Short bio

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 obtained my Ph.D. in statistics on October 7, 2020 from the University of Toulouse where I was supervised by Pierre Chainais and Nicolas Dobigeon, within the SC group of the IRIT laboratory.

In spring 2019, I was a research visiting scholar at the Department of Statistics of the University of Oxford working with Arnaud Doucet.

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.

Research interests

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).

Awards & Distinctions


2022/09 1 paper accepted at NeurIPS 2022!
2022/06 New paper on personalised federated learning!
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!