DHC | Data Sciences | May 18, 2017

Professor Vincent Blondel,
Rector of the Université catholique de Louvain,
Professor Michel Devillers,
Vice Rector of the Science and Technology Sector,
Professor Michel Verleysen,
Dean of the Louvain School of Engineering,
Professor Enrico Vitale,
Dean of the Faculty of Science,
Professor Philippe Chevalier,
Head of the IMMAQ institute,
Professor Jean-Didier Legat,
Head of the ICTEAM institute,

will be honoured to welcome you to the awards ceremony for the title of Doctor honoris causa

to Professor Stephen Boyd, and Professor Peter Bühlmann

for their achievements in the field of « Data Sciences »

Stephen Boyd

Professor of electrical engineering, Stanford University

Stephen Boyd is Professor of Electrical Engineering at Stanford University. He received the A.B. degree in Mathematics from Harvard University in 1980, and the Ph.D. in Electrical Engineering and Computer Science from the University of California, Berkeley, in 1985, and then joined the faculty at Stanford.
His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance. He is the author of numerous highly cited research articles, three books, and several open-source tools.
Stephen Boyd is a Fellow of the IEEE, SIAM, and INFORMS, a Distinguished Lecturer of the IEEE Control Systems Society, and a member of the National Academy of Engineering. He received many awards for his teaching and research, including the IEEE Control Systems Award, the IEEE James H. Mulligan, Jr. Education Medal and the Mathematical Optimization Society’s Beale-Orchard-Hays Award.

Peter Bühlmann

Professor of mathematics and statistics, ETH Zürich

Peter Bühlmann is Professor of Mathematics and Statistics, and currently Chair of the Department of Mathematics at ETH Zürich. He received his doctoral degree in mathematics in 1993 from ETH Zürich. After having spent three years at UC Berkeley, he returned to ETH Zürich in 1997.
His main research interests are in high-dimensional and computational statistics, machine learning, causal inference and applications in the bio-medical field. He has been a highly cited researcher in mathematics in the last few years.
Peter Bühlmann is Fellow of the IMS, the ASA and recipient of several awards including the Winton Research Prize. He served as Co-Editor of the prestigious Annals of Statistics during 2010-2012 and has guided 29 doctoral students to date.

on Thursday, May 18, 2017

Auditorium BARB 94

Programme

08:30 am | Welcome
09:00 am | Introduction to the workshop on «Data sciences»

09:10 am | Optimisation, networks and machine learning
(F. Glineur, UCL - J.-C. Delvenne, UCL - P. Dupont, UCL)

François Glineur, UCL - Performance estimation of first-order optimization methods

Optimization algorithms are widely used in a large variety of domains in engineering, computer science, economics and management. Because of the ever-increasing amounts of data available and the growing demand for more accurate models, larger and larger optimization models have to be solved. This is one of the reasons for the renewed interest in first-order methods, which are particularly suited for large-scale models. In this talk, we describe the recently developed framework of performance estimation, that allows to compute tight performance guarantees for a large class of first-order methods in a completely automated manner.

Jean-Charles Delvenne, UCL - Network Science: data science meets dynamical systems

Network science has appeared as the unifying framework able to formulate parallel questions emerging in different communities -computer science, statistics, physics, control theory-pertaining to the pairwise interactions of many individual entities. We focus on the example of clustering, aka community detection, intuitively defined as the search of densely connected subgraphs. In different contexts- image processing, bioinformatics, social analysis, multi-agent systems, etc.-it may be formulated as a variant of minimum cuts in graphs, as a statistical inference problem, as a model-reduction problem for the dynamics taking place on the networks, such as opinion dynamics or epidemics. Although arising from different motivations, the mathematical formulations overlap on simple cases (undirected networks, memoryless dynamics, etc.) which they generalise in different directions. We discuss these formulations and their hidden pitfalls.

Pierre Dupont, UCL - Machine learning methods for precision medicine: even small data can raise big challenges

Machine learning (ML) is the science of getting computers to act without being explicitly programmed. ML typically follows a data-driven methodology where models are built from observed data before making predictions on new data.
This talk will present several ML applications to precision medicine, an area of medicine where decisions, treatment and follow-up are aimed to be tailored to each individual patient.

We present prototypical examples including breast cancer prognosis, early diagnosis of undifferentiated arthritis or treatment response prediction of an immunotherapy against melanoma.
Such examples illustrate core ML concepts including multi-class prediction, multitask or transfer learning, and feature selection.

At times where big data is ubiquitous, we discuss briefly why scarce data can sometimes be even more challenging.

