Kelly,
Royal Hospital for Neuro-disability, UK

Rafael Ramirez (MTG)

3:30 pm 
Room 55.410

Music Therapy with Prolonged Disorders of Consciousness: in Retrospect and Prospect

15

 

---

 

 

---

 

3:30 pm 
Room 52.S31

 

---

 

19 
(Mon)

Ye Wang, 
National University of Singapore

Rafael Ramirez (MTG)

3:30 pm 
Room 55.410

Sound, Music and Sensor Computing for Health and Wellbeing.

22

Ralph Andrzejak, 
UPF-DTIC

NTSA

1:00 pm 
Auditorium

[Integrative Research Seminar]

Luz Rello, 
Carnegie Mellon University

Ricardo Baeza-Yates (WRG)

3:30 pm 
Room 52.S31

Change Dyslexia: Early Detection and Intervention at Large Scale

29

Ana Baiges, 
UPF Library Services

Aurelio Ruiz

3:30 pm 
Room 52.S31

Scientific Dissemination, Online Repositories, and Author's Rights

 

Nov

Speaker

Host/Group

Remarks

Title

2
(Mon)

Jeffrey C. Smith , 
CEO and Co-Founder,Smule

Xavier Serra (MTG)

1:15 pm 
Room 52.S27

User Engagement with Data Science

5

Ichiro Fujinaga, 
McGill University

Xavier Serra (MTG)

3:30 pm 
Room 52.S31

Single Interface for Music Score Searching and Analysis Project

12

Seiji Isotani, 
University of Sao Paulo

Davinia Hernandez-Leo (GTI)

3:30 pm 
Room 52.S31

Advancements in Intelligent Support for Collaborative Learning

13 
(Fri)

José Vicente Manjón Herera,
UPV

Miguel Angel Gonzalez Ballester (SIMBIOSYS)

11:30 am 
Room 52.S27

Applications of non-local medical image processing

19

Leo Wanner, 
UPF-DTIC

TALN

1:00 pm 
Auditorium

[Integrative Research Seminar]

Olivier Coulon, 
Aix-Marseille University

Miguel Angel Gonzalez Ballester (SIMBIOSYS)

4:30 pm 
Room 52.329

Organization and variability of the cerebral cortex: quantification and modeling

26

Daniel Wolff
UPF-DTIC

Emilia Gomez (MTG)

3:30 pm 
Room 52.S31

Spot The Odd Song Out: Similarity models in analysis of corpora and listener groups

 

Dec

Speaker

Host/Group

Remarks

Title

3

Jesus Alonso-Zarate, 
CTTC

Boris Bellalta (WN)

3:30 pm 
Room 52.S29

The Internet of Things: A Brave New World

10

Marcelo Bertalmío, 
UPF-DTIC

IP4EC

12:30 pm 
Auditorium

[Integrative Research Seminar]

17

 

---

 

 

---

 

 

---

 

 

---

 

24

 

---

 

 

---

 

 

---

 

 

---

 

31

 

---

 

 

---

 

 

---

 

 

---

 

 

Jan

Speaker

Host/Group

Remarks

Title

7

 

---

 

 

---

 

3:30 pm 
Room 55.410

 

---

 

14

Gustavo Deco, 
UPF-DTIC

CNS

12:30 pm 
Auditorium

[Integrative Research Seminar]

Antonios Lioutas
CRG, BIOcomuniCA'T

Aurelio Ruiz

3:30 pm 
Room 55.410

Session 1/2 : How to prepare a good scientific poster. [Slides]

19 
(Tue)

Gwanggil Jeon, 
Incheon National University, Korea

Marcelo Bertalmío (IP4EC)

3:30 pm 
Room 55.410

Color Demosaicking in Frequency Domain

21

Ricardo Marques, 
UPF-DTIC

GTI

3:30 pm 
Room 55.410

Spherical Integration for Global Illumination: From Quasi to Bayesian Monte Carlo

