The Steering Board
The program committee designates the projects and animation actions to be supported. It is composed of :
- representatives of 8 graduate schools (known as "GS") of the Université Paris-Saclay ;
- five national research organizations ;
- a representative of the Institut Minès-Télécom Business School ;
- 2 representatives of the Institut Polytechnique de Paris and HEC.
Research Director at CEA, François Terrier is in charge of the Artificial Intelligence program at CEA. After a PhD in AI and 10 years of R&D in the field, he conducted research on software engineering and trust systems. Author of more than 100 publications, he was the CEA representative in the network of excellence on real-time systems led by Joseph Sifakis, and a player in the standardization of this topic at the OMG. Department head from 2010 to 2020, he was in charge of the development of activities on model-based engineering and formal methods that led to the production of international open source platforms (Papyrus, Frama-C). In this mission, he supported the emergence of new activities on cyber security, resilient distributed systems, including blockchain. Thanks to his dual culture in AI and trust systems engineering, he has built the CEA's artificial intelligence of trust axis, which he pilots and deploys in various projects such as confiance.ai and the European network of excellence TAILOR.
Pierre Zweigenbaum, PhD, FACMI, FIAHSI, is a senior researcher at the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN, Orsay, France), a laboratory of the Centre National de la Recherche Scientifique (CNRS) and the University of Paris-Saclay, where he led LISN's natural language processing group for seven years. Before the CNRS, he was a researcher at the Paris Public Hospitals in an Inserm team for twenty years. He was also a part-time professor at the Institut national des langues et civilisations orientales for ten years. His research focuses on natural language processing, with medicine as the main field of application. He is interested in information extraction in multilingual contexts and has authored or co-authored methods and tools for detecting various types of medical entities, extending abbreviations, resolving coreferences, and detecting relationships. He has also designed methods for automatic linguistic knowledge acquisition from corpora and thesauri, to help extend monolingual and bilingual lexicons and terminologies, using parallel and comparable corpora. He graduated from École Polytechnique (1980) and Télécom Paris (1982), and holds a PhD from Télécom Paris (1985). A former vice president of the French Association for Natural Language Processing (ATALA) and the French Association for Artificial Intelligence (AFIA), founder and president of the French-speaking SIG of the International Medical Informatics Association, he was elected fellow of the American College of Medical Informatics in 2014 and fellow of the International Academy of Health Sciences Informatics in 2019.
Lina Ye studied computer science and information systems at the University of Surrey, England, and the University of Paris-Sud 11. She then received the PhD degree in Computer Science from the University of Paris-Sud 11, France, in 2011. She held a post-doctoral position in the CONVECS research team at Inria Rhône-Alpes in 2012-2014.
She is currently an associate professor in computer science at CentraleSupélec, Université Paris Saclay. Her research work was done at the LRI (Laboratoire de Recherche en Informatique) laboratory until the end of 2020 and now at the LMF (Laboratoire Méthodes Formelles) laboratory, Université Paris Saclay, France.
Alexandra Bensamoun is a professor of private law and criminal sciences (University of Paris-Sud/Paris-Saclay - Center for Studies and Research in Intellectual Property Law - CERDI), specializing in IP/IT. Appointed as a qualified personality at the Conseil Supérieur de la Propriété Littéraire et Artistique (CSPLA), she has conducted several reports for the Ministry of Culture, for example on the status of Internet technical intermediaries and on the right of communication to the public. She is a member of the DATAIA Institute's Board of Directors, and is very involved in scientific research and reflection on AI. She has written several contributions on its regulation, particularly in terms of responsibility and ethics. She also co-led the "Legal Issues" part of the #FranceIA report (at the request of the Prime Minister, 2017).
Fabrice Le Guel is an economist, HDR lecturer at the University of Paris Saclay, member of the board of directors of the Master 2 IREN (Network Industries and Digital Economy). His research interests include digital economics, innovation economics, network economics and privacy economics. He co-directs with Laurence Devillers the Chair in Artificial Intelligence 'HUMAAINE' (HUman-MAchine Affective INteraction & Ethics) and is a member of the program committee of the DATAIA Paris-Saclay Institute.
Emmanuel Vazquez is a researcher in the field of Bayesian design and analysis of computer experiments (Bayesian DACE). He teaches Bayesian statistics at CentraleSupélec. He is also the coordinator of data science projects. In the past, he has also taught functional analysis and probability theory.
The design and analysis of computer experiments consists in using statistical approaches to solve problems such as approximation, uncertainty quantification, optimization... involving computer programs (or simulators) that emulate physical systems (see, for example, Santner 2003). His work is based on Bayesian sequential decision theory. In the domain of computer experiments, the Bayesian approach begins with a prior distribution that represents our prior belief about the structure of the computer model. The use of this approach for computer experiments emerged in the 1980s (see the seminal paper by Sacks et al. 1989).
Teaching : Numerical methods - Data analysis - Statistical modeling - Neural networks - Statistical learning.
Responsible for the Master TRIED (Information Processing and Data Exploitation)
Research : statistics applied to the environment - observation and modeling of atmospheric precipitation (extreme events) - spatial remote sensing
Specializations : Research in statistics applied to the natural environment, Teaching, Research contracts, Journal reporter, Habilitation to direct research. Head of the SPACE (Statistical Process Atmosphere Water Cycle) team at LATMOS
His research activity is focused on the evolutionary analysis of genomes and biological networks. In this context, Olivier Lespinet is involved in the development of several projects, the most significant of which are described below :
- The evolution of synteny in prokaryotes
The exhaustive comparison of the sequences of several hundred prokaryotic genomes has allowed us to identify numerous families of orthologous genes, i.e. sets of genes that have a common ancestor and that are related to each other only by speciation events. Among these families, we looked for orthologous genes whose neighborhood is conserved during evolution. These groups of genes constitute what is called synteny blocks.
