Mechanical Engineering: Stewart Harris Seminar Series

Hao Su, PhD

Associate Professor, New York University
Director, Biomechatronics and Intelligent Robotics Lab
Center Director, Center of Assistive and Personal Robotics for Independent Living, (APRIL)

Abstract:

Wearable and surgical robots can assist human capabilities, but their progress has been constrained by two persistent challenges: they are often bulky and confined to lab settings, and they struggle to adapt to unseen scenarios. This talk presents innovations that address these challenges through advances in hardware and algorithms. Onthehardware side, I will introducehigh-torquedensity motors that electrify robotic actuation, enabling compact and lightweight medical robots. On the algorithmic side, I will highlight a physics-informed, data-driven learning-in-simulation framework, combined with deep reinforcement learning, that creates adaptive controllers without intensive human experiments and directly overcomes the data scarcity problem that limits many AI methods. Unlike supervised learning, which mimics demonstrations, this approach uses physics-informed reinforcement learning to create novel control policies that generalize to new scenarios. By integrating these two advances, we move beyond lab prototypes toward versatile, real-world robotic systems that make human movement easier, surgery safer,and robotics more accessible.

Bio:

Dr. Hao Su is an Associate Professor at New York University, Director of the Biomechatronics and Intelligent Robotics Lab, and Center Director of the Center of Assistive and Personal Robotics for Independent Living (APRIL). He is a keynote speaker at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Dr. Su has received numerous honors including the National Science Foundation CAREER Award, the Switzer Distinguished Fellowship from U.S. Department of Health and Human Services, the Toyota Mobility Challenge Discover Award, Best Medical Robotics Paper Award at the IEEE International Conference on Robotics and Automation (ICRA), and Best Paper Award from the ASME Dynamic Systems and Control Division. His research has been published in Nature, Science Robotics, Nature Machine Intelligence, Science Advances, IEEE Transactions on Robotics, and IEEE/ASME Transactions on Mechatronics. He serves as Technical Editor of the IEEE/ASME Transactions on Mechatronics, Associate Editor of the IEEE Robotics and Automation Magazine and the ASME Journal of Mechanisms and Robotics, and is on the Editorial Advisory Board of the International Journal of Medical Robotics and Computer-Assisted Surgery. He also holds multiple patents in surgical robotics, wearable robots, and socially assistive robotics.

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