28

Francisco Herrera
University of Granada

Xavier Binefa

12:30 pm 
Room 52.S31

Big data preprocessing

Simón Lee, 
Incubio

Aurelio Ruiz García

3:30 pm 
Room 55.410

Incubio: The Big Data Academy

 

Feb

Speaker

Host/Group

Remarks

Title

3 
(Wed)

Nicolas Schweighofer, 
University of Southern California

Paul Verschure (SPECS)

4:00 pm 
Room 55.410

Computational neurorehabilitation: modeling interactions between arm use and function post-stroke

4

Antonios Lioutas
CRG, BIOcomuniCA'T

Aurelio Ruiz

12:00 noon 
Room 52.S31

Session 2/2: Preparing your scientific poster.[Slides]

Diemo Schwarz, 
IRCAM, Paris

Xavier Serra (MTG)

3:30 pm 
Room 52.123

Tangible and Embodied Interaction on Surfaces, with Mobile Phones, and with Tapioca

Bob Sturm
Queen Mary University of London

Xavier Serra (MTG)

4:30 pm 
Room 52.123

The scientific evaluation of music content analysis systems: Toward valid empirical foundations for future real-world impact

11

Diarmuid P. O'Donoghue, 
Maynooth University, Ireland

Horacio Saggion (TALN)

3:30 pm 
Room 55.410

Computational Modelling of Analogy and Blending for scientific creativity [Slides]

18

Antoni Ivorra, 
UPF-DTIC

BERG

12:30 pm
Auditorium

[Integrative Research Seminar]

25

Aurelio Ruiz, 
UPF-DTIC

Internal Speaker

3:30 pm 
Room 52.S31

Communication Skills in Science: Preparing for Research in 4 minutes [Slides]

 

Mar

Speaker

Host/Group

Remarks

Title

3

Alexandros Karatzoglou, 
Telefonica Research

Gergely Neu (AI)

3:30 pm 
Room 55.410

Deep Learning [Slides]

10

Carla Rafols Salvador, 
UPF-DTIC

WiCom

3:30 pm 
Room 55.410

Cryptography for Non-Cryptographers

17

Emilia Gómez

MTG

1:00 pm 
Auditorium

[Integrative Research Seminar]

24

 

---

 

 

---

 

 

---

 

 

---

 

31

 

---

 

 

---

 

 

---

 

 

---

 

 

Apr

Speaker

Host/Group

Remarks

Title

7

Miguel Ángel González Ballester

SIMBIOSYS

12:30 pm 
Auditorium

[Integrative Research Seminar]

11 
(Mon)

Kadi Bouatouch andChristian Bouville, 
INRIA/IRISA Rennes, France

Josep Blat (GTI)

11:00 am 
Room 55.410

Toward More and More Realism in Computer Graphics

14

Simone Tassani
UPF-DTIC

SIMBIOSYS

3-5 pm (2 hours) 
Room 52.S29

Session 1 of 3: Statistical Analysis and Design of Experiments [Slides: 0, 1]

19 
(Tue)

Alfonso Martinez, 
UPF-DTIC

ITC

12:30 pm 
Room 55.410

Some Results on Mismatched Decoding in Information Theory

21

Simone Tassani
UPF-DTIC

SIMBIOSYS

3-5 pm (2 hours) 
Room 55.410

Session 2 of 3: Statistical Analysis and Design of Experiments [Slides: 2, 3]

28

Simone Tassani
UPF-DTIC

SIMBIOSYS

3-5 pm (2 hours) 
Room 55.410

Session 3 of 3: Statistical Analysis and Design of Experiments [Slides: 4, 5]

 

May

Speaker

Host/Group

Remarks

Title

4 
(Wed)

Roberto Martinez-Maldonado, 
University of Technology, Sydney (UTS)

Davinia Hernández-Leo (GTI)

3:30 pm 
Room 55.410

Multi-modal sequence mining and analytics of face-to-face collaborative learning

5

Abelardo Pardo, 
University of Sydney

Davinia Hernandez-Leo (GTI)

