CV

 

Education

  • 1998-2001: ENSIIE - Computer Science School (Grandes Ecoles) http://www.ensiie.fr/
  • 2000-2001: Master Artificial Intelligence and Pattern Recognition (DEA IARFA), University Pierre et Marie Curie - Paris France.
  • December 2004: Phd In Computer Science, University Pierre et Marie Curie - Paris France. ''Apprentissage et Inférence Statistique dans les bases de documents semi-struturés"

Employment

  • 2004-2005: Assistant Professor (ATER), University Pierre et Marie Curie, Paris France
  • 2005-2014: Associate Professor (Maitre de conférences), University Pierre et Marie Curie, Paris France
  • 2014-now: Professor (Professeur des Universités),  University Pierre et Marie Curie, Paris France

Responsibilities

  • 2016-2017: Chargé de Mission Open Data/Open Science, UPMC
  • 2014-now: Co-head of the Data Science Master (http://dac.lip6.fr/master)
  • 2011-2014: Member o fthe Vivier d'experts, UPMC
  • 2009-2010: Member of the LIP6 Consdeil de laboiratoire

Events

  • 2016: Best Student Paper Award (Gabriella Contardo), ICONIP 2016
  • 2014 and 2016: Co-organizer of the Machine Learning and Information Retrieval Hackdays (during CORIA 2014, CORIA 2016, CAP 2014 and CAP 2016) http://hackday.lip6.fr
  • 2015: Industry Chair, Conference IEEE DSAA 2015
  • 2015: Co-president of the Scientific Comitee of Conference CAP 2015
  • 2013-2014: Two months spent at Yahoo! Research - Barcelona
  • 2013: Co-organizer of the Sequential Prediction workshop at ICML.
  • 2005-2010: Organizer of the XML Mining Challenge. Funded by the PASCAL and DELOS European Networks of Excellence. Participation of more than 40 international research teams.
  • 2009-2011: Délégation CNRS, Machine Learning for Social Networks and Sequential Desicion Models
  • 2010: One month spent in University of Siena (Marco Gori)
  • 2008-2009: CRCT, Exploring Machine Learning Techniques for Social Networks
  • 2007-2008: Co-Organizer of the Web Spam/Graph Labeling Challenge Challenge. . Collaboration with Yahoo!. Organization of a workshop during de ECML/PKDD
    2008.
  • 2006: Creation and release of the Wikipedia XML Corpus. Reference dataset for many academic competitions (INEX, CLEF, ...).

PHD Students

  •  Francis Maes: Learning in Markov Decision Processes for Structured Prediction - PhD 2009 - Now R&D Head at D/Labs
  •  Sheng Gao: Link Prediction with Latent Factors Models - PhD 2012 - Now Associate Professor at Beijing University of Posts and Telecommunications
  • Yann Jacob: Regularized Models for Labelling Heterogeneous Multi-Relationnal Social Networks - PhD  june 2013 - Now Data Scientist at Iraiser.io
  • Gabriel Arnold-Dulac: Sequential Methods for Classication - PhD  december 2013 - Now working at Google DeepMind
  • Maria Laura Maag: Apprentissage pour l'anonymisation de grans graphes dynamiques - thèse CIFRE Alcatel - PhD  june 2015 - Still at Alcatel
  • Gabriella Contardo: Online Budgeted Learning -PhD  march 2017.
  • Ali Ziat: Spatio-Temporal Deep Neural Networks (CIFRE with VEDECOM) - September 2017
  • Nassim Aklil: Budgeted Learning for Robots (with Mehdi Khamassi) - June 2017
  • Aurélia Leon: Machine Learning for Sequential Interactive Models - 2018
  • Mickael Chen: Generative models for Multi-views - 2019
  • Edouard Delasalles: Sequential Models - 2019

