I am a tenured researcher at Inria, where I am part of the Magnet Team (MAchine learninG in information NETworks) and affiliated with CRIStAL (UMR CNRS 9189), a research center of the University of Lille. I am also an invited associate professor at Télécom Paris. I obtained the French habilitation thesis (HDR) in 2021.
Prior to joining Inria, I was a postdoctoral researcher at the University of Southern California (working with Fei Sha) and then at Télécom Paris (working with Stéphan Clémençon). I obtained my Ph.D. from the University of Saint-Etienne in 2012 under the supervision of Marc Sebban and Amaury Habrard.
My main line of research is in the theory and algorithms of machine learning. I am particularly interested in designing large-scale learning algorithms that provably achieve good trade-offs between statistical performance and other key criteria such as computational complexity, communication, privacy and fairness.
My current research focus includes:
- distributed / federated / decentralized learning algorithms
- privacy-preserving machine learning
- representation learning and distance metric learning
- graph-based methods
- optimization for machine learning
- statistical learning theory
- fairness in machine learning
- applications to NLP and speech recognition