Di Wang
- Assistant Professor, Computer Science
Biography
Di Wang is an assistant professor of Computer Science and the principal investigator of the KAUST Provable Responsible AI and Data Analytics (PRADA) Lab.
Before joining KAUST, he obtained his Ph.D. in Computer Science and Engineering ('20) from the State University of New York (SUNY) at Buffalo, U.S.; a M.S. in Mathematics ('15) from the University of Western Ontario, Canada; and a B.S. in Mathematics and Applied Mathematics ('14) from Shandong University, China.
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.
