Koushil Sreenath 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 in 2011. He was a postdoctoral scholar at the GRASP Lab at University of Pennsylvania from 2011–13 and an assistant professor at Carnegie Mellon University from 2013–17. His research interest lies 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 CBS, CNN, the Discovery Channel, ESPN and FOX. His work on dynamic aerial manipulation was featured on the IEEE Spectrum, New Scientist and Huffington Post. His work on adaptive sampling with mobile sensor networks was published as a book entitled Adaptive Sampling with Mobile WSN (IET). 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.
Relevant expertise:
- Dynamic autonomous robotics: designing controllers for dynamic, fast, energy-efficient autonomous maneuvers on hybrid and underactuated systems including legged and aerial robots
- Learning-based autonomous control: developing reinforcement learning and nonlinear control techniques for autonomous systems operating in complex, hybrid dynamic environments