My major research area is machine learning, including theory, algorithms and systems. I am deeply interested in designing algorithms that make machine learning faster and better, developing theories that guide the design of such algorithms, and creating systems that are efficient and user-friendly. Recently I am focusing on distributionally robust optimization (DRO), generalization theory, fairness and causal inference.