Joint Seminar: Department of Computer Science, Department of Electrical and Computer Engineering, and Laboratory for Computational Sensing and Robotics

Description

Haimin Hu, a final-year doctoral candidate in electrical and computer engineering at Princeton University, will give a talk in a seminar jointly hosted by the Department of Computer Science, the Department of Electrical and Computer Engineering, and the Laboratory for Computational Sensing and Robotics.

Abstract:

From autonomous vehicles navigating busy intersections to quadrupeds deployed in household environments, robots must operate safely and efficiently around people in uncertain and unstructured situations. However, today's robots still struggle to robustly handle low-probability events without becoming overly conservative. In this talk, I will discuss how planning in the joint space of physical and information states (e.g., beliefs) enables robots to make safe, adaptive decisions in human-centered scenarios. I will begin by introducing a unified safety filter framework that combines robust safety analysis with probabilistic reasoning to enable trustworthy human-robot interaction. I will discuss how robots can reduce conservativeness without compromising safety by closing the interaction-learning loop. Next, I will show how game-theoretic reinforcement learning tractably synthesizes a safety filter for high-dimensional systems, guarantees training convergence, and reduces the policy's exploitability. Finally, I will present an algorithmic approach to scaling up game-theoretic planning for resolving conflicts and optimizing social welfare for strategic interactions involving many agents. I will conclude with a vision for next-generation human-centered robotic systems that actively align with their human peers and enjoy verifiable safety assurances.

Bio:

Hu's research integrates dynamic game theory with control systems safety and reinforcement learning to enable trustworthy human-robot interaction. Prior to his doctoral studies, he received his Master of Science in Engineering in electrical engineering from the University of Pennsylvania in 2020 and a Bachelor of Engineering in electronic and information engineering from Shanghai Tech University in 2018. From 2017 to 2018, he was a visiting student in the Electrical Engineering and Computer Sciences Department at UC Berkeley. He has worked at the Toyota Research Institute, the Honda Research Institute, and the National Institute for Nuclear Physics in Padova, Italy, and he currently serves as an associate editor for the IEEE Robotics and Automation Letters. In 2024, he was named a Human-Robot Interaction Pioneer by IEEE and the Association for Computing Machinery.