I am a postdoctoral researcher at LPSM (Sorbonne University, Paris, France). My main research interests are statistical inference and optimal transport. I study how computational optimal transport, approximate inference and implicit generative modeling algorithms can be used jointly for large-scale machine learning applications.


June 2022: I am honored to have received the first prize of IP Paris Best Thesis Award 2022 for my PhD dissertation, and the Best Paper Award at IEEE ICASSP 2022 for our paper “Generalized Sliced Probability Metrics”.

January 2022: Our paper “Generalized Sliced Probability Metrics” was accepted IEEE ICASSP 2022.

November 2021: I defended my PhD thesis.

September 2021: Our paper “Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections” was accepted at NeurIPS 2021.