3:30 pm 
Room 55.410

Feedback at scale with a little help from my algorithms

6 
(Fri)

Rubén Moreno

UPF-DTIC

12:00 pm 
Auditorium

[Integrative Research Seminar]

10 
(Tue)

Miguel Ballesteros, 
UPF-DTIC

TALN

12:30 pm 
Room 52.121

Deep Learning for Transition-based Natural Language Processing. [Streaming]

12

Aurelio Ruiz

UPF-DTIC

3:30 pm 
Room 55.410

Reproducibility in research

18 
(Wed)

Arianne Bercowsky, 
UPF-DTIC

Oscar Camara (PhySense)

4:30 pm 
Room 55.410

Colorectal Cancer preventive treatment approach

19

Malcolm Bain
id law partners

Emilia Gomez (MTG)

3:30 pm 
Room 55.410

Software licensing – from basic to advanced licensing and business models

26

Andreas Kaltenbrunner, 
EURECAT

Vicenç Gómez (AI)

3:30 pm 
Room 55.410

Studying Societal Debates through Wikipedia

 

Jun

Speaker

Host/Group

Remarks

Title

2

 

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3:30 pm 
Room 55.410

 

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9

Rosa Montañà, 
TDX and PhD thesis coordinator

UPF Library

3:30 pm 
Room 52.S29

Copyright in PhD thesis reports. [Slides]

14 
(Tue)

Clarence Barlow, 
UCSB

Xavier Serra (MTG)

3:30 pm 
Room 55.410

On Synthrumentation - the Spectral Analysis of Speech for Subsequent Resynthesis by Acoustic Instruments

16

Hector Geffner

AIG

12:30 pm
Auditorium

[Integrative Research Seminar]

23

 

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30

 

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2014-2015

Sep

Speaker

Host

Remarks

Title

25

Daniele Quercia
Yahoo! Research

Xavier Binefa

3:30pm
Room 52.321

The shortest path to happiness: Recommending beautiful, quiet, and happy routes in the city.Video

 

Oct

Speaker

Host

Remarks

Title

2

 

---

 

 

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3 (Fri)

Bert Kappen
Radboud University Nijmegen, 
The Netherlands

Xavier Binefa (CMTech)

3:30 pm 
Room 55.309

Optimal control and optimal sampling: A statistical physics perspective.

7 (Tue)

Periklis Chatzimisios 
ATEITHE, Tessaloniki, Greece

Boris Bellalta (NeTS)

10:00 am
Room 55.410

Technologies, Standards and Applications of Wireless Local Area Networking (moving from WiFi to 5G)

9

 

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16

 

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23

Jordi Gonzalez
UAB

Xavier Binefa (CMTech)

3:30 pm 
Room 55.410

Towards Video-Hermeneutics: From Pixels to Semantics

24 (Fri)

Shihab Shamma
University of Maryland

Paul Verschure (SPECS)

11:00 am 
Room 55.410

Cortical Mechanisms to Navigate Complex Auditory Scenes

30

José L. Pons
CSIC

Antoni Ivorra (BERG)

3:30 pm
Room 55.410

Hybrid Neurorobots and Neuroprostheses for Rehabilitation and Assistance

 

Nov

Speaker

Host

Remarks

Title

6

Jean-Pierre Changeux
Institute Pasteur, Paris

Paul Verschure (SPECS)

10:30 am 
Poblenou campus Auditorium

The selective stabilisation of synapses and the development of cultural circuits in the human brain

6

Tobias Maier
Maier Mateu Science Communication

Aurelio Ruiz

3:30 pm
Room 55.410

Career Paths for Scientists - The Quest for the Best Alternative

12 (Wed)

Jan D'hooge
KU Leuven

Gemma Piella (SIMBioSys)

12:00 noon 
Room 55.410

Novel directions in Cardiac Ultrasound

13

 

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14 (Fri)

Fernando Villavicencio
National Institute of Informatics, Japan

Jordi Bonada (MTG)

