Since 2022, I am a Senior Research Scientist at the Criteo AI Lab in Paris.
Previously, I was a Research Scientist at the Lagrange Mathematics and Computing Research Center of Huawei working with Alain Durmus and Eric Moulines.
I am affiliated to the ORION-B project which gathers astrophysicists, data scientists and statisticians in order to better understand the formation of stars in our universe.
My current research interests lie in Bayesian statistics, Monte Carlo methods, federated learning, privacy-preserving learning and recommendation systems.
During my journey at Huawei, I worked on distributed/federated Bayesian approaches and privacy-preserving machine learning. My Ph.D. works focused on deriving a broad approximate statistical framework and associated Monte Carlo sampling approaches by taking inspiration from the variable splitting method in optimisation (e.g., used by quadratic penalty approaches).
- Prix Léopold Escande, 2020
- Finalist, Best Student Paper Award, IEEE MLSP 2018
2022/01 1 paper accepted at AISTATS 2022!
2022/01 I’ve joined the Criteo AI Lab!
2021/11 1 paper accepted for publication in Journal of Machine Learning Research!
2021/08 Our review paper on high-dimensional Gaussian sampling has been accepted for publication in SIAM Review!
2021/06 New preprint on Bayesian federated learning!
2021/05 1 paper accepted at ICML 2021 (long talk, top 14% of accepted papers).