Zhenwei (Joseph) Tang

Ph.D. Candidate
Department of Computer Science
University of Toronto
josephtang [at] cs [dot] toronto [dot] edu

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I am a Ph.D. candidate in Computer Science at University of Toronto, advised by Prof. Ashton Anderson and co-advised by Prof. Richard Zemel; my supervisory committee also includes Prof. Chris Maddison and Prof. Colin Raffel. I am also a Student Researcher at Google and a Faculty Affiliated Researcher at the Vector Institute.

My research focuses on human behavior modeling with AI/ML: understanding and modeling human decision-making, particularly in strategic domains and AI testbeds such as chess, using large-scale training of models on human behavioral data. My broader interests span LLM evaluation, LLM post-training, knowledge graphs, and recommender systems.

Previously, I received my M.S. in Computer Science from King Abdullah University of Science and Technology (KAUST), where I worked on knowledge representation learning and neuro-symbolic reasoning with Prof. Xiangliang Zhang and Prof. Robert Hoehndorf. I obtained my B.S. in Telecommunication Engineering from Beijing University of Posts and Telecommunications, where I was a member of the Elite Class.

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Education Research Experience Professional Service

  • Conference Reviewer / PC Member: NeurIPS (2024-2026), ICML (2025, 2026), ICLR (2025, 2026), AAAI (2024-2027), IJCAI (2024-2026), KDD (2024-2026), WWW (2024, 2025), AISTATS (2025, 2026), COLM (2026), ACML (2025), IC2S2 (2025), IJCLR-NeSy (2022).
  • Journal Reviewer: ACM TOIS, ACM TKDD, IEEE TKDE, IEEE Transactions on Games, Elsevier IP&M, Elsevier Information Fusion, Elsevier Information Systems.
  • Teaching Assistant: Introduction to Computer Programming (UofT, Fall 2022), Introduction to Artificial Intelligence (UofT, Winter 2023).


Last update: June 2026.