Past Research Seminars
December   
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, 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

January  
January, 24th  
 
15:30 h
 
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.

February  
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/

If the seminar is ofered via streaming in: 

- Room 55.309 or 55.410 follow this link

- Auditorium follow this link

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