12:00 noon 
Room 52.s31

Some applications of Voice-Transformation to Singing-Voice

20

Jordi Garcia Ojalvo
CEXS, UPF

Aurelio Ruiz

3:30 pm 
Room 55.410

Information integration by dynamical networks

27

Victor Pascual Avila
WebRTChacks.com

Miquel Oliver (NeTS)

3:30 pm
Room 55.410

WebRTC: The Democratization of multimedia communications

 

Dec

Speaker

Host

Remarks

Title

4

 

---

 

 

---

 

 

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11

Giovanni Pezzulo
ISTC-CNR, Italy

Paul Verschure (SPECS)

3:30 pm 
Room 52.s25

Planning and the rat hippocampus

18

 

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25

 

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---

 

 

---

 

 

---

 

 

Jan

Speaker

Host

Remarks

Title

1

 

---

 

 

---

 

 

---

 

 

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8

 

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15

 

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16 (Fri)

Sergio Escalera
UB

Miguel Ángel González Ballester (SIMBioSys)

10:30 am
Room 55.309

Multi-class Learning via Error-Correcting Output Codes and its applications to Human Pose Recovery and Behavior Analysis

22

Mayo Fuster
UAB and Berkman Center

Josep Blat (GTI)

3:30 pm
Room 55.410

P2Pvalue: Conditions that favor value creation in collaborative processes onlineVideo

29

Martha A Garcia-Murillo
Syracuse University

Miquel Oliver (NeTS)

3:30 pm
Room 55.410

Workshop on Leadership and Culture
For Master's and PhD students only!

30 (Fri)

Daniel Grajales
Institut Català de Nanociència i Nanotecnologia

Aurelio Ruiz

10:30 am
Room 52.223

DIYbio Barcelona

 

Feb

Speaker

Host

Remarks

Title

5

Jornada d'Investigadors Predoctorals Interdisciplinària: An all-day event organized by UB and recommended for PhD students. Students interested in participating in the Speed Networking activity or those who would like to have an oral presentation should register by January 18th. No registration is needed if you are only interested in attending the event.

12

Antonios Lioutas
CRG, BIOcomuniCA'T

Aurelio Ruiz

3:30pm 
Room 52.327

Session 1: The basics of good science communication

13 (Fri)

Joan Domingo Gispert
Pasqual Maragall Foundation

Bart Bijnens (PhySense)

12:00 noon
Room 55.410

Neuroimaging in the Alzheimer & Families (ALFA) Study: Role of the APOE4 genotype

Germund Hesslow
Lund University

Paul Verschure (SPECS)

4:00 pm
Room 55.410

Synaptic mechanisms of learned timing in the cerebellum

18 (Wed)

Ángel Alejandro Juan Pérez
UOC

Aurelio Ruiz

3:30 pm
Room 55.410

Simheuristic algorithms: applications to Logistics, Transportation, and Volunteer Computing

19

Antonios Lioutas
CRG, BIOcomuniCA'T

Aurelio Ruiz

3:30pm 
Room 55.410

Session 2: How to prepare a good scientific poster
link to slides

26

Antonios Lioutas
CRG, BIOcomuniCA'T

Aurelio Ruiz

3:30pm 
Room 55.410

Session 3: Preparing your poster
link to slides

 

Mar

Speaker

Host

Remarks

Title

5

Maria Esther Vidal
Universidad Simón Bolívar, Caracas, Venezuela

Jorge Lobo

3:30 pm
Room 55.410

Discovering Associations from Semantically Annotated Biomedical Data
slides in pdf

12

Eugenio Tacchini
Università Cattolica di Piacenza, Italy

Xavier Serra (MTG)

3:30 pm
Room 55.410

State of the art of Music Recommender Systems and open challenges
slides in pdf

18 (Wed)

Francesco Bonchi 
Yahoo Labs Barcelona

Miguel Ángel González Ballester (SIMBioSys)

3:30 pm
Room 52.s31

On information propagation and communities in social networks

19

Juan Alvarez de Lara 
Seed and Click

Aurelio Ruiz

3:30 pm 
Room 52.329

New Ways of Funding: Crowdfunding and Business Angels & PRIMAVERAPRO STARTUPS 2015

26

Naila Murray
Xerox Research Centre Europe

Amin Mantrach (Yahoo! Research)

3:30 pm 
Room 55.410

Generalized Max Pooling

 

Apr

Speaker

Host

Remarks

Title

2

 

---

 

 

---

 

Happy Easter!