- The discovery and identification of orphan enzymatic activities
Each original enzymatic activity is associated with a unique identifier consisting of a series of 4 digits called EC number. This identifier allows to indicate in a precise and univocal way the biochemical function of each enzyme. For example the EC number 22.214.171.124 is associated with enzymes of the alcohol dehydrogenase type.
- Annotation and genome analysis of the filamentous fungus Podospora anserina
Podospora anserina is a filamentous fungus of the class Ascomycetes that grows on the excrement of herbivores. It is also a model organism that has been used in genetics for more than 60 years to study different fundamental biological processes such as meiosis, aging or prion-like proteinaceous inheritance mechanisms. The nuclear genome sequence of the S mat+ strain of Podopsora was determined and assembled by the Genoscope. It is a 10X coverage obtained by a Shotgun approach.
- Study of the diversity, dynamics and evolution of biological networks
The study of biological networks (genetic regulation networks, protein interaction networks, metabolic networks) is a good way to understand how life evolves and functions. Apart from purely experimental approaches aiming, for example, at listing the proteins interacting with each other in a given physiological condition for a particular organism, in silico approaches based on these experimental data coupled with comparative genomics approaches also allow today to study biological networks.
Mathilde Mougeot is a researcher and professor in data science at the École nationale supérieure d'informatique pour l'industrie et l'entreprise (ENSIIE) and holds the Industrial data analytics and machine learning chair at the Borelli Center.
Her atypical background, in industry and academia, gives her a double competence that she puts at the service of research and teaching in data science.
Director of research at the CNRS, Sébastien Descotes-Genon did his PhD at the Orsay Institute of Nuclear Physics (CNRS-INP3/Paris-Sud) and a post-doctorate at the University of Southampton (UK), after studying at the Ecole Polytechnique. He is currently working at the Laboratoire de Physique Théorique d'Orsay (CNRS-INP/Paris-Sud).
Zakia Benjelloun-Touimi is Head of Department at IFP Energies Nouvelles and Project Manager @IFPEN.
Nicolas Soulié is a lecturer in digital economics at Institut Mines-Télécom Business School. He holds a PhD in economics from the University Toulouse 1 - Capitole. His work focuses on personal data and online privacy issues on social networks (discrimination, targeting, etc.), and on the impact of Information Technologies (smartphone, application, etc.) on individuals' mobility (decision, well-being, etc.).
Sophie Schbath received her PhD in Statistics from the University of Paris V on October 25, 1995. She did her thesis at the Biometrics laboratory of INRA (Institut National de la Recherche Agronomique) in Jouy-en-Josas, where she obtained a permanent research position in August 1996. In 1996, she did a one-year post-doctoral fellowship in Los Angeles, in the team of Simon Tavaré and Michael Waterman. In 2000, she joined the new multidisciplinary laboratory MIG (Mathematics, Informatics & Genome) at INRA-Jouy and she defended her habilitation on September 22, 2003. Sophie Schbath was president of the French Bioinformatics Society (300 members) from 2010 to 2016 and she co-directed the French Research Group "Molecular Bioinformatics" (1000 members) from 2006 to 2014.
She is now a research director at INRAE. Since 2015, she is the head of the MaIAGE laboratory. She is also the scientific leader of the bioinformatics facility Migale.
Her main interest is to develop statistical methods for genome and metagenome analysis. Her favorite objects are DNA motifs in all their forms: words, kmers, degenerate words, structured motifs, positional weight matrices, exact maximum matches, etc. She mainly studies their frequency but also their structure. She mainly studies their frequency but also their localization along the genome, by looking for co-localized motifs. She initiated and participated in the development of the R'MES software, which evaluates the statistical significance of the number of motifs in DNA sequences.
In recent years, she has been particularly interested in the study of microbial ecosystems in her laboratory.
Steve Oudot is Director of Research at the Inria Saclay Ile-de-France center and Professor at École Polytechnique. His main areas of interest are :
- topological data analysis ;
- persistence theory: algebra, topology, algorithms, statistics, machine learning ;
- learning of manifolds ;
- mesh generation.
Gaël Richard is the executive director of Hi! Paris and professor at Télécom Paris, Institut Polytechnique de Paris. His research work is at the heart of digitization and is dedicated to the analysis, transformation, understanding and automatic indexing of acoustic signals (including speech, music, environmental sounds) and to a lesser extent of heterogeneous and multimodal signals. In particular, he has developed several source separation methods for audio and music signals based on machine learning approaches.
David Filliat is a professor in the Computer Science and Systems Engineering Unit (U2IS) of ENSTA Paris and a member of the INRIA/ENSTA Paris FLOWERS team on developmental robotics. He is also the scientific director of the Interdisciplinary Center for Defense and Security Studies (CIEDS) at IP Paris.
His research focuses on robotics and more particularly on perception and learning issues. He seeks to develop methods to simplify and make more robust the use of robots and to increase their autonomy. He is particularly interested in :
- navigation, cartography, planning ;
- learning applied to multi-modal perception and reinforcement learning ;
- applications to mobile robots, drones and autonomous vehicles.