Frédéric Chazal is a Directeur de Recherche (senior researcher) at Inria Saclay - Ile-de-France and Director of the DATAIA Paris-Saclay Institute. After a PhD in pure mathematics, he oriented his research to computational geometry and topology. He is now leading the DataShape team (Inria Saclay - Ile-de-France), a group working on Topological Data Analysis (TDA), a recent fast growing field at the crossing of mathematics, statistics, machine learning and computer science. Frédéric’s contributions to the field go from fundamental mathematical aspects to algorithmic and applied problems. He published more than 80 papers in major computer sciences conferences and mathematics journals, he co-authored 2 reference books and 3 patents. He is also an associate editor of 4 international journals: Discrete and Computational Geometry (Springer), SIAM Journal on Imaging Science, Graphical Models (Elsevier), Journal of Applied and Computational Topology (Springer).
During the last few years Frédéric has been heading several national and international research projects on geometric and topological methods in statistics and machine learning. He is also the scientific head of joint industrial research projects between Inria and several companies such as Fujitsu (TDA, Machine Learning and explainable AI) or the French SME Sysnav.
Frédéric Pascal is a full Professor in the L2S laboratory at CentraleSupélec. From Jan. 2017, he is the head of the “Signals and Statistics” group of L2S. He is also the coordinator of the data science activities at CentraleSupélec and the chair holder of the Givaudan chair on data sciences. From Sept. 2017, he is in the Executive Committee of the DATAIA institute as the Program Coordinator. From 2015 to 2017, Frederic Pascal was the Chair of the EURASIP SAT in Theoretical and Methodological Trends in Signal Processing (TMTSP) and he is a member of the IEEE Signal Processing Society SAM technical committee (Jan. 2015-present). Frederic Pascal serves as an Associate Editor for the IEEE Transactions on Signal Processing (2015-2018), for the EURASIP Journal on Advances in Signal Processing (2015-present) and for Elsevier Signal Processing (2018-present). His research interests contain estimation, detection and classification for statistical signal processing and applications in radar and image processing. He is the author / coauthor of more than one hundred papers in the top journals and conferences in Signal Processing, Image Processing and Statistics.
Sarah Cohen-Boulakia is a full Professor at the Laboratoire de Recherche en Informatique at Universite Paris-Sud. She has been working for fifteen years with multi-disciplinary groups involving computer scientists and biologists of various domains. She spent two-years as a postdoctoral researcher at the University of Pennsylvania, USA and 18 months at the Institute of Computational Biology (IBC) of Montpellier in Inria groups. Locally she is member of the Center for Data Science steering committee. S. Cohen-Boulakia’s research interests include provenance and design of scientific workflows, reproducibility of scientific experiments, integration, querying and ranking in the context of biological and biomedical databases. She is actively involved in the CNRS GDR MaDICS on data sciences and takes the lead of the GDR in January 2020. She is strongly involved in teaching activities of the computer science department: Master of Computer Science, Master of Bioinformatics, Vice-President of the departement in charge of the coordination of the undergraduated program since 2017.
Alexandra Bensamoun is Professor of private law and criminal sciences (University Paris-Saclay - Center for studies and research in immaterial law CERDI ), IP / IT specialist. Appointed qualified personality at the Higher Council of Literary and Artistic Property (CSPLA), she conducted for the Ministry of Culture several reports, for example on the status of technical intermediaries of the Internet and the right of communication to the public. In charge of mission at the DATAIA Institute's board, she is very involved in the reflection and scientific research related to AI and has written several contributions on its regulation, particularly in terms of responsibility and ethics. She also co-chaired the "Legal Issues" section of the #FranceIA report (at the request of the Prime Minister, 2017).
Antoine Cornuéjols is a professor at AgroParisTech, head of the EKINOCS (Learning and Integration of Knowledge) team in the UMR AgroParisTech/INRAE MIA-Paris. His research focuses on learning from data flows, learning by transfer and supervised and unsupervised collaborative learning methods. He is co-author with Laurent Miclet and Vincent Barra of the book "Apprentissage Artificiel. Concepts and Algorithms. From Bayes and Humes to deep learning" (4th edition in 2021). He is also co-responsible for the H@rvest partnership chair on digital agriculture.
