CV

You can download my complete resume here.

Education

• Ph.D in Electrical and Computer Engineering, New York University, 2025
  • Thesis title: Reasoning About Perception Uncertainty in Nonlinear Model Predictive Control
  Thesis

  Abstract

  In robotics, nonlinear Model Predictive Control (MPC) has emerged as a promising tool to generate complex motions while enabling online adaptation of the robot behavior as the environment changes. However, the lack of efficient computational methods hindered its widespread deployment on real hardware. In practice, MPC formulations and computational methods are often simplified to obtain real-time capable controllers. In this thesis, we develop efficient numerical methods to fully leverage the promises of MPC on robots by ensuring safe and globally optimal plans while being aware of the uncertainty resulting from the partial sensing of the environment.
• M.S. in Data Science, MVA, Ecole normale supérieure Paris-Saclay, 2019
• B.S. in Applied Mathematics, Ecole normale supérieure Paris-Saclay, 2017