10:25 am | Coffee break

10:45 am | Statistics and spatial geography (B. Govaerts, UCL and I. Thomas, UCL)

Bernadette Govaerts, UCL - Integrating chemometrics and statistical methods in the analysis of spectral Omics data

The use of omics technologies becomes common in a variety of health and pharmaceutical applications with the aim of better understanding the link between the genetic, transcriptomics, proteomic, metabolomic… profiles of biological samples with outcomes of interest as the presence of a disease, a treatment effect,… Among these technologies, spectroscopic techniques (MS, NMR) produce target or untargeted proteomic or metabolomic fingerprints in the form of 1D or 2D high-dimensional spectra that must be preprocessed by finely tuned algorithms and analyzed by advanced multivariate methods in order to extract the relevant information for the biological/medical question of interest.
The talk will present several places where the integration of statistical and chemometrics methods provide solutions to process and analyze spectral omics data and how the UCL metabolomic team of ISBA/IMMAQ tries to contribute to the field. Chemometrics methods, traditionally applied in chemistry to the analysis of spectral data, have indeed limitations in the presence of (omics) biological samples affected many sources of variability, issued from complex experimental studies and to answer questions where interpretability and reliable statistical significance measures are necessary to validate the outcomes of the data analysis (e.g. biomarker discovery).

Isabelle Thomas, UCL - « Big data » in urban and economic geography: revolution or evolution?

BRUNET is a 4 years multidisciplinary research project financed by Innoviris and running at CORE. It aims at revealing socio-economic communities in and around Brussels with big data.
We here present a selection of results and demonstrate (1) how this new generation of data and methods are undoubtedly opportunities for geographers and decision makers, but (2) big data are not “the” panacea from solving most quantitative geography issues. There is still a high potential for further multidisciplinary research. Big data are like statistics: « What they reveal is suggestive, but what they conceal is vital ».

11:30 am    |   Round table: Moderator: Michel Verleysen (UCL).
                        Stephen Boyd (Stanford University), Peter Bühlmann (ETH Zürich),
                        Pierre Deville (Bisnode Group), Thibault Helleputte (DNalytics)

12:00 pm | Lunch

2:00 pm | Presentation by Stephen Boyd, Stanford University - « Convex Optimization »

Convex optimization has emerged as useful tool for applications that include data analysis and model fitting, resource allocation, engineering design, network design and optimization, finance, and control and signal processing.
After an overview of the mathematics, algorithms, and software frameworks for convex optimization, we turn to common themes that arise across applications, such as sparsity and relaxation.
We describe recent work on real-time embedded convex optimization, in which small problems are solved repeatedly in millisecond or microsecond time frames, and large-scale distributed convex optimization, in which many solvers are coordinated to solve enormous problems.

3:00 pm | Presentation by Peter Bühlmann,ETH Zürich - « The Statistics-"Machine" in Data Science »

Statistics plays a unique role in Data Science for quantifying uncertainties, addressing pressing needs on replicability, and contributing towards improving the search for scientific findings. We will discuss recent developments for statistical inference statements in high-dimensional, large-scale data models - from regression to causality.

4:30 pm | Doctor Honoris Causa ceremony
5:30 pm - 7:00 pm | Drink (Hall Sainte Barbe)

The ceremony will be held in the Auditorium BARB 94 - Place Sainte Barbe, 1 - 1348 Louvain-la-Neuve
All professors are invited to wear their gown / The cortege will depart from the « décanat EPL » Rue Archimède, 1 at 4:15 pm.

Registration is free but compulsory. Please register by completing the registration form. / Registration deadline: April 25, 2017

Recommended parking: Baudouin 1er

Contact person

Mrs. Tatiana Regout
tatiana.regout@uclouvain.be
+32.10.47.94.07

Accommodation

We suggest the hotel IBIS next to the campus, others are in the area of the campus

    • Hotel Ibis Styles Meeting Center
    Boulevard de Lauzelle, 61
    B - 1348 Louvain-la-Neuve, Belgique
    Phone: +32 (0)10 53 90 00 (booking) +32 (0) 10 45 07 51 (Reception)
    Website : Ibis Styles

    • Best Western Wavre Hotel (with shuttle to LLN)
    B - Avenue Lavoisier 12 - 1300 Wavre, Belgique
    Phone: +32 (0)10 88 74 30
    Website : http://www.bestwesternwavre.com/

    • Hotel "Les 3 Clés" (with public transport to LLN)
    B - Chaussée de Namur 17 - 5030 Gembloux, Belgique
    Phone: +32 81 61 16 17
    Website : http://www.3cles.be/

    • Hotel Leonardo (with shuttle transport to LLN)
    B - Rue de la Wastinne 45 B - 1301 Wavre
    Phone: +32 (0)10 41 13 63
    Website : https://www.leonardo-hotels.com/leonardo-hotel-wavre