Di Wang is currently an assistant professor of computer science and adjunct srofessor of Statistics. Before that, he got his Ph.D. in computer science and engineering at the State University of New York (SUNY),  Buffalo, his M.S. at in mathematics as the University of Western, and his B.S. also in mathematics at Shandong University. His research areas include privacy-preserving machine learning, interpretability, machine learning theory, and trustworthy machine learning. During his Ph.D. studies, he s invited as a visiting student to the University of California, Berkeley, Harvard University, and Boston University. He is also a visiting professor at the University of Helsinki, Inria, and the Finnish Center of Artificial Intelligence. His research areas include differentially private machine learning, adversarial machine learning, interpretable machine learning, and robust estimation and optimization. He has received the SEAS Dean’s Graduate Achievement Award and the Best CSE Graduate Research Award from SUNY Buffalo.