Student researcher at Google DeepMind, in Paris. Previously PhD from Sorbonne University under the supervision of Professor Matthieu Cord, and intern at FAIR Meta. My works have initially explored how ensembling, weight averaging and invariance can improve the robustness and out-of-distribution generalization in deep learning; I am now investigating how the generalization literature can help for alignment, to improve reward modeling, to create AGIs benefiting society as a whole, in all its diversity.
PhD in Deep Learning, 2020 - 2023
Sorbonne University (ISIR).
Master of Science in Applied Mathematics and Operations Research, 2014 - 2015
Columbia University
Diplôme d’ Ingénieur Polytechnicien, 2011 - 2014
Ecole Polytechnique
Student Researcher, Oct 2023 - Jan 2024
Google DeepMind
Research Scientist Intern, Sep 2022 - Feb 2023
FAIR Meta, Fairness and Robustness Team
Research Scientist in Deep Learning, 2016 - 2020
Heuritech