Di Wang
- Assistant Professor, Computer Science
Biography
Di Wang is an assistant professor in the Computer Science Program and an adjunct professor in the Statistics Program within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division at KAUST. He earned his Ph.D. in computer science and engineering from the State University of New York at Buffalo, his M.S. in mathematics from Western University, and his B.S. in mathematics from Shandong University.
His research focuses on privacy-preserving machine learning, interpretability, machine learning theory, and trustworthy machine learning. During his Ph.D. studies, he was invited as a visiting student to the University of California, Berkeley; Harvard University; and Boston University. He has also served as a visiting professor at the University of Helsinki, Inria, and the Finnish Center for Artificial Intelligence.
Wang has received the SEAS Dean’s Graduate Achievement Award and the Best CSE Graduate Research Award from SUNY Buffalo.
Research Interests
Professor Wang’s research interests include machine learning (ML), security, theoretical computer science and data mining. His overall research focuses on solving issues and societal concerns arising from ML and data mining algorithms, such as privacy, fairness, robustness, transferability and transparency.
His PART team develops accurate learning algorithms that are equally private, fair, explainable and robust. These algorithms are supported by rigorous mathematical and cryptographic guarantees.
His research includes three perspectives: theory, practice and system. The theoretical component of his work provides rigorous mathematical guarantees for PART’s algorithms. The practical part develops trustworthy learning algorithms for biomedical, health care, genetic and social data, with a final focus on deploying trustworthy learning systems for healthcare and other applicable industries.