 

---

 

7 (Tue)

Ian Poole
Toshiba Medical Visualization Systems, Edinburgh

Miguel Ángel González Ballester (SIMBioSys)

3:00 pm
Room 55.410

Landmarks and Atlases

9

Anastasios A. Economides
University of Macedonia, Greece

Miquel Oliver (NeTS)

3:30 pm
Room 55.410

Internet of Things, Wireless Sensor Networks & Security

16

Marlies Van der Wee
Ghent University

Miquel Oliver (NeTS)

3:30 pm
Room 52.327

Supporting strategic decisions in FTTH deployments – Techno-economic evaluation in a multi-actor setting

23

 

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Happy Sant Jordi! 

 

 

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30

Wolfgang Minker 
University of Ulm

Leo Wanner (TALN)

3:30 pm
Room 55.410

Spoken Dialogue Systems – Towards User-Centred Functionality and Assistance

 

May

Speaker

Host

Remarks

Title

7

Angel Herraiz, 
Utani Lab

Narcís Parés (CMTech)

3:30 pm
Room 55.410

R+D+I (Rock+Dream+Impact)

12 (Tue)

Esteban Maestre, 
McGill University, Montreal

Rafael Ramírez (MTG)

3:30 pm
Room 55.410

Recent progress in efficient physics-based synthesis of string instrument sound

14

David Escudero, 
Universidad de Valladolid

Leo Wanner (TALN)

3:30 pm
Room 55.410

Text-to-speech: past, present and future of talking machines

21

Aurelio Ruiz, 
UPF-DTIC

Internal Speaker

3:30 pm
Room 55.410

Communication Skills in Science: Preparing for Research in 4 minutesslides in pptx

27 (Wed)

Anders Jonsson, 
DTIC, UPF

Artificial Intelligence Group (AIG)

3:30 pm 
Room 55.410

Under the Hood of Deep Learning

28

Amparo Alonso Betanzos, 
Universidade da Coruña

Miquel Oliver (NeTS)

3:30 pm
Room 55.410

Divide et impera: Machine Learning for distributed environments

 

Jun

Speaker

Host

Remarks

Title

4

Monika Dominguez Bajo, 
DTIC, UPF

Internal Speaker (TALN)

3:30 pm
Room 55.410

Presenting your Research Proposal. A Hands-On Workshop.slides in pdf

8 (Mon)

Jan Atkinson, 
University College London
Oliver Braddick, 
University of Oxford

Nava Rubin

3:30 pm
Room TBA

The Developing Visual Brain: from newborn infants to numeracy

11

Alessandro Checco, 
Trinity College Dublin

Boris Bellalta (NeTS)

3:30 pm
Room 55.410

Privacy Issues in Recommender Systems

18

Gabriel Martins Dias, 
UPF-DTIC

Internal Speaker (NeTS)

3:30 pm 
Room 55.410

6 Reasons Why You Should Start Using R

25

DTIC Participants of Rin4

UPF-DTIC

3:30 pm 
Room 55.410

Get to know about your colleagues' experience of participating in Research in 4 Minutes

2013-2014

Sep

Speaker

Host/Group

Remarks

Title

26

 

---

 

 

---

 

Room 52.321, 3:30pm

 

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Oct

Speaker

Host/Group

Remarks

Title

1 (Tue)

Jônatas Manzolli
UNICAMP, Brazil

Narcis Pares (CMTech)

