Research Seminars Archives >> 

January

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 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 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.
 

February, 1st 

10:00 

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.

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,8th 

15:30

Room 55.410

Phd Research Seminar

A professional career in Data Science, a personal view

By Aleix Ruiz de Villa.

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,15th 

15:30

Room 55.410

Phd Research Seminar

Scientific Dissemination, Online Repositories, and Author's Rights

By  Ana Baiges
 

Abstract

 

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.

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.

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, 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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