His research focuses on developing and applying fast algorithms for machine learning and data science. He is keen on understanding the fundamental theory and computation limits of optimization for different machine learning problems. His current research focus is on reinforcement learning theory and applications, learning for control, non-convex optimization, and streaming algorithms.