崔逸凡 - 浙江大学

个人简介

崔逸凡，长聘副教授（研究员），博士生导师。北卡罗来纳大学教堂山分校统计与运筹专业博士，曾任宾夕法尼亚大学沃顿商学院博士后研究员、新加坡国立大学统计与数据科学系助理教授。国家级青年人才计划入选者（2021），当选ISI（国际统计学会）Elected Member，入选福布斯亚洲U30杰出青年。先后主持国家自然科学基金面上项目、国家重大科技项目。教学与课程 Instructor: - 2013105: Causal Inference and Machine Learning, ZJU, Spring 2025 - 82120020: Statistical Learning, ZJU, Spring 2025 - 2013105: Causal Inference and Machine Learning, ZJU, Spring 2024 - 82120020: Statistical Learning, ZJU, Spring 2024 - 7121039: Causal Inference and Machine Learning, ZJU, Spring 2024 - 0623111: Statistical Data Analysis, ZJU, Fall 2023 - ST5198: Graduate Seminar, NUS, Spring 2022 - ST5201/ST5201X: Statistical Foundation of Data Science, NUS, Fall 2021 - STOR155: Introduction to Data Models and Inference, UNC-Chapel Hill, Spring 2017

研究领域

· 非参与半参统计 · 因果推断与机器学习 · 强化学习 · 精准决策与个性化医疗 · 生存分析

近期论文

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Shen, T., Cui, Y. Proxy-Aided Demand Learning with an Application to Various Pricing Problems. Operations Research. In press. Zhao, P., Cui, Y. A Semiparametric Instrumented Difference-in-Differences Approach to Policy Learning. Biometrika. In press. Cui, Y., Guo, J., Li, W., Tanser, F., Xiang, D. Learning Optimal Treatment Regimes with Survival Data under Imperfect Compliance: An Instrumental Variable Approach. Statistica Sinica. In press. Cui, Y., Han, S. Policy Learning with Distributional Welfare. Journal of the American Statistical Association. In press. Gao, Y., Cui, Y. Proximal Causal Learning. Wiley StatsRef: Statistics Reference Online. In press. Zhang, B., Shen, T., Cui, Y. Neural Estimation of Treatment Bridge Functions for Proximal Causal Inference. Statistical Analysis and Data Mining. In press. Chen, C.*, Zhou, W.*, Cui, Y.*, Cao, K., Chen, M., Qu, R., Miao, J., Qi, J., Wu, X., Chen, J., Zhang, H., Dai, A., Feng, Q., Yang, Y., Zhou, J., Dong, N., Yang. S. Global, Regional, and National Characteristics of the Main Causes of Increased Disease Burden due to the COVID-19 Pandemic: Time-series Modeling Analysis of Global Burden of Disease Study 2021. BMJ. In press. Bai, Y., Cui, Y. Partial causal identification for right censored data with noncompliance. Journal of Nonparametric Statistics. In press. Yu, T., Peng, M., Cui, Y., Chen, E., Chen, C. Exploring causal effects of hormone- and radio-treatments in an observational study of breast cancer using copula-based semi-competing risks models. Statistics in Medicