This page lists and links to various activities.

• Projects I have been, or am, involved in.
• Various responsabilities
• Participation to program committees, and/or organization of conferences
• Skills
• Software development

Projects

On-going academic collaborations and projects:

• 2021-2024: I am co-head of an AI chair with O-A. Maillard, dedicated to reinforcement learning.
• 2021-2022: Stic AMSud EMISTRAL project, with Inria Chile (coordinator), Universidad de la República, Uruguay, Universidade Federal do Rio Grande do Norte, Brazil.
• 2020-2023: Chist-ERA ``Causal eXplanations in Reinforcement Learning'' accepted, with University of Sheffield (coordinator), and University of Vienna.
• 2020-2024: Inria associate team Data Collection for Smart Crop Management has been accepted for 3 years. I am coordinator.
• 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. More information through this link.
• 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. More information through this link (in French only).
• 2019-2023: Participation to Inria Project Lab: HY_AIAI.
• since Fall 2018: starting collaborations with Christian Duriez, Defrost, on the use of reinforcement learning to control soft robots (2018-2022). Pierre Schegg's Ph.D.
• 2018-2023: Participation to Inria Project Lab: HPC Big-Data.

On-going collaborations with PhD Students:

• Matheus Medeiros Centa, since Nov. 2021.
• Johan Ferret, CIFRE with Google, since Dec. 2019.
• Romain Gautron, funded by CIRAD and CIAT/CGIAR (supervised by Marc Corbeels, CIRAD), since Spring 2019.
• Nathan Grinsztajn, funded by École Polytechnique, since Oct. 2019.
• Léonard Hussenot, CIFRE with Google, since March 2020.
• Patrick Saux, funded by the B4H project, since Nov. 2020
• Pierre Schegg, Defrost, funded by Robocath (supervised by Ch. Duriez and J. Desquidt of team Defrost), since Jan. 2019.

• Mohit Mittal, IPL HYAIAI, since Nov. 2020
• Alena Shilova, IPL HPC meets Big Data, since Jan. 2022
• Riccardo della Vecchia, CausalXRL, since Sep. 2021

• Tomy Soumphonphakdy
• Julien Teigny

Responsabilities

Research management (on-going) :

• Head of Scool, Inria team-project (Nov. 1st 2020-), joint group with UMR CNRS CRIStAL.
• Délégué scientifique adjoint (deputy scientific head), Inria Lille, since 2016.
• Member of the Inria commission d'évaluation (evaluation committee, CE) since 2016.
• 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 the IRD since Sep. 2020.

In the past:

• April 2006-Oct. 2020: Head of SequeL research group at Inria, joint with CRIStAL (CNRS, Université de Lille).
• Head of the ``Data Intelligence'' thematic group within CRIStAL (2013-Jan. 2019).
• 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.
  • co-organizer of the 14^th European Workshop on Reinforcement Learning (EWRL), Oct 1-3 2018, Lille.
  • co-organizer of Big Data : Modelisation, Estimation and Selection, June 2016
  • Local organization chair for ICML 2015, Lille
  • PC co-chair CAP, Villeneuve d'Ascq, 3-5 juillet 2013
  • co-organizer Challenge Exploration/Exploitation 2012 based on data provided by Yahoo!,
    and the accompanying workshop on new Challenges for Exploration & Exploitation.
  • co-organizer of the 8^th European Workshop on Reinforcement Learning, June-July 2008, Villeneuve d'Ascq, Post-proceedings in the Springer, LNAI series, volume 5323.
  • co-organizer of the workshop Kernel Machines and Reinforcement Learning during ICML, Pittsburgh, June 29^th, 2006
  • workshops chairman of 2006 (janvier) à Villeneuve d'Ascq
  • main organizer of the journées PDMIA, juin 2005 à Villeneuve d'Ascq (french speaking days on Markov Decision Processes and Reinforcement Learning)
  • co-organizer of the series of meetings « Systèmes complexes et SHS », Université de Lille 3, 2004-2007
  • local organization of Artificial Evolution 1999, Dunkerque
• PC, and reviewing: (I have declined many invitations since 2018 (like ICML, ICLR): at some point, it was taking me too much time)
  • 2022: SPC AAAI, PC: IJCAI, ECML.
  • 2021: PC AAAI, ECML/PKDD EGC.
  • 2020: SPC ECML; PC AAAI, IJCAI, EGC, JDS; reviewer: AI & Stats, NIPS.
  • 2019: PC IJCAI, AAAI, ECML, AIMLAI-XKDD workshop at ECML/PKDD 2019, EGC, journées de la Société Francophone de Classification; reviewer: ICML, AI & Stats.
  • 2018: SPC IJCAI; PC ICML, ECML, EWRL, EGC, JFPDA, journées de la Société Francophone de Classification; reviewer: AI & Stats, NIPS.
  • 2017: PC AI & Stats, ECML, 1st Workshop on Transfer in Reinforcement Learning (TiRL), EGC, JFPDA, journées de la Société Francophone de Classification; reviewer: AI & Stats, NIPS.
  • 2016: PC ECML, ADPRL, ICPRAM, EGC, JFPDA, journées de la Société Francophone de Classification; reviewer: NIPS.
  • 2015: PC IJCAI Machine learning track, ADPRL, ICPRAM, EGC, JFPDA, journées de la Société Francophone de Classification; reviewer: ICML, NIPS.
  • 2014: PC ADPRL, ICPRAM, EGC, JFPDA; reviewer: ICML, NIPS.
  • 2013: PC ICML, Prediction with Sequential Models workshop at ICML, ADPRL, ICPRAM, EGC, JFPDA; reviewer: NIPS.
  • 2012: PC ICML, EWRL, ICPRAM, EGC, JFPDA; reviewer: NIPS.
  • 2011: PC ADPRL, EGC, JFPDA; reviewer: NIPS.
  • 2010: PC ICML, EGC, JFPDA; reviewer: NIPS.
  • 2009: PC ECML, IJCAI, ADPRL, EGC.
  • 2008: PC ECML, EGC.
  • 2007: PC Artificial Evolution, ADPRL.
  • 2006: PC JFPDA.
  • 2005: PC Artificial Evolution.
  • 2003: PC Artificial Evolution.
  • 2001: PC Artificial Evolution.
  • 1999: PC Artificial Evolution.

(some) Older projects:

• 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, now with Total.
• 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). 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)
• the ANR-Lampada (2010-2014)
• the FUI Hermès project (2013-2016)
• collaboration with Squoring Technologies (2010-2014), Toulouse
• 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)
• contracts of research 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
• the DYNAPP (= Learning Dynamics) project, 2004-2006
• the ABC (Behavior-based animations) Robea project, in 2003
• the ACI Cognitique project, 2000-2003
• looking for the late « Groupe Apprentissage par REnforcement » (GARE = Reinforcement Learning Group): 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 whole lot of maths, and statistics.

• Programming languages:
  • high proficiency: C
  • decent proficiency: R, 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 (those 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 AI related personnal work 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.

Software

Please, check this page.

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