About

Viet Duong is a Ph.D. candidate in Computer Science at William & Mary, where he is advised by Dr. Huajie Shao. His research focuses on developing reliable and concept-based interpretable machine learning frameworks that leverage weak supervision to reduce reliance on costly expert annotation, enabling deployment in real-world and high-stakes settings. Viet’s work has been published in top-tier AI venues, including the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), where he received a Best Paper Award, the IEEE/ACM International Conference on Software Engineering (ICSE), and Transactions on Machine Learning Research (TMLR). In 2025, he received the Stephen K. Park Graduate Research Award from William & Mary.

Before joining William & Mary, Viet earned his M.S. in Computer Science and dual Bachelor’s degrees in Data Science and Mathematics from University of Rochester.

Education

• College of William & Mary (2022 - )
  Ph.D Computer Science
• University of Rochester (2014 - 2021)
  M.S Computer Science
  B.A Data Science
  B.S Mathematics