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The project aims to develop a novel set of certifiable data-driven technologies for the control, design, and risk analysis of highly challenging autonomous systems.

The project aims to develop high-coverage and low-cost testing methods for intelligent autonomous systems

“Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability” by Laura, Yue, and Andres. “Enforcing safety for vision-based controllers via Control ” by Mukun and Charles.

Chuchu Fan invited to give a seminar at The National Centres of Competence in Research Symposium, 2022. She will be presenting on the interplay of dynamical systems, neural networks and controls.

Chuchu joins the MIT Laboratory for Information and Decision Systems as a PI.

Kunal Garg, Oswin So, Yongchao Chen, Mingxin Yu, Ruixiao Yang and Rujul Gandhi join REALM

Chuchu gave a keynote talk at the 4th Learning for Decision and Control (L4DC) conference, held in Stanford, in June 2022.