 Participation in PhD committees

Examinateur
    • Robin Allesiardo, 2016, Bandits Manchots sur Flux de Données Non Stationnaires
    • Tsirizo RABENORO, 2015, Outils statistiques de traitement d’indicateurs pour le diagnostic et le pronostic des moteurs d’avion
    • Mohamed EL MAHRSI, 2013, Analyse et fouille de données de trajectoires d’objets
    • Cedric Lagnier, 2013, Diffusion de l’information dans les réseaux sociaux
    • Laurent Boyer, 2011, Apprentissage probabiliste de similarités d'édition
    • Matthieu Durut, 2011, Algorithmes de Classification répartis sur le cloud
    • Alfonso Romero, 2009, Document Classification Models Based On Bayesian Networks
Rapporteur
      • Alberto GARCÍA-DURÁN, 2016, Learning representations in multi-relational graphs : algorithms and applications
      • Timothé Collet, 2016, Optimism in Active Learning
      • Maria-Irina Nicolae, 2016, Learning Similarities for Linear Classification:
        Theoretical Foundations and Algorithms
      • Djalel BENBOUZID, 2014, Sequential prediction for budgeted learning : Application to trigger design
      • Bilal Piot, 2014, Apprentissage Hors-Ligne avec Démonstrations Expertes
      • Julien Becker, 2014, Protein Structural Annotation: Multi-task learning and feature selection
      • Olivier Nicol, 2014, Data Driven Evaluation of Contextual Bandits

Participation in HDR committees

      • Albert Bifet, 2016, Big Data Stream Mining, Large Scale Real-Time Analytics (Examinateur)

Research Projects

Participation in academic projects

  • Projet ANR Marmota - 2005...2008 - MAchine learning pRobabilistic MOdels Tree lAnguages (Participant) -- Partenaires : Mostrare (INRIA LNE), BDAA (LIF - Marseille), Laboratoire Huber Curien (Saint Etienne), LIP6 (Paris)
  • Projet ANR Lampada - 2009...2014 - Learning Algorithms, Models an sPArse representations for structured DAta (Responsable Scientifique - LIP6) - Partenaires : Mostrare (INRIA LNE), SequeL (INRIAL LNE), BDAA (LIF - Marseille), Laboratoire Huber Curien (Saint Etienne), LIP6 (Paris)
  • Projet DIM/DIGITEO REMI - 2011..2014 - RElational data based Machines for Image annotation (Responsable Scientifique - LIP6) -- Partenaires : Telecom ParisTech (Paris), LIP6 (Paris)
  • Projet ANR Blanc MLVIS - 2012-2015 - Machine Learning for visual annotations in large social networks (Responsable Scientifique - LIP6) -- Partenaires : Telecom ParisTech (Paris), LIP6 (Paris)
  • Projet LABEX SMART OnBul - 2013 - 2016 - Online Budgeted Learning (Porteur du projet) -- Partenaires : ISIR (Paris), LIP6 (Paris)
  • Projet Institut de la Santé (IUIS - UPMC) APTITUDE - 2016 -  Deep LEarning pour l'aide à la chirurgie de la cataracte (Porteur) -- Partenaires: LIP6 (Paris) et Institut de la Vision (Paris)
  • Projet ANR Deep In France - 2016 - 2020