Room 55.309 
3:30pm

Interactive Composition, Sonification based on Models derived from Computational Neuroscience

3

 

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Room 52.321, 3:30pm

 

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10

Paul Verschure 
UPF-DTIC

Internal Speaker (SPECS)

Room 52.321, 3:30pm

Consciousness in Brains and Machines: The Distributed Adaptive Control theory of consciousnessVideo

17

Javier Vázquez-Corral
UPF-DTIC

Internal Speaker (IP4EC)

Room 52.321, 3:30pm

Color constancy in natural scenes through color naming and sensor sharpenningVideo

24

George Tzanetakis
University of Victoria

Xavier Serra (MTG)

Room 52.321, 3:30pm

Physical Modelling Beyond Sound Synthesis: three case studiesVideo

31

Lonce Wyse
National Univ. of Singapore

Sergi Jordà (MTG)

Room 52.321, 3:30pm

Audio and Interaction through the BrowserVideo

 

Nov

Speaker

Host/Group

Remarks

Title

7

Dimitris Kugiumtzis
Aristotle University of Thessaloniki

Ralph Andrzejak (NTSA)

Room 52.321, 3:30pm

Time series, connectivity and networksVideo

13 (Wed)

Bob L. Sturm
Aalborg University

Xavier Serra (MTG)

Room 55.410 
3:30pm

The crisis of evaluation in MIR

14

Felipe Calderero
UPF-DTIC

Internal Speaker (GPI)

Room 52.321, 3:30pm

Recovering relative depth from low-level features without explicit T-junction detection and interpretationVideo

21

Tammo Delhaas 
University of Maastricht

Bart Bijnens (PhySense)

Room 52.321, 3:30pm

SIT happens...but doesn't pose problems

22 (Fri)

Jean-Julien Acouturier
Temple University, Japan

Xavier Serra (MTG)

Room 55.410 
3:30pm

Spectro-temporal receptive fields (STRFs): a biologically-plausible alternative to MFCCs?

27 (Wed)

Thomas Wosch
University of Applied Sciences Würzburg-Schweinfurt

Perfecto Herrera (MTG)

Room 52.S29 
3:30pm

Introduction to music therapy and use of ICT in music therapy diagnostic

28

Gonzalo Vázquez Vilar
UPF-DTIC

Internal Speaker (ITC)

Room 52.321, 3:30pm

Sub-Nyquist SamplingVideo

 

Dec

Speaker

Host/Group

Remarks

Title

5

Germund Hesslow
Lund University

Paul Verschure (SPECS)

Room 55.410 
11:00am

Pavlovian conditioning of motor responses. What do we know about the physiology?

12

 

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19

 

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---

 

26

 

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---

 

 

---

 

 

Jan

Speaker

Host/Group

Remarks

Title

2

 

---

 

 

---

 

 

---

 

 

---

 

9

Gabriele Facciolo 
ENS Cachan, France

Coloma Ballester (GPI)

Room 52.321, 3:30pm

Reproducible Research, IPOL, and Satellite Stereo ImagePDF

16

Julián Urbano 
UPF-DTIC

Internal Speaker (MTG)

Room 52.321, 3:30pm

Evaluation in (Music) Information Retrieval through the Audio Music Similarity taskVideo

21 (Tue)

Gustavo Deco
UPF-DTIC

Internal Speaker (CNS)

Room 52.019 
10:30-12:30 (2 hours)

Linking the Functional and Structural Human Connectome

23

Juan Alvarez de Lara
Seed and Click

Aurelio Ruiz

Room 52.321, 3:30pm

New Ways of Financing: Crowdfunding and business angelsVideo

30

 

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Room 52.321, 3:30pm

 

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Feb

Speaker

Host/Group

Remarks

Title

4 (Tue)

Jérôme Noailly
IBEC

Oscar Camara (PhySense)

Room 52.321 
10:30-12:30 (2 hours)

In silico integration of biomechanical and biophysical models to explore musculoskeletal diseases

