Research Projects
Ongoing
- PRIDE (Privacy-Preserving Decentralized Machine Learning), 2021-.
Funded by the French National Research Agency (ANR). Role: Principal Investigator. - FLAMED (Federated Learning and Analytics on Medical Data), 2020-.
Funded by Inria. Role: Principal Investigator. - SLANT (Spin and Bias in Language Analyzed in News and Texts), 2019-.
Funded by the French National Research Agency (ANR). Role: Project Member. - Comprise (Cost-effective, Multilingual, Privacy-driven voice-enabled services), 2018-.
Funded by the H2020-ICT-2018-2020. Role: Project Member. - DEEP-PRIVACY (Distributed, Personalized, Privacy-Preserving Learning for Speech Processing), 2018-.
Funded by the French National Research Agency (ANR). Role: Project Member. - PAD-ML (Privacy-Aware Distributed Machine Learning), 2018-.
INRIA Associate Team with the Privacy-preserving data analysis group at Alan Turing Institute. Role: Principal Investigator. - PAMELA (Personalized and decentrAlized MachinE Learning under constrAints), 2016-.
Funded by the French National Research Agency (ANR). Role: Project Member. - GRASP (GRAph-based machine learning for linguistic Structure Prediction), 2016-.
Funded by the French National Research Agency (ANR). Role: Project Member. - LEGO (LEarning GOod representations for natural language processing), 2016-.
INRIA Associate Team with Fei Sha's group at USC. Role: Principal Investigator.
Past
- SkMetricLearn (Scikit-learn Integrated Metric Learning), 2017-2019.
Software development project funded by INRIA. Role: Principal Investigator. - ERC Proof of Concept SOM (Statistical modeling for Optimization Mobility), 2016-2018.
Funded by ERC. Role: Project Member. - Machine Learning for Big Data, 2014-2015.
Funded by Télécom Paris and several companies. Role: Project Member. - BABEL, 2013-2014.
Funded by IARPA. Role: Project Member. - LAMPADA (Learning Algorithms, Models and sPArse representations for structured DAta), 2009-2013.
Funded by the French National Research Agency (ANR). Role: Project Member. - PASCAL2 Network of Excellence, 2009-2013.
Funded by the European Commission. Role: Project Member.
Scientific Events
Organizer
- Privacy Preserving Machine Learning
Workshop at CCS 2021, Seoul (South Korea), November 2021
Co-organized with James Bell, Adrià Gascón, Olya Ohrimenko, Mariana Raykova, Phillipp Schoppmann, Carmela Troncoso. - Privacy Preserving Machine Learning
Workshop at NeurIPS 2020, Virtual event, December 2020
Co-organized with Borja Balle, James Bell, Kamalika Chaudhuri, Adrià Gascón, Antti Honkela, Antti Koskela, Casey Meehan, Olya Ohrimenko, Mijung Park, Mariana Raykova, Mary Anne Smart, Yu-Xiang Wang and Adrian Weller. - Federated Learning One World Seminar (FLOW)
Online seminar on federated learning with 800+ registered attendees, started in May 2020
Co-organized with Peter Richtárik, Virginia Smith and Dan Alistarh. - French Workshop on Privacy Protection (APVP 2019)
10th edition, Baie de Somme (France), July 2019
Co-organized with Pierre Bourhis, Walter Rudametkin and Marc Tommasi. - Privacy Preserving Machine Learning
Workshop at NeurIPS 2018, Montreal (Canada), December 2018
Co-organized with Adrià Gascón, Niki Kilbertus, Olya Ohrimenko, Mariana Raykova and Adrian Weller - Workshop on Privacy-Aware Distributed Machine Learning
Workshop at INRIA, Lille (France), October 2018
Co-organized with Adrià Gascón - Workshop on Decentralized Machine Learning, Optimization and Privacy
Workshop at INRIA, Lille (France), September 2017
Co-organized with Morten Dahl, Sébastien Gambs, George Giakkoupis and Joseph Salmon - Private Multi-Party Machine Learning
Workshop at NIPS 2016, Barcelona (Spain), December 2016
Co-organized with Borja Balle, David Evans and Adrià Gascón - Similarity and Distance Metric Learning with Applications to Computer Vision
Tutorial at ECML/PKDD 2015, Porto (Portugal), September 2015
Co-organized with Matthieu Cord
Area Chair
PC Member
- ICML 2015 2016 2017 2018
- NIPS (now NeurIPS) 2016 2017 2018 2019
- AISTATS 2017 2018 2019 2020 2021
- ECML/PKDD 2011 2013 2014
- IJCAI 2013 2016
- MOD 2015 2016 2017
- CAp 2018 2019 2020 2021
- Privacy in Machine Learning and Artificial Intelligence workshop at ICML & IJCAI 2018
- Privacy-Preserving Machine Learning workshop at CSS 2019
- Privacy in Machine Learning workshop at NeurIPS 2019
- Federated Learning workshop at NeurIPS 2019
- Workshop on Privacy-Preserving Artificial Intelligence at AAAI 2020
- Towards Trustworthy ML: Rethinking Security and Privacy for ML at ICLR 2020
- International Workshop on Federated Learning for User Privacy and Data Confidentiality at IJCAI 2020
- Workshop on Privacy-Preserving Artificial Intelligence at AAAI 2021
- International Workshop on Federated Learning for User Privacy and Data Confidentiality at ICML 2021
Supervision
We are always looking for good students, postdocs and engineers! Check out this page for information on some open positions in the team.
Postdocs
- Mohamed Maouche (2019-, co-supervised with M. Tommasi and E. Vincent)
- Melissa Ailem (2017-2018, Inria@SiliconValley fellowship, co-supervised with P. Denis, F. Sha and M. Tommasi)
PhD students
- Mahsa Asadi (2018-, co-supervised with M. Tommasi)
- Brij Mohan Lal Srivastava (2018-, co-supervised with M. Tommasi and E. Vincent)
- Mariana Vargas Vieyra (2018-, co-supervised with P. Denis)
- Robin Vogel (2017-2020, CIFRE thesis with IDEMIA, co-supervised with S. Clémençon and A. Sabourin)
Engineers
- William de Vazelhes (2017-2019, working on metric-learn)
Visiting PhD students
- Ali Shahin Shamsabadi (2020-2021, Queen Mary University of London)
- Tejas Kulkarni (2018, University of Warwick)
- Valentina Zantedeschi (2018, University of Saint-Etienne)
Master interns
- 2020: Edwige Cyffers (ENS Lyon)
- 2019: Paul Mangold (ENS Lyon)
- 2018: Antoine Capriski (University of Lille), Arthur d'Azémar (University of Lille)
- 2016: Thibault Liétard (ENS Rennes), Paul Vanhaesebrouck (École Polytechnique - best internship award), Pierre Dellenbach (École Polytechnique), Robin Vogel (ENSAE)
- 2015: Maxime Flauder (ENS Paris)