CV
Education
- October 2023-Now: PhD in Federated Reinforcement Learning, Ecole Polytechnique, October 2023-Now
- 2022-2023: Master 2 in Applied Mathematics and Machine Learning, Université Paris-Saclay (Master MVA et troisième année du cycle ingénieur)
- 2021-2022: Master 1 in Applied Mathematics and Machine Learning, Télécom Paris (Deuxième année du cycle ingénieur)
- 2020-2021: Third year of Bachelor in Mathematics, Physics and Computer Science, Télécom Paris (Première année du cycle ingénieur)
- 2019-2020: Second year of Bachelor in Mathematics, Physics and Computer Science, Lycée du Parc, Lyon (Prépa MP*)
- 2018-2019: First year of Bachelor in Mathematics, Physics and Computer Science, Lycée Daudet, Nîmes (Prépa MPSI)
Work experience/Research Internships
- April 2023-September 2023 (6 months): Biomedical Informatics Lab, ETH Zurich
- Research Internship
- Topic: Model Selection In Deep Learning using PAC-Bayes Bounds.
- July 2022-September 2022 (3 months): LTCI lab, Télécom Paris
- Research Internship
- Topic: Variationnal Inference
- Summer 2021 (2 months): Melexis, Neuchâtel, Switzerland
- Summer internship in Automatisation
- Duties included: Program a user interface in Python that coordinates different lab equipment for sensors measurements; Manipulate several current sensors and lab devices (current source, magnetic field generator, sourcemeter, etc.) to rigorously test the program.
Service
- I serve as a reviewer for NeurIPS, AISTATS, ICLR, ICML and TMLR.