About me
I am a researcher in statistics and machine learning in the MAGNET team of Inria Lille. My current focus is on decentralized learning methods and the impact of imposing trustworthy ML constraints over them.
From June 2023 to July 2024, I was a postdoc in the ARGO team of Inria Paris and DI ENS (computer science department of Ecole Normale Supérieure), working with Kevin Scaman on the generalization properties of Federated Learning algorithms. I also worked in close collaboration with Aurélien Bellet, Marc Tommasi and Giovanni Neglia. Before that, I was a postdoc in the MAGNET team, working with Marc Tommasi, Aurélien Bellet and Anne-Marie Kermarrec (EPFL) on decentralized optimization.
In January 2021, I completed a PhD in applied mathematics at Centre Borelli, ENS Paris-Saclay, under the supervision of Prof. Nicolas Vayatis and Argyris Kalogeratos. My thesis work focused on statistical learning problems for data observed over graph structures, with applications to anomaly and change-point detection. Prior to my thesis, I obtained a master in mathematics, computer vision and machine learning (MVA) at ENS Paris-Saclay.
You can learn more about me on my CV.
Research interests
- Statistical Learning, High dimentional statistics
- Decentralized Optimization, Federated Learning
- Trustworthy ML
- Conformal Prediction
- Machine Learning with Graphs
- Privacy in Machine Learning
News
- PhD position on Conformal Prediction and Physics-Informed ML here.
PhD position on Private and Byzantine-Robust Federated Learning here.13-05-2024- Les BD du frangin, le restaurant de la mamma et les photos du beau-père.