秦 天
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Currently I am a fourth year Ph.D. candidate of School of Artificial Intelligence in Nanjing University and a member of LAMDA Group, led by Prof. Zhi-Hua Zhou. I received my B.Sc. degree in Computer Science and Technology in June 2020 from Nanjing University. In the same year, I was admitted to pursue Ph.D. degree without entrance examination.
My research interests include machine learning, causal inference, and data mining.
Tian Qin, Long-Fei Li, Tian-Zuo Wang, and Zhi-Hua Zhou. Tracking Treatment Effect Heterogeneity in Evolving Environments. Machine Learning, 2024. [supp][code]
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou. Rehearsal Learning for Avoiding Undesired Future. In: Advances in Neural Information Processing Systems 36 (NeurIPS'23), New Orleans, LA, 2023. [code]
Tian-Zuo Wang, Tian Qin, and Zhi-Hua Zhou. Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge. Artificial Intelligence, 2023.
Tian-Zuo Wang, Tian Qin, and Zhi-Hua Zhou. Estimating Possible Causal Effects with Latent Variables via Adjustment. In: Proceedings of the 40th International Conference on Machine Learning (ICML'23), Honolulu, HI, 2023.
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou. Learning Causal Structure on Mixed Data with Tree-Structured Functional Models. In: Proceedings of the 23rd SIAM International Conference on Data Mining (SDM'23), Minneapolis, MN, 2023. [supp][code]
Tian-Zuo Wang, Tian Qin, and Zhi-Hua Zhou. Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge. In: Advances in Neural Information Processing Systems 35 (NeurIPS'22), New Orleans, LA, 2022.
Tian Qin, Tian-Zuo Wang, and Zhi-Hua Zhou. Budgeted Heterogeneous Treatment Effect Estimation. In: Proceedings of the 38th International Conference on Machine Learning (ICML'21), Online, 2021. [supp][code]