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Bio
Bio
Dr. Dawei Zhou is an Assistant Professor at the Computer Science Department of Virginia Tech. Zhou’s primary research focuses on Open-World Machine Learning and AI for Scientific Discovery. His group develops intelligent systems that can autonomously generate, validate, and refine scientific hypotheses—advancing discovery pipelines in metamaterial design, healthcare, financial forensics, autonomous driving, and physics-guided predictive maintenance. He obtained his Ph.D. degree from the Computer Science Department of the University of Illinois Urbana-Champaign (UIUC). He has authored more than 60 publications in premier academic venues across AI, data mining, and information retrieval (e.g., ICML, NeurIPS, ICLR, KDD, WWW, TMLR) and has served as Vice Program Chair/Proceeding Chair/Student Travel Award Chair/Local Chair/ Session Chairs/(Senior) Program Committee Members in various top ML and AI conferences (e.g., KDD, WWW, ICDM, BigData, NeurIPS, ICML, ICLR, AAAI, IJCAI, etc.). VLOG lab received generous support from a diverse set of funding sources across federal agencies, industry, and private sectors, including NSF, DARPA, DHS, the Commonwealth Cyber Initiative, 4-VA, Deloitte, Amazon, Google, and Cisco. His work has been recognized by the 24th CNSF Capitol Hill Science Exhibition, Cisco Faculty Research Award (2023), AAAI New Faculty Highlights Roster (2024), NSF Career Award (2024), National Distinction Program (2025), and Virginia Tech Outstanding Assistant Professor Award (2025).
Lab Openings
Lab Openings
I am actively looking for self-motivated Ph.D. students (3 GRAs + 2 GTAs) and one postdoc (Virginia Tech Presidential Fellowship) to join my group in the Fall 2026 semester.
My current research includes, but is not limited to, the following topics:
Scientific Hypothesis Discovery and Evaluation (e.g., mechanical material [ICML'25-UniMate], evaluation [KDD'25-MetamatBench], disorder protein-protein interaction [DISPROTBENCH])
Artificial Long-Tail Intelligence (e.g., spectral filtering [NeurIPS'25-HeroFilter], representation learning [KDD'24-HierTail], benchmark [NeurIPS'24-HeroLT])
LLM (e.g., generalization [ICML'25-LensLLM], hallucination [ICLR'26-HalluGuard], in-context learning, and reasoning [ICLR'26-Plan and Budget])
Dynamic Ontology and Concept Drift in Open Worlds (e.g., evolving domain discrepancy [ICML'24-EvoluNet])
Machine Learning for Finance (e.g., financial forecasting [WWW'20-Dandelion], financial fraud detection [TKDD'20-HOSGRAP])
AI Safety (e.g., uncertainty quantification [KDD'25-NCPNet][WWW'25-QuaCov], evidential reasoning [KDD'25-EviNet], data sanitation [ICAIF'23-TGEditor], autonomous driving [KDD'25-DVBench])
Students with CS, Statistics, and Physics backgrounds are particularly encouraged to apply! Please drop me an email (zhoud[at]vt[dot]edu) with your CV and transcripts if you are interested.
News
News
[4/2026]: I am invited to deliver a Keynote Lecture on Open-World Long-Tailed Learning at the 65th Midwest Graph Theory Conference.
[4/2026]: Honored to receive a new grant from the Commonwealth Cyber Initiative as PI to support our research on LLM Hallucination Characterization.
[3/2026]: Honored to receive the Virginia Tech Big Contribution Grant. Congrats to Steve for his first leading PI grant since joining VT!
[2/2026]: I am delighted to serve as the Undergraduate and REU Consortium Chair for IEEE BigData 2026, which will be held in Phoenix, Arizona.
[1/2026]: Three papers have been accepted by ICLR 2026. Congrats to Xinyue and Junhong for their leading-author papers on LLM Hallucination Characterization and Test-Time Scaling for LLM Reasoning, respectively!
Sponsors
Sponsors
Contact
Contact
Office: 3160 F, Torgersen Hall, 620 Drillfield Dr., Blacksburg, VA 24060
Phone: (540) 231-2642
Email: zhoud [at] vt [dot] edu
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