I am an Assistant Professor in Statistics in the Donald Bren School of Information and Computer Sciences 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 learning and bandits, natural language processing and explainable 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.
Contact me: hengrc1@uci.edu
- Causal Inference and Causal Structure Learning
- Reinforcement Learning and Bandits
- Natural Language Processing and Explainable Deep Learning
- Precision Medicine
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PhD in Statistics, 2022
North Carolina State University
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B.S. in Statistics, 2017
Zhejiang University
News
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Aug 2024: Our work is supported by NSF-DMS. Thanks NSF!
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Aug 2024: I will serve as Area Chair for International Conference on Learning Representations (ICLR 2025).
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July 2024: Our work Defining Boundaries: A Spectrum of Task Feasibility for Large Language Models is available on ArXiv.
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Feb 2024: Our tutorial book on Causal Decision Making is online! Check https://causaldm.github.io/Causal-Decision-Making/.
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Dec 2023: Congratulations to my student Wenbo Zhang on passing the Ph.D. Advancement to Candidacy with the title Towards Trustworthy Machine Learning: A Lens on Explainability !
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Oct 2023: Our tutorial proposal on Foundations, Practical Applications, and Latest Developments in Causal Decision Making is accepted at AAAI-2024 Tutorial!
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Sept 2023: Our paper On Learning Necessary and Sufficient Causal Graphs is accepted at NeurIPS 2023 as a spotlight!
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Sept 2023: Our paper Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning is accepted at Journal of the American Statistical Association.
Awards and Honors
- CDS&E-MSS Award, National Science Foundation, 2024
- The Information and Computer Sciences (ICS) Research Award, University of California Irvine, 2023 & 2024
- Academic Senate Council on Research, Computing and Libraries (CORCL) Award, University of California Irvine, 2023
- Amazon Web Services Cloud Research Award, Amazon, 2022
- ENAR Distinguished Student Paper Award, The International Biometric Society, 2020
- Nominated for the Outstanding TA Award, NCSU, 2019 and 2021
- Mu Sigma Rho, National Statistics Honor Society, NCSU, 2017 - Present
- National Undergraduate Research Fund, 2017
- Meritorious Winner in American Mathematical Contest, 2016
Selected Publications
(* co-first author, ___ graduate student author, ^ corresponding author)
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Cai, H., Wang, Y., Jordan, M., & Song, R. (2023). On Learning Necessary and Sufficient Causal Graphs. Advances in Neural Information Processing Systems (NeurIPS).
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Shen, Y. *, Cai, H. *, & Song, R. (2023). Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning. Journal of the American Statistical Association.
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Zhang, W., Wu, T., Wang, Y., Cai, Y., & Cai, H.^ (2023) Towards Trustworthy Explanation: On Causal Rationalization. In International Conference on Machine Learning (ICML 2023).
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Watson, RA. *, Cai, H. *, An, X., McLean, S., & Song, R. (2023). On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs. In International Conference on Machine Learning (ICML 2023).
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Cai, H. *, Shi, C. *, Song, R., & Lu, W. (2023). Jump Q-Learning for Individualized Decision Making with Continuous Treatments. Journal of Machine Learning Research.
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Cai, H.^, Lu, W., Marceau West R., Mehrotra DV., & Huang, L. (2022). CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search. Statistics in Medicine.
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Cai, H. *, Shi, C *., Song, R., & Lu, W. (2021). Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. Advances in Neural Information Processing Systems (NeurIPS).
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Cai, H., Song, R., & Lu, W. (2021). ANOCE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning. International Conference on Learning Representations (ICLR).
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Cai, H., Lu, W., & Song, R. (2020). On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies. International Conference on Machine Learning (ICML).
Some Preprints
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Zhang, W., Xu, Z., & Cai, H.^ (2024+). Defining Boundaries: A Spectrum of Task Feasibility for Large Language Models. arXiv preprint arXiv:2408.05873.
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Cai, H. *, Jin, H. *, Li, L. (2024+). Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference. arXiv preprint arXiv:2408.01582.
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Wei, H. *, Cai, H. *, Shi, C., & Song, R. (2024+). On Efficient Inference of Causal Effects with Multiple Mediators. arXiv preprint arXiv:2401.05517.
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Cai, H. *, Liu, S. *, & Song, R. (2024+). Is Knowledge All Large Language Models Needed for Causal Reasoning? arXiv preprint arXiv:2401.00139.
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Cai, H., Lu, W., & Song, R. (2024+). CODA: Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome. arXiv preprint arXiv:2104.10554.
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Ma, T., Cai, H., Qi, Z., Shi, C., & Laber, E. B. (2024+). Sequential Knockoffs for Variable Selection in Reinforcement Learning. arXiv preprint arXiv:2303.14281.
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Shen, Y., Wan, R., Cai, H., & Song, R. (2024+). Heterogeneous Synthetic Learner for Panel Data. arXiv preprint arXiv:2212.14580.
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Price, K.+, Cai, H., Shen, W., & Hu, G. (2024+). How much does Home Field Advantage matter in Soccer Games? A causal inference approach for English Premier League analysis. arXiv preprint arXiv:2205.07193.
Advisees
Current Students
- Wenbo Zhang (Ph.D. Student)
- Liner Xiang (Ph.D. Student)
- Lijinghua Zhang (Ph.D. Student)
Previous Students
- Shih Ting Huang (Master Student, Graduated at Summer 2023)
- Guanchen Wu (Undergraduate Student, Graduated at Winter 2024)
- Louis Chu (Undergraduate Student, Graduated at Spring 2024)
- Zihang Xu (Undergraduate Student, Graduated at Summer 2024)
Teaching
University of California Irvine (2022-)
Instructor:
- STATS 295: Causal Machine Learning (Fall 2024, elective course)
- STATS 120C/281C: Introduction to Probability and Statistics III (Spring 2024, two sections)
- STATS 120C/281C: Introduction to Probability and Statistics III (Spring 2023, two sections)
- STATS 280: Seminar in Statistics (Fall 2023)
North Carolina State University (Prior to 2022)
Lab Instructor:
- ST 703: Statistical Methods I (Fall 2019)
- ST 114: Introduction to Statistical Programming - Python (Spring 2022)
Teaching Fellow:
- ST 422: Introduction to Mathematical Statistics II (Fall 2021)
- ST 745: Analysis of Survival Data (Spring 2021)
- ST 405/505: Applied Nonparametric Statistics (Fall 2020)
- ST 311: Introduction to Statistics (Spring 2019)
- ST 790: Financial Statistics (Fall 2018)
- ST 312: Introduction to Statistics II (Spring 2018)
- ST 511: Introduction to Statistics for Biological Sciences (Fall 2018)
- ST 350: Economic and Business Statistics (Fall 2017)
Contact
- hengrc1@uci.edu
- Bren Hall 2224, Irvine, CA 92697