2023-2026: I head the ANR project ``Bandits improve patient follow-up'' (BIP-UP). This project is based on a collaboration with Professor François Pattou from Unviersité de Lille, CHU de Lille, INSERM, a follow-up of the B4H project (see below).
2023-2026: collaboration with Saint-Gobain Research based on the PhD of Yann Berthelot. Topic: Model-based reinforcement learning.
2021-2024: I am co-head of an AI chair with O-A. Maillard, dedicated to reinforcement learning. This chair is managed by I-SiTE ULNE, and funded by Métropole Européenne de Lille, ANR, Université de Lille, and Inria.
February 2019: starting a collaboration with Romain Gautron (PhD student at CIRAD) on using sequential decision making under uncertainty for sustainable development in agriculture in developing countries. Among other results, this work led to the gym-DSSAT which is a state-of-the-art crop management simulator following the gym API, to be controlled by RL. More information through this link.
On-going collaborations with PhD Students:
Yann Bethelot, CIFRE grant with Saint-Gobain Research, since May 2023.
Matheus Medeiros Centa, AI Ph.D. grant, since Nov. 2021.
Hector Kohler, funded by an AI Ph.D. grant, since Oct. 2022.
post-docs:
Alena Shilova, IPL HPC meets Big Data, since Jan. 2022,
Responsabilities
Research management (on-going) :
Head of Scool, Inria team-project (Nov. 1st 2020-), joint group with UMR CNRS CRIStAL.
Member of the Project Committee Board (bureau du comité des projets) of Inria Lille since 2015.
Member of the Project Committee (comité des projets) of Inria Lille Nord Europe Research Center since 2006.
Member of the scientific committee data science and models of IRD since Sep. 2020.
Scientific coordinator of the CPER project CornelIA.
Member of the scientific committee of CRIStAL (2015-Jan. 2019).
Head of the LIFL at Université de Lille 3 (2005-2007, 9/2013-12/2014).
Founder and director of the Laboratoire d'Informatique du Littoral at Université du Littoral Côte d'Opale, Calais, France (1994-1/2003).
Head of Alg research group at LIL (1994-1/2003).
Cursus:
Head of the master in « machine learning & Data science » (closed)
Head of the master Mathématiques et Informatique Appliquées aux Sciences Humaines et Sociales (MIASHS), Université de Lille 3 (2005-2007)
Head of the DEA « Modélisation et Simulation des Systèmes Complexes » (computer science and signal processing diploma), Université du Littoral Côte d'Opale (2002-2003)
Participation to conference organization
Organization of scientific events:
co-organizer of the 1st summer school entirely dedicated to RL and bandits: Reinforcement Learning Summer Scool in Villeneuve d'Ascq, 1-12 July 2019.
2021-2022: Stic AMSud EMISTRAL project, with Inria Chile (coordinator), Universidad de la República, Uruguay, Universidade Federal do Rio Grande do Norte, Brazil.
2019-2023: project ``Bandits for Health'' (B4H) has been accepted by i-iste ULNE. I am co-PI of this project. Starting a collaboration with François Pattou and his group at CHU Lille, Inserm, and Université de Lille.
2019-2023: Participation to Inria Project Lab: HY_AIAI.
2018-2022: collaboration with Christian Duriez, Defrost, on the use of reinforcement learning to control soft robots (2018-2022). Pierre Schegg's Ph.D. Among other results, this work led to SofaGym which is a soft robots simulator that can be controlled by RL algorithms.
2018-2023: Participation to Inria Project Lab: HPC Big-Data.
2019-2020, collaboration with Tanguy Levent and Yvan Bonnassieux, PICM laboratory at École Polytechnique, on smartgrid control with reinforcement learning. TL defended his PhD in Dec. 2020.
Dec. 2018-2020: Project RAID has been accepted for funding by Région Hauts-de-France. RAID aims at investigating the use of deep learning in radiology. Project done in collaboration with radiologists at CHU Lille (2019-2020). Publication. PI.
Feb-Sep 2019: advising start-up sharemyspace.
Critéo, on computational advertizing, through a PhD student grant (CIFRE), Oct. 2017-2019
Renault, on the autonomous vehicle, through a PhD student grant (CIFRE), Oct. 2017-2020
Work with Sidexa, on deep learning and vision (2017-2018)
I was a member of the late Pascal network of excellence
the Ubiquitous Virtual Seller (2009-2011), from the ``Pôle de Compétitivité Industries du Commerce'', Région Nord-Pas de Calais/FEDER funding
the ANR EXPLORA: EXPLOration - EXPLOitation for efficient Resource Allocation. Applications to optimization, control, learning, and games. (2009-2011)
contract with Addressing Business, Lille (2010-2011)
research contracts with Orange Labs:
contract in 2009 on ad display on websites,
contract 2009-2012 on sequential machine learning,
contract 2014-2017 on sequential machine learning,
a PhD student grant (CIFRE), with Dr. Tanguy Urvoy, 2014-2017.
1994-2005: collaboration with Jean-Claude Darcheville, professor in psychology at Université de Lille 3, and his group. The topic was: animal behavior, dynamical systems, and reinforcement learning. Fundings:
2004-2006: the DYNAPP (= Learning Dynamics) project.
2000-2003: ACI Cognitique project.
1997-2000: PhD grant (Samuel Delepoulle).
the ABC (Behavior-based animations) Robea project, in 2003, about animating virtual entites using reinforcement learning.
looking for the late « Groupe
Apprentissage par REnforcement » (GARE = Reinforcement Learning
Group) in the early 2000's: the webpage is gone!
See Scool for my current activities in reinforcement learning.
Skills
I got acquainted with computer science in the early 1980's at the
very exciting period of micro-computers. I learnt some of the most
important things about programming with a
simple TI 57
programmable calculator; then, I became proficient with programming
with an Oric
1 micro-computer. Then I was trained as a computer scientist in
the 1980's. Since then, I learnt by myself a lot of maths, and statistics.
Programming languages:
high proficiency: C,
decent proficiency: R,
doing my best (mostly because this is used in teaching, big sigh): python,
former high proficiency: various lisp dialects (Le_Lisp 15 for those who see what I mean), Smalltalk, Pascal, Ada, Prolog, various assembly languages and machine code (6502, 8080, 8088, 8086, 68000, Z80, Cray Y-MP aka CAL),
older stuffs: Cobol, Pl/1, Fortran, Forth.
OS: Unix, Multics
Compiler design, and code generation
...
I've been fascinated by artificial intelligence since my earliest contacts with programmable devices. Around 1981, I tried to program my TI 58 to solve the Rubik's cube, and to play Yams. Then, I discovered AI languages such as Lisp, Prolog, and Smalltalk. I implemented a subset of a Le_Lisp interpretor on my Oric-1, hand-coded in 6502 code machine (readers who are less than 30y old can probably not even understand what I mean!). As an undergrad, I tried (and failed!) to implement a Prolog engine. My first official AI related project during my studies has been related to Smalltalk. Then, I did my PhD which was not AI related. Afterwards, I got interested in neural networks, and genetic algorithms. Then, I eventually touched upon machine learning around the end of the 1990's, in particular reinforcement learning, a topic that has remained my research field since then.