6

Ana Baiges and Anna Magre
UPF Library Services

Aurelio Ruiz

Room 52.321, 3:30pm

Scientific Dissemination, Online Repositories, and Author's RightsVideoPDF

13

Miriam Redi
Yahoo! Research

Ricardo Baeza-Yates (WRG)

Room 52.321, 3:30pm

Can Machines Like and Understand Pictures?Video

18 (Tue)

James Sharpe
Centre de Regulació Genòmica

Oscar Camara (PhySense)

Room 52.223 
10:30-12:30 (2 hours)

Data-driven multiscale modelling of organogenesis

20

Malcolm Bain
id law partners

Emilia Gómez (MTG)

Room 55.309, 3:30pm

IPR in the XXI Century – are we doing it right?Video

25 (Tue)

Mariano Vázquez
Barcelona Supercomputing Center (BSC)

Oscar Camara (PhySense)

Room 52.223 
10:30-12:30 (2 hours)

HPC-based cardiovascular simulations

27

Pablo Serrano
UC3M, Madrid

Jaume Barcelo (NeTS)

Room 52.321, 3:30pm

Greening (Heterogeneous) Wireless Networks: Overview and Future Directions

 

Mar

Speaker

Host/Group

Remarks

Title

4 (Tue)

Paula Rudenick
Hospital de la Vall d'Hebron and UPF

Oscar Camara (PhySense)

Room 52.321 
9:30-11:30 (2 hours)

Multidimensional approaches for modelling cardiovascular haemodynamics

6

Mariano Alcañiz
LabHuman, UPV

Josep Blat (GTI)

Room 52.321, 3:30pm

Objective techniques for presence measurement in virtual environments by means of brain activity analysisVideo

13

Antoni Buades 
Universitat de les Illes Balears

Gloria Haro (GPI)

Room 52.321, 3:30pm

A Nonlocal Variational Model for Pansharpening Image FusionVideo

20

Boris Bellalta
UPF-DTIC

Internal Speaker (NeTS)

Room 52.321, 3:30pm

Next-Generation Wireless Networks: 2020 - 2030

26 (Wed)

Gloria Haro
UPF-DTIC

Inernal Speaker (GPI)

Room 55.410, 3:30pm

Image processing and computer vision techniques for digital post-production, image enhancement, and 3D reconstruction

27

Ernest Montbrió 
UPF-DTIC

Internal Speaker (CNS)

Room 55.410, 3:30pm

Dynamics of large populations of interacting cells: Collective synchronization and other forms of self-organization in complex systems.

 

Apr

Speaker

Host/Group

Remarks

Title

2 (Wed)

Horacio Saggion
UPF-DTIC

Inernal Speaker (TALN)

Room 55.410
3:00 pm

Inducing Templates from Concise Summaries

3

Olivier Van Laere
Yahoo! Research

Ricardo Baeza-Yates (WRG)

Room 52.321, 3:30pm

Find me if you can: predicting geographical coordinates from unstructured textVideo

10

Mehdi Molkaraie

Albert Guillén i Fàbregas (ITC)

Room 52.321, 3:30pm

Partition Function of the Ising Model via Factor Graph Duality

11 (Fri)

Alexis Roche
Siemens Healthcare
Lausane, Switzerland

Miguel Ángel González Ballester (SIMBioSys)

Room 55.410
3:30 pm

Statistical modeling and inference in brain image processing

17

 

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24

Luca Bonatti
UPF-DTIC (CBC)

Internal Speaker (RICO)

Room 55.309, 3:30pm

Rational reasoning in an infant mind

25 (Fri)

Arrate Muñoz Barrutia
University of Navarra

Miguel Ángel González Ballester (SIMBioSys)

Room 55.410
3:30 pm

About lung cancer, one cell at a time.