Academic and Industrial Projects

  •  Projet ANR ATASH - 2005...2008 - Machine Learning for Documents Transformations - (Responsable Scientifique - LIP6) – Partenaires : Xerox R&D (Grenoble), Mostrare (INRIA LNE), LIP6
  • Projet ANR MADSPAM - 2008...2011 - Automatic SPAMdexing detection in large Information Networks (Responsable Scientifique - LIP6) – Partenaires : BlogSpirit (Malako ), Orange R&D (Issy les Moulineaux), LIP6 (Paris)
  • Projet ANR/DGCIS ExDeus/Cèdres 2009...2012 - Social Networks Analysis (Responsable Scientifique - LIP6) - Partenaires : KXEN, LIPN (University Paris 13), Skyrock, AF83, Heaven, Mondomix, LIP6
  • Projet Systematic Vigies 2008...2011 - Visualization and Electronic Interceptions (Responsable Scientifique - LIP6) – Partenaires : Alcatel-Lucent, France Telecom, Onera, Vecsys, LIP6
  • Projet FUI DIFAC 2010...2013 - Information Spreading and Opinion Leader Detection in Social Networks (Responsable Scientifique - LIP6) -– Partenaires : BlogSpirit (Malako ), Orange R&D (Issy les Moulineaux), LIP6 (Paris)
  • Projet ANR LIVES 2016 - 2020 - Multi View Learning
  • Projet ANR PAMELA 2016 - 2020 - Decentralized Privacy-safe Machine Learning -- Partenaires: LIP6, INRIA Lille, INRIA Rennes, Mediego, SNIPS

Public Softwares

 

 Teaching Activities

  • 2014- now: Co Head of the Data Science Master (http://dac.lip6.fr/master)
  • 2014-2016: Responsible of the Business Intelligence Course (M1)
  • 2011-2016: Responsible of the 'Advanced Web Technologies' Course (L3)
  • 2012-now: Co-responsible of the 'Introduction to Artificial Intelligence (and Data Science)' Course (L3)
  • 2012-2014: Co Head of the EDOW speciality in the Computer Science Master
  • (approx...) 2010-2012: Responsible of the Object Oriented Progamming Course - Master SDI
  • (approx...) 2006-2011: Responsible of the 'Programmig Project' Course (L2)

Also Lecturer in the Artificial Intelligence Speciality at ENSIIE during 8 years

 

 Invited Talks

  •  Le controle Parental Sur Internet, Qu'en savez-vous vraiment ? Conference pour les curieux, 2006
  • XML Structure Matching, workshop Processing Text-Technological Resources, Germany, 2008
  • Apprentissage et inference sur les reseaux sociaux. Exemples pour l'analyse de textes, French Society of Statistics, 2010
  • Incremental Models for Text Classi cation, University of Siena, 2010
  • Classi cation of Multi-Relationnal Social Networks, University of Siena, 2010
  • Learning Propagation Schemes in Multi-Graphs, Complex Networks, UPMC, 2011
  • Learning Propagation Schemes in Multi-Graphs, Telecom ParisTech, BILAB Team, 2011
  • Classi cation with Reinforcement Learning, University of Liege, 2011
  • Learning with Relational Data : Sequential Models and Propagation Models for Structured Classi cation and Labeling, Universite Paris 5, 2013
  • Learning Graph Embeddings for Heterogeneous networks classification and Information Diffusion, Yahoo! Barcelona, 2013
  • Apprentissage de représentation pour la diffusion d’Information dans les réseaux sociaux, GRD ISIS 2013
  • Methodes d'apprentissage sequentiel et methodes de propagation pour la classi cation, la transformation et l'etiquetage de donnees complexes, Universite Paris 7,2013
  • Classi cation with Reinforcement Learning,EPAT 2014 (Ecole d'été en apprentissage)
  • Big Data, Data Science, Enseignement et Recherche, Séminaire DEP 2014 (Data Quality)
  • Apprentissage de représentation pour la diffusion d’Information dans les réseaux sociaux, Séminaire de la DGA 2015
  • Budgeted Sequential Learning for Data Processing, Criteo , 2015
  • Reinforcement Learning for Data Processing and Deep Reinforcement Learning, Machine Learning Meetup, Paris 2015
  • Budgeted Sequential Models for Data Acquisition and Processing, WOS, Rennes 2015
  • Machine Learning, Deep Learning (Données de perception et Automobile) - Séminaire Intelligence Artificielle - Renault 2016
  • Sequential Budgeted Learning - Facebook FAIR (Paris) - 2016
  • Deep Learning, Roundtable, Conference CESA 2016
  • TEDX La Rochelle, Apprentissage Machine