Alexandre Amice

Alexandre Amice is a fourth-year PhD candidate at the Massachusetts Institute of Technology (MIT) in the Department of Electrical Engineering and Computer Science (EECS), advised by Professor Pablo Parrilo and Professor Russ Tedrake. His research focuses on optimal and efficient decision-making for complex dynamical systems, particularly leveraging polynomial and graph structures to develop tractable algorithms for control theory and certification.

• Doctoral Student, MIT (2020–Present)
• Research Intern, Boston Dynamics AI Institute (May–September 2023)
• Open Source Developer, Drake Robotics Toolbox (2022–Present)
• Masters and Undergraduate Researcher, University of Pennsylvania (2018–2020)

His contributions include work on collision-free configuration space certification, sums-of-squares optimization for controller synthesis, and robust actuator scheduling under matroid constraints. He is also an active contributor to the open-source Drake simulator.

His publications highlight applications in robotics, including certified polyhedral decompositions, efficient trajectory certification, and optimization techniques for motion planning and resilient control. His work intersects robotics, optimization, and mathematical structures like posets and matroids.

He has collaborated with researchers such as Peter Werner, Tobia Marcucci, and Alejandro Ribeiro on projects related to control theory, motion planning, and collision detection. His technical experience spans institutions like MIT, the University of Pennsylvania, and Boston Dynamics AI Institute.