I am an Assistant Professor in the Department of Statistics at University of California Irvine. I obtained my Ph.D. degree in Statistics at North Carolina State University (NCSU), co-advised by Dr. Wenbin Lu and Dr. Rui Song. Prior to that, I obtained a B.S. in Statistics from Zhejiang University in July 2017.
I have broad research interests in methodology and theory in causal inference, reinforcement learning, graphical model, and their interchanges, to establish reliable, powerful, and interpretable solutions to wide real-world problems. Currently, my main research work includes individualized optimal decision making with complex data, policy evaluation in reinforcement/deep learning, and causal discovery for high-dimensional individual mediation analysis, directly motivated by precision medicine, customized economics, personalized marketing, modern epidemiology, etc.
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PhD in Statistics, 2022
North Carolina State University
B.S. in Statistics, 2017
, Wu, T., Wang, Y., Cai, Y., & Cai, H. (2022) On Causal Rationalization. In NeurIPS 2022 Workshop on Causality for Real-world Impact.
Cai, H., Lu, W., Marceau West R., Mehrotra DV., & Huang, L. (2022). CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search. Statistics in Medicine. 2022;1-14. DOI:10.1002/sim.9507.
Cai, H. *, Shi, C *., Song, R., & Lu, W. (2021). Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. Accepted at the 35th Conference on Neural Information Processing Systems (NeurIPS 2021).
Cai, H., Song, R., & Lu, W. (2021). ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning. Accepted at 9th International Conference on Learning Representations (ICLR 2021).
Cai, H., Song, R., & Lu, W. (2021). GEAR: On Optimal Decision Making with Auxiliary Data. Stat, 10(1):e399.
Cai, H., Cen, Z., Leng, L., & Song, R. (2021). Periodic-GP: Learning Periodic World with Gaussian Process Bandits. Accepted at IJCAI-21 Reinforcement Learning for Intelligent Transportation Systems Workshop.
Cai, H., Cen, Z., & Song, R. (2021). MAGNET: Multi-Agent Graph Cooperative Bandits. Accepted at NeurIPS-21 Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice Workshop.
Cai, H., Lu, W., & Song, R. (2020). On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies. In International Conference on Machine Learning (ICML) (pp. 1262-1270). PMLR.
Cai, H., Mandaviya, C., Levkin, R., & Song, R. (2020). Marketing Experiment Bridging: Time Inverse Bayesian Learning (TIBL). Accepted at the 8th Amazon Machine Learning Conference (AMLC 2020).
Yuan, Y., Zhou, Q. M., Li, B., Cai, H., Chow, E. J., & Armstrong, G. T. (2018). A Threshold-free Summary Index of Prediction Accuracy for Censored Time to Event Data. Statistics in medicine, 37(10), 1671-1681.
Cai, H., Lu, W., & Song, R. (2022+). CODA: Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome. arXiv preprint arXiv:2104.10554.
Shen, Y. *, Cai, H. *, & Song, R. (2022+). Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning. arXiv preprint arXiv:2110.15501.
Cai, H. *, Shi, C. *, Song, R., & Lu, W. (2022+). Jump Q-Learning for Individualized Decision Making with Continuous Treatments. arXiv preprint arXiv:2111.08885.
Price, K.+, Cai, H., Shen, W., & Hu, G. (2022+). How much does Home Field Advantage matter in Soccer Games? A causal inference approach for English Premier League analysis. arXiv preprint arXiv:2205.07193.
(* co-first author, ___ graduate student)
I was a teaching fellow in Department of Statistics at North Carolina State University.