Koushil Sreenath

Koushil Sreenath is an Assistant Professor of Mechanical Engineering at the University of California, Berkeley. He received a Ph.D. degree in Electrical Engineering and Computer Science and a M.S. degree in Applied Mathematics from the University of Michigan at Ann Arbor, MI, in 2011. He was a Postdoctoral Scholar at the GRASP Lab at University of Pennsylvania from 2011 to 2013 and an Assistant Professor at Carnegie Mellon University from 2013 to 2017. His research interests lie at the intersection of highly dynamic robotics and applied nonlinear control. His work on dynamic legged locomotion on the bipedal robot MABEL was featured on several media outlets, and his work on dynamic aerial manipulation and adaptive sampling with mobile sensor networks has been published in various journals and books. He received the Best Paper Award at the Robotics: Science and Systems (RSS) Conference in 2013 and the Google Faculty Research Award in Robotics in 2015.

Koushil Sreenath is a Mechanical Engineering professor at UC Berkeley, specializing in Control, Robotics, and Learning. His research focuses on developing safety-critical control methods for robotic systems, including control barrier functions, hybrid zero dynamics, and reinforcement learning. He has published extensively on topics such as bipedal walking, quadrotor control, and cooperative manipulation of suspended payloads. His work emphasizes the integration of geometric control theory with learning-based approaches to achieve robust and efficient robotic motion. Sreenath's research also addresses real-world applications, such as humanoid locomotion and data-driven safety filters for uncertain systems.