About me

I am a third-year Ph.D. student in the WILLOW team at Inria Paris (Department of Computer Science at École Normale Supérieure de Paris), under the supervision of Justin Carpentier (Inria & ENS Paris) and Nicolas Perrin-Gilbert (ISIR at Sorbonne University).

As a Ph.D. student in robotics, I focus on improving robots’ agility and dexterity through the integration of optimal control and reinforcement learning. My research explores sampling-based optimization methods enhanced with gradient information and expressive policy representations such as flow-matching. This involves designing algorithms for efficient control and optimization, and exploring their theoretical foundations and real-world applications.

Prior to my Ph.D., I gained experience as a research engineer at Wandercraft, where I used RL solutions to control a self-balanced exoskeleton, and at Inria, where I developed new features for Pinocchio and Proxsuite. I hold a master’s degree in Robotics, Cognition and Intelligence from Technical University Munich (TUM), which I obtained with distinction in January 2021. During my studies, I worked on machine learning for robotics projects in leading research labs in Germany and Japan under the supervision of Prof. Laura Leal-Taixé and Prof. Yoshihiko Nakamura.