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, with a particular interest in studying the impact of trustworthy constraints and in quantifying prediction uncertainty.

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
• Conformal Prediction
• Machine Learning with Graphs
• Robust Statistics
• Privacy in Machine Learning

News

• PhD position on Private and Byzantine-Robust Federated Learning here. _^13-05-2024