Tian-Zuo Wang @ LAMDA, NJU-AI
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王 天 佐 |
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About Me
Currently I am an assistant researcher (Yuxiu Young Scholar) in School of Artificial Intelligence at Nanjing University, and I am also a member of LAMDA Group. I obtained my Ph.D. degree from Department of Computer Science and Technology in Nanjing University in September 2023, where I was very fortunate to be advised by Prof. Zhi-Hua Zhou.
For prospective students: I mainly work on causal inference and decision-making methods leveraging structural information. Additionally, I am interested in applying causality to traditional machine learning problems. If you are interested in working with me, please send me an email with your CV, transcript, a description of your research interests, and other related materials.
Research Interests
My research interest includes topics in Machine Learning and Artificial Intelligence. More specifically, I am interested in
- Causal inference, especially on some topics regarding latent variables;
- Decision-making methods, especially on Rehearsal learning.
Publication
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Avoiding undesired futures with minimal cost in non-stationary environments.[PDF]
Wen-Bu Du, Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou.
In: Advances in Neural Information Processing Systems 37 (NeurIPS'24), Vancouver, Canada, 2024.
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An efficient maximal ancestral graph listing algorithm. (Spotlight)[PDF]
Tian-Zuo Wang, Wen-Bo Du, and Zhi-Hua Zhou.
In: Proceedings of the 41st International Conference on Machine Learning (ICML'24), Vienna, Austria, 2024.
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Rehearsal learning for avoiding undesired future.[PDF]
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou.
In: Advances in Neural Information Processing Systems 36 (NeurIPS'23), New Orleans, Louisiana, 2023.
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Tracking treatment effect heterogeneity in evolving environments.[PDF]
Tian Qin, Long-Fei Li, Tian-Zuo Wang, and Zhi-Hua Zhou.
Machine Learning, 2023
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基于专家知识的主动因果效应辨识.[PDF]
王天佐, 周志华.
中国科学：信息科学, 2023.
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Sound and complete causal identification with latent variables given local background knowledge.[PDF]
Tian-Zuo Wang, Tian Qin, and Zhi-Hua Zhou.
Artificial Intelligence, 2023.
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Estimating possible causal effects with latent variables via adjustment.[PDF]
Tian-Zuo Wang, Tian Qin, and Zhi-Hua Zhou.
In: Proceedings of the 40th International Conference on Machine Learning (ICML'23), Hawaii, Honolulu, 2023.
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Learning causal structure on mixed data with tree-structured functional models.[PDF]
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou.
In: Proceedings of the 23rd SIAM International Conference on Data Mining (SDM'23), Minneapolis, Minnesota, 2023.
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Sound and complete causal identification with latent variables given local background knowledge.[PDF]
Tian-Zuo Wang, Tian Qin, and Zhi-Hua Zhou.
In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), New Orleans, Louisiana, 2022.
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Actively identifying causal effects with latent variables given only response variable observable.[PDF]
Tian-Zuo Wang and Zhi-Hua Zhou.
In: Advances in Neural Information Processing Systems 34 (NeurIPS'21), Online, 2021.
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Budgeted heterogeneous treatment effect estimation.
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou.
In: Proceedings of the 38th International Conference on Machine Learning (ICML'21), Online, 2021.
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Cost-effectively identifying causal effects when only response variable is observable.[PDF][Supp][Code][Poster]
Tian-Zuo Wang, Xi-Zhu Wu, Sheng-Jun Huang, and Zhi-Hua Zhou.
In: Proceedings of the 37th International Conference on Machine Learning (ICML'20), Online, 2020.
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Towards identifying causal relation between instances and labels.[PDF][Code]
Tian-Zuo Wang, Sheng-Jun Huang, and Zhi-Hua Zhou.
In: Proceedings of the 19th SIAM International Conference on Data Mining (SDM'19), Alberta, Canada, 2019.
Academic Service
Reviewer for Conferences: ICML(2024,2023,2022,2021), NeurIPS(2024,2023,2022,2021,2020), ICLR(2023,2022,2021), UAI(2023,2022), IJCAI(2022,2021), ECAI(2020), AAAI(2023,2019), CCML(2019), PRICAI(2018)
Reviewer for Journals: Artificial Intelligence, Frontiers of Computer Science, 中国科学：信息科学, SCIENCE CHINA Information Sciences, Fundamental Research, TMLR, TKDD
Reviewer for Workshop: WHY 21@NeurIPS(2021)
MLA-2023 Organizing Committee Member (Link)
MLA-2018 Workflow chair (Link)
Correspondence
Email:
wangtz@lamda.nju.edu.cn, wangtz1994@gmail.com
Office:
Room 910, Computer Science Building, Xianlin Campus of Nanjing University
Address:
Tian-Zuo Wang, National Key Laboratory for Novel Software Technology, Nanjing University, Xianlin Campus Mailbox 603, 163 Xianlin Avenue, Qixia District, Nanjing 210023, China
(南京市栖霞区仙林大道163号, 南京大学仙林校区603信箱, 软件新技术国家重点实验室, 210023.)