Hengrui Cai (蔡亨瑞)

Hengrui Cai (蔡亨瑞)

Assistant Professor in Statistics

University of California Irvine

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. Contact me: hengrc1@uci.edu

  • Causal Inference and Causal Structure Learning
  • Reinforcement Learning and Bandits
  • Natural Language Processing and Explainable Deep Learning
  • Precision Medicine
  • PhD in Statistics, 2022

    North Carolina State University

  • B.S. in Statistics, 2017

    Zhejiang University


Awards and Honors

  • The Information and Computer Sciences (ICS) Research Award, University of California Irvine, 2023
  • 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)

Some Preprints


  • Wenbo Zhang (Ph.D. Student)
  • Shih Ting Huang (Master Student)
  • Louis Chu (Undergraduate Student)
  • Guanchen Wu (Undergraduate Student)
  • Miya Wang (Undergraduate Student)
  • Wang Ma (Undergraduate Student)


University of California Irvine (2022-)


  • STATS 120C/281C: Introduction to Probability and Statistics III (Spring 2023, two sections)

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)


  • DJL: Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings. Available on GitHub.

  • ANOCE-CVAE: Analysis of Causal Effects with Multiple Mediators via Constrained Structural Learning. Available on GitHub.

  • CODA: Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome. Available on GitHub.

  • CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search. Available on GitHub.

  • JQL: Jump Q-Learning for Individualized Interval-Valued Dose Rule. Available on CRAN.

  • APtool: Average Positive Predictive Values (AP) for Binary Outcomes and Censored Event Times. Available on CRAN.

  • APRL: Assets Portfolio Model by Reinforcement Learning. Available on GitHub.