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.
Click here for my name in Chinese and how to pronounce it.
PhD in Statistics, 2022
North Carolina State University
B.S. in Statistics, 2017
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)
I was a teaching fellow in Department of Statistics at North Carolina State University.