Claire Nédellec is a research director in computer science, head of the Bibliome team (INRAE Jouy-en-Josas and Université Paris-Saclay). After 10 years spent at the LRI (Université Paris-Saclay) as a thesis under the supervision of Yves Kodratoff, then as a teacher-researcher, she joined the MaIAGE unit at INRAE where she created the Bibliome team. Her research focuses on the extraction of information from texts in the field of life sciences and their formalisation through ontologies. She also contributes to the development of open text mining services for scientists within the framework of international and national projects. She coordinated the drafting of the CoSO (Committee for Open Science) recommendations on automatic document analysis (2019).
David Rousseau is a physicist, Director of Research at CNRS/IN2P3 in the IJCLab-Orsay laboratory at Paris Saclay University. He is a member of the ATLAS collaboration with the Large Hadron Collider at CERN, studying mainly the physics of the Higgs boson. He has a particular interest in the use of Artificial Intelligence in physics and sciences more generally, in particular substitution models, dimensionality reduction, classification in the presence of uncertainties. For this purpose he has organised two Kaggle challenges and is co-leader of the Interexperiment Machine Learning group at CERN, and co-leader of the Center for Data Science Paris Saclay.
Director of research at the CEA, François Terrier is in charge of the Artificial Intelligence programme at the CEA. After a PhD in AI and 10 years of R&D in the field, has conducted research on software engineering and trust systems. Author of more than 100 publications, he has been the CEA representative in the network of excellence on real-time systems led by Joseph Sifakis, and has been an actor for standardization on the subject at the OMG. Head of department from 2010 to 2020, he was in charge of developing activities on model-based engineering, 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 the blockchain. Thanks to its dual culture in AI and trust systems engineering, it has built the CEA's trust artificial intelligence axis that it pilots and deploys in different projects such as confiance.ai and the European network of excellence TAILOR.
Fatiha Saïs is a University Professor at Université Paris Saclay and a member of the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN) where she leads the LaHDAK (Large-scale Heterogeneous Data and Knowledge) team. Her research interests include: data linking and fusion in the Web of Data, error detection and fact validation in knowledge graphs, as well as the discovery of graph rules and patterns in graph data for data linking, link prediction, decision making, and explanation of causal relationships. Her work draws on techniques from several fields: knowledge representation and reasoning, data mining and machine learning. She is currently a member of the board of directors of the AFIA (Association Française pour l'Intelligence Artificielle) and an active member of the GDR MaDICS on data science and of the GDR IA (Aspects Formels et Algorithmiques de l'Intelligence Artificielle). Finally, in teaching at the University of Paris Saclay, Fatiha Saïs is co-responsible for the Computer Science mention of the GS ISN at the Master level, including 15 Master 1 and Master 2 courses, and she is co-responsible for the Data Science course.
Sylvain Chevallier is a professor at the University of Paris-Saclay and works in the Laboratoire Interdisciplinaire des Sciences du Numériques (LISN) on geometric methods for multivariate time series analysis and prediction, as well as for anomaly detection. He worked for 10 years at the Laboratoire d'Ingénierie des Systèmes de Versailles on assistance to disabled people, integrating brain interfaces in experimental applications and art-science collaboration. He is vice-president of the learned society CORTICO for the promotion of brain interfaces. He leads several open and citizen science projects to improve scientific reproducibility and facilitate the appropriation of brain-computer interfaces.
Emilie Chouzenoux received the engineering degree from Ecole Centrale, Nantes, France, in 2007, and the Ph.D. degree in signal processing from the Institut de Recherche en Communications et Cybernétique (IRCCyN, UMR CNRS 6597), Nantes, in 2010. Between 2011 and 2019, she was a Maître de conferences at the University of Paris-Est Marne-la-Vallée, Champs-sur-Marne, France (LIGM, UMR CNRS 8049). Since September 2019, she has been a Researcher at Inria Saclay, in CVN lab at CentraleSupélec, University Paris Saclay, France. She is an Associated Editor of SIAM Journal on Mathematics of Data Science and of SIAM Journal on Imaging Science. Since January 2020, she has been the principal investigator of a Starting Grant from the European Research Council. Her research interests are in large scale optimization algorithms for inverse problems and machine learning problems of image processing.