I am a Postdoctoral Research Fellow at the Sloan Kettering Institute for Cancer Research, where I develop deep generative models and active learning algorithms to discover effective combination therapies.
I earned a Ph.D. at the Centre Borelli of the ENS Paris-Saclay in France. My thesis was sponsored by the Michelin tire company and conducted under the supervision of Pr. Mathilde Mougeot, Pr. Nicolas Vayatis and François Deheeger. My thesis focuses on developing reliable machine learning models under the intrinsic constraints of engineering design, such as domain shift and costly labeling.
I am particularly interested in developing translational ML research that can make a meaningful impact on real-world challenges, particularly in industrial and medical applications. To achieve this, my research focuses on transfer learning, domain adaptation, active learning, uncertainty quantification, and out-of-distribution detection.