Dawei Zhou

Dr. Dawei Zhou is an Assistant Professor at the Department of Computer Science, Virginia Tech, and the Director of the Virginia Tech Learning on Graphs (VLOG) Lab. His research focuses on Open-World Machine Learning (OpenML), with applications in AI for Material Science, Finance, and Healthcare. He holds a Ph.D. from the University of Illinois Urbana-Champaign (UIUC).

Education:

• Ph.D., Computer Science, UIUC (2021)
• M.S., Electrical and Computer Engineering, University of Rochester (2014)
• B.S., Electrical Engineering, Nanjing University of Posts and Telecommunications (2012)

Research Interests: Long-tail category analysis, transfer learning across graphs, symbolic reasoning on knowledge graphs, trustworthy learning on graphs, graph generative models for scientific domains, and AI for finance.

Grants & Awards:

• NSF Career Award (2024)
• AAAI New Faculty Highlights Roster (2024)
• Cisco Faculty Research Award (2023)
• Virginia Tech Outstanding Assistant Professor Award (2025)
• Amazon and Google Cloud Computing Grants (2024-2025)

Advising & Lab: Directs the VLOG Lab, actively recruiting Ph.D. students and postdocs. Notable advisees include Shuaicheng, Haohui, Longfeng, and others. The lab focuses on cutting-edge research in graph learning and AI-driven scientific discovery.

Service: Serves as Proceedings Chair for ACM SIGKDD 2026, Workshop Chair for IEEE BigData 2025, and on program committees for top conferences (NeurIPS, ICML, KDD).