I am a research associate 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 research interests lie in Bayesian modelling, the development of efficient computational methods for inferring unknown objects in complex problems and their applications to signal/image processing and machine learning.
My recent 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
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).
2020/11 I’ve joined the Lagrange center of Huawei and will work with Eric Moulines.