Projects

  • MELISSA: MEthodological contributions in statistical Learning InSpired by SurfAce engineering. ANR PRCE 2024-2029
  • ADADA: Adaptive Datasets for Enhancing Reasoning in Large Language Models ANR JCJC Damien Siléo 2024-2028
  • REDEEM:REsilient, DEcentralized and privacy-prEserving Machine learning.  PEPR IA. 2023-2027
  • FaCTor: Fairness Constraints and Guarantees for Trustworthy Machine Learning, ANR JCJC Michael Perrot  2023-2027.
  • FLUTE: Federate Learning and mUlti-party computation Techniques for prostatE cancer (HORIZON-HLTH-2022-IND-13-02) 2023-2026
  • FedMalin: FEDerated MAchine Learning over the INternet. INRIA Defi, 2022-2026.
  • TRUMPET: TRUstworthy Multi-site Privacy Enhancing Technologies. 2022-2025
  • SSF-ML-DH Apprentissage automatique sécurisé, sûr et équitable pour les applications en santé, PEPR Santé numérique.
  • IPop, Projet interdisciplinaire sur la protection des données personnelles, PEPR Cybersécurité 2022-2028.
  • CAPSUL, CAmpus Participatif en Santé numérique du site Universitaire de Lille Appel à Manifestation d’Intérêt « Compétences et Métiers d’Avenir » Santé numérique, PIA4. 2022-2027.
  • PRIDE: Privacy-Preserving Decentralized Machine Learning ANR, 2020-2024
  • PMR: Privacy-preserving methods for Medical Research, ANR, 2021-2025
  • IMPRESS: Improving embeddings with semantic knowledge, Inria-DFKI 2020-2024
  • SLANT: Spin and bias in language analyzed in news and texts, ANR PRCI 2020-2024
  • COMPRISE: Cost-effective, Multilingual, Privacy-driven voice-enabled Services, H2020 ICT, 18-21
  • ANR DEEP-Privacy:  Distributed, Personalized, Privacy-Preserving Learning for Speech Processing, ANR, 19-23
  • PAMELA: Personalized and decentrAlized MachinE Learning under constrAints, ANR, 16-20
  • GRASP: GRAph-based machine learning for linguistic Structure Prediction, ANR JCJC, 16-20
  • REM: Analysis of English modal constructions, ANR, 16-20
  • PAD-ML:  Privacy-Aware Distributed Machine Learning, North-European Associate Team with the PPDA team at the Alan Turing Institute, 18-19
  • HyAIAI: Hybrid Approaches for Interpretable AI, INRIA 2019-2022
  • MUST: Méthodologie d’exploitation des données d’usage des véhicules et d’identification de nouveaux  services pour les usagers et les territoires, ADEME, 17-19
  • LEGO: LEarning GOod representations for natural language processing, Inria International team with USC, 17-18 et 19-20
  • MyLocalInfo: Open API for privacy-friendly collaborative computing in the internet of things, CPER DATA, 18-21
  • SOM: Statistical modeling for Optimization Mobility, ERC PoC, 16-17