Research Seminars Archives >> 

November 

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.

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,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

January, 11th 

15:30

Room 55.309

PhD Research Seminar

"How to prepare a good abstract"

By Bart Bijnens

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.

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 impres
 

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,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:

  1. Linear regression

  2. T-test

  3. F-test

  4. Analysis of Variance (ANOVA)

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,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.

The second part of the course will apply the theory presented in the first part in order to present different kind of advanced Design of Experiments.

Power analysis for the a-priori identification of the required sample size. The complete and fractioned factorial projects, the “confounding” i.e. concept of confused effect, determination of blocs in functions of confused effects and presentation of the Taguchi’s Method.

The course will than introduce the analysis with more than 2 levels and how to evaluate linear and quadratic component of the data.

It will finally conclude with the Response Surface Methodology for the analysis of continuous variables.

March, 1st 

13:30

Room 52.223

Phd Seminar : Software development best-practices for reproducible research

By  Alastair Porter

March, 8th 

15:30

Room 55.410

 

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. 

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