![]() |
王 天 佐 |
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, where I was very fortunate to be advised by Prof. Zhi-Hua Zhou.
My research interest is mainly on Machine Learning and Artificial Intelligence. More specifically, I am interested in Causality, especially on some topics regarding latent confounders.
Rehearsal learning for avoiding undesired future.
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou.
In: Advances in Neural Information Processing Systems 36 (NeurIPS'23), New Orleans, Louisiana, 2023, to appear.
Tracking Treatment Effect Heterogeneity in Evolving Environments.
Tian Qin, Long-Fei Li, Tian-Zuo Wang, and Zhi-Hua Zhou.
Machine Learning, 2023
基于专家知识的主动因果效应辨识.
王天佐, 周志华.
中国科学:信息科学, 2023.
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.
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.
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.
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.
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.
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.
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.
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.
Probability theory and mathematical statistics. (With Associate Professor Wei Gao; For Undergraduate Students, Fall, 2019)
Game theory. (With Assistant Researcher Wei Gao; For Undergraduate Students, Fall, 2018)
LAMDA Machine Learning Summer Seminar. (For New Students in LAMDA, Summer, 2018)
Introduction to machine learning. (With Prof. Zhi-Hua Zhou; For Undergraduate Students, Spring, 2018)
Reviewer for Conferences: ICML(2023,2022,2021), NeurIPS(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: 中国科学:信息科学, SCIENCE CHINA Information Sciences, Fundamental Research, TMLR, TKDD
Reviewer for Workshop: WHY 21@NeurIPS(2021)
MLA-2018 Workflow chair (Link)
Nanjing University Yuxiu Scholar Program (南京大学“毓秀青年学者”计划)
Outstanding Reviewer for ICML 2022 (top 10%)
Program A for Outstanding PhD candidate of Nanjing University (16 people/year)
National Scholarship for Doctoral Students, MOE of PRC, 2021
The First Class Academic Scholarship in Nanjing University, Nanjing, 2017-2022
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.)