Sparse regularization for multi-omics data

20th May 2021
13:00-14:30 (WEST – Lisbon) / 14:00-15:30 (CEST) (held online)

Speakers: Susana Vinga (INESC-ID/IST) & Valentina Boeva (ETH Zürich)
Chair/Moderator: Niko Beerenwinkel (ETH Zürich)

ZOOM link: https://videoconf-colibri.zoom.us/j/84981014599
No password or registration needed for this session

The Twin Seminars will contribute to disseminate the scientific work and expertise of INESC-ID and all the Olissipo Project Consortium that includes Inria, ETH Zürich and EMBL. These seminars will comprise two short presentations, one researcher from Lisbon and one from a twin international institution working on similar topics in Computational Biology. The seminars will be opened to everyone interested and will include a discussion to further promote the interaction between all the participants.

Abstract

Regularized optimization has proved to be a promising and valuable strategy to solve regression problems in high-dimensional spaces by imposing constraints on the parameters. We will discuss novel methods beyond the classical elastic net that allows to include a priori knowledge, such as network-based information. The application to multi-omics patient data, from classification problems to survival analysis, illustrates the potential of sparse structured models for more interpretable and personalized medicine.

Short Bios

Susana Vinga, Instituto Superior Técnico (IST) and INESC-ID (Lisbon, Portugal)

Susana is an Associate Professor at IST (ULisboa) in a joint position at the Dept. of Computer Science and Engineering (DEI) and the Dept. of Bioengineering (DBE). She is a Senior Researcher at INESC-ID in the Information and Decision Support Systems lab, a member of the INESC-ID Board of Directors, and Vice-President of DEI. Prof. Vinga received a Mechanical Engineering degree (1999), a post-graduate degree in Probability and Statistics at IST, a Biomedical specialization at Politecnico of Milan, and a PhD degree in Bioinformatics (2005) at ITQB-UNL (Portugal). From 2006-2013, she was a researcher in the Knowledge Discovery and Bioinformatics group at INESC-ID and invited assistant professor of Biostatistics and Informatics at the Faculty of Medical Sciences. Between 2013-2018 she was a Principal Investigator at Mechanical Engineering Institute (IDMEC/IST). In 2010, she was granted the Young Research Award of the Technical University of Lisbon, and in 2017 she was awarded the Scientific Prize of ULisboa/CGD in the area of Computer Science and Engineering for the impact of her publications. Susana’s main scientific achievements are in the area of systems biology, with the development of models for the analysis of biological networks, and in computational biology and bioinformatics, where she is interested in data science and machine learning methods for the analysis of high-dimensional clinical data. Susana is the Principal Coordinator of the OLISSIPO Twinning Project.

Valentina Boeva, ETH Zürich (Zürich, Switzerland)

Valentina is a Tenure Track Assistant Professor of Biomedical Informatics at the Department of Computer Science of ETH Zürich (Switzerland). She was previously a group leader of the laboratory of Computational Epigenetics of Cancer at Inserm, located at the Cochin Institute in Paris, France (2016-2021). Prof. Valentina received a MSc degree in Applied Mathematics (2003) at Lomonosov Moscow State University (MSU) (Russia) and a PhD degree in Biophysics and Bioinformatics (2007) at MSU. From 2002-2006, she also worked at Inria (France) in sequence analysis algorithms and statistics of DNA motifs and from 2004-2007 in GosNIIgenetika developing statistical methods for DNA sequence analysis. Valentina also worked at Ecole Polytechnique (France) where she contributed to the analysis of cancer-related metabolic networks (2007-2008). Before joining the Cochin Institute in 2016, she worked for about seven years at the Curie Institute, also in Paris. First as a postdoc, then as a researcher scientist. Valentina was an ATIP-Avenir 2015 laureate and received the French Embassy Award in 2012. Her research focuses on understanding the role of epigenetic cancer drivers, and developing computational approaches to process multi-omics information to help clinicians make treatment choices for cancer patients based on genomic, epigenetic, transcriptomic, and other information.

Know more about Olissipo Project at https://olissipo.inesc-id.pt/

LxMLS 2021 will take place July 7th to July 15th in online format (via zoom and slack). It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), Unbabel and Cleverly.

Click here for information about past editions (LxMLS 2011, LxMLS 2012, LxMLS 2013, LxMLS 2014, LxMLS 2015, LxMLS 2016, LxMLS 2017, LxMLS 2018, LxMLS 2019, LxMLS 2020) and to watch the videos of the lectures (2016, 2017, 2018, 2020).

Call for Participation

Important Dates
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* Application Deadline: May 15, 2021
* Decision: June 1, 2021
* Early Registration: June 15 – July 1, 2021
* Summer School: July 7 – 15, 2021


Topics and Intended Audience
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The school will cover a range of Machine Learning (ML) topics, from theory to practice, that are important in solving Natural Language Processing (NLP) problems that arise in the analysis and use of Web data.

Our target audience is:

• Researchers and graduate students in the fields of NLP and Computational Linguistics;
• Computer scientists who have interests in statistics and machine learning;
• Industry practitioners who desire a more in depth understanding of these subjects.

Features of LxMLS:

• No deep previous knowledge of ML or NLP is required, but the attendants are assumed to have some basic background on mathematics and programming
• Lecturers are leading researchers in machine learning and natural language processing (see speakers)
• Days are divided into morning lectures and afternoon lab sessions and practical talks (see schedule)
• The Labs guide will be provided one month in advance. Last year’s guide can be found here
• A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises
• Both basic (e.g linear classifiers) and advanced topics (e.g. deep learning, reinforcement learning) will be covered

Online Format:

Due to the current COVID-19 pandemic, the 11th Lisbon Machine Learning School will be held online (via zoom and slack). Similar to last year, we are excited for the opportunity to create a virtual school, where you will be able to attend all the lectures, and participate in the Q&As and labs remotely. We will also provide the tools for students to engage with each other remotely. The lectures will also be streamed to YouTube, and will become freely available later in our YouTube channel. The Q&A, labs and social activities will remain restricted to the accepted students only.

List of Confirmed Speakers
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LUIS PEDRO COELHO Fudan University | China
MÁRIO FIGUEIREDO Instituto de Telecomunicações & Instituto Superior Técnico | Portugal
ANDRE MARTINS Instituto de Telecomunicações & Unbabel | Portugal
IRYNA GULEYVICH Technical University Darmstat | Germany
NOAH SMITH University of Washington & Allen Institute for Artificial Intelligence | USA
SLAV PETROV Google Inc. | USA
XAVIER CARRERAS dMetrics | USA
GRAHAM NEUBIG Carnegie Mellon University | USA
BHIKSHA RAJ Carnegie Mellon University | USA
CHRIS DYER Google Deep Mind | UK
ELIAS BARENBOIM Columbia University | USA
ADELE RIBEIRO Columbia University | USA
STEFAN RIEZLER Institut für Computerlinguistik, Universität Heidelberg | Germany
BARBARA PLANK IT University of Copenhagen | Denmark
SASHA RUSH Cornell Tech | USA

Please visit the webpage for up to date information: http://lxmls.it.pt/2021

To apply, please fill the form in https://lisbonmls.wufoo.com/forms/application-form-lxmls-2021/
Any questions should be directed to: lxmls-2021@lx.it.pt.

The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.

Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.

The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).

Important Dates:
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021

More information is available here.