Bio
Haimin Hu is an Assistant Professor of Computer Science at Johns Hopkins University. His research focuses on the algorithmic foundations of human-centered autonomy. By integrating dynamic game theory with machine learning and safety-critical control, his work enables verifiable, deployable, and trustworthy embodied AI systems, from autonomous vehicles to drones and quadrupedal robots. Specifically, his research covers the following topics:
- Uncertainty-aware interactive motion planning: How can robots plan safe and efficient motion by accounting for their evolving uncertainty, as well as their ability to reduce it through future interaction, sensing, communication, and learning?
- Human–AI co-evolution and co-adaptation: How can embodied AI systems learn from human teammates while helping them refine existing skills and acquire new ones in a safe, personalized manner?
- Safe human-compatible autonomy: How can autonomous systems ensure prescribed safety while remaining aligned with human values and attuned to human cognitive limitations?
- Scalable and generalizable strategic decision-making: How can multi-robot systems make safe, coordinated decisions in dynamic, human-populated environments?
He has received several awards and recognitions, including a 2026 Penn AI Fellow, a 2025 Robotics: Science and Systems Pioneer, a 2025 Cyber-Physical Systems Rising Star, and a 2024 Human-Robot Interaction Pioneer.
Currently, he serves as an Associate Editor for IEEE Robotics and Automation Letters (RA-L). He received a PhD (2025) and an MA (2022) in Electrical and Computer Engineering from Princeton University, an MSE (2020) in Electrical Engineering from the University of Pennsylvania, and a BEng (2018) in Electronic and Information Engineering from ShanghaiTech University. From 2025 to 2026, he was a postdoctoral fellow with the PRECISE Center and the GRASP Lab at the University of Pennsylvania.
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Hobbies
Skiing, road trips, video gaming, photography