He has published over 30 papers in major machine learning and control journals and conferences. His research focuses have been on deriving algorithms for risk-sensitive, safe, robust control, sequential decision making, and (model-based and model-free) reinforcement learning, with applications to problems in robotics, power systems, and personalized recommendation.