Short bio
I am a Staff 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 have been 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 privacy-preserving machine learning and data valuation.
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
- Top Reviewer, AISTATS 2022
- Prix Léopold Escande, 2020
- Finalist, Best Student Paper Award, IEEE MLSP 2018
News
2024/10 New paper on distribution-aware mean estimation under user-level differential privacy!
2024/09 Our paper on dataset valuation using novel Shapley value estimators has been accepted at NeurIPS 2024!
2024/09 Our position paper on local differential privacy & computational advertising has been accepted at WISE 2024!
2024/03 1 paper accepted at TMLR!