 

May

Speaker

Host/Group

Remarks

Title

1

 

---

 

 

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---

 

5 (Mon)

Yue Zhang
Singapore University of Technology and Design

Leo Wanner (TALN)

Room 55.410
3:30 pm

Syntax-based word ordering: a learning-guided-search approach

8

Subhrakanti Dey
Uppsala University

Albert Guillén i Fàbregas (ITC)

Room 52.321, 3:30pm

Throughput Scaling Laws for Undelay Cognitive Multiple Access ChannelsVideo

15

Vicenç Gómez 
UPF-DTIC

Internal Speaker (AI)

Room 52.321, 3:30pm

Some fundamental topics on machine learning and applications

22

Manel Simon
Manduka Games

Aurelio Ruiz

Room 52.321, 3:30pm

Wearable Gaming. Sustainable R+D+i

27 (Tue)

Gemma Àlvarez Cruellas 
UPF Library Services

Aurelio Ruiz

Room 54.021 (Tallers)
3:30pm
REGISTER HERE!!!

Mendeley Workshop

29

Sergio Sayago
UC3M

Josep Blat (GTI)

Room 52.321, 3:30pm

Ethical aspects in research involving human participants in ICTs: questions to live with and an ongoing mindsetVideo

30 (Fri)

Alejandro Ribés Cortés
EDF - Electricité de France

Miguel Ángel González Ballester (SIMBioSys)

Room 52.S27
3:30 pm

In-situ Analysis and Visualization for Large Fluid Mechanics Simulations: Visual Coprocessing and Parametric Statistical Studies for Code_Saturne

 

Jun

Speaker

Host/Group

Remarks

Title

5

Miguel-Angel Otaduy 
URJC, Madrid

Josep Blat (GTI)

Room 52.321, 3:30pm

Modeling and Animation of Complex Mechanical Phenomena - Looking for the Right Models and Algorithms

11 (Wed)

Thomas Pengo
Centre for Genomic Regulation, Barcelona

Miguel Ángel González Ballester (SIMBioSys)

Room 55.410
10:00 am

Observing life with computers. Where biology, optics and computer science meet

12

Sergi Valverde
CEXS, UPF

Aurelio Ruiz

Room 52.321, 3:30pm

Networks in Action: Communication, Computation and EvolutionVideo

19

 

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26

Carlos Alberto Figueroa
University of Michigan and King's College

Bart Bijnens (PhySense)

Room 52.S27
4:00 pm

Advances in 3D Blood flow Simulation: Methods and Clinical Applications

30 (Mon)

Carlos H. Muravchik
La Plata National University, Argentina

Federico Sukno(CMTech)

Room 52.S27​
10:30 am

Some results on EIT conductivity-change tracking and the effect of a subdural grid on scalp EEG

2012-2013

Sep

Speaker

Host/Group

Remarks

Title

26 (Wed)

Gert Lanckriet
University of California, San Diego

Emilia Gómez (MTG)

Room 52.421
12:00pm

Music Recommendation with Multi-Modal Metric Learning to Rank

27

 

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Oct

Speaker

Host/Group

Remarks

Title

4

Gautham J. Mysore
Adobe's Advanced Technology Labs, San Francisco

Xavier Serra (MTG)

Room 52.321, 3:30pm

Non-negative Hidden Markov Modeling of Audio

11

Vladimir Estivill-Castro
UPF, DTIC

Internal Speaker (WRG)

Room 52.321, 3:30pm

Failure mode and effects analysis (FMEA) and model-checking of software for embedded systems by sequential scheduling of vectors of logic-labelled finite-state machines

16 (Tue)

Annalu Waller
University of Dundee

Ricardo Baeza-Yates (WRG)

Room 55.309
12:30pm

Augmentative and Alternative Communication across the Lifespan of Individuals with Complex Communication Needs.PDF

16 (Tue)

Irina Bocharova 
St. Petersburg University of Information Technologies

Albert Guillén i Fàbregas (ITC)

Room 55.309
3:30pm

Woven graph codes

18

 

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Room 52.321, 3:30pm

 

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23 (Tue)

Thippur V. Sreenivas
Indian Institute of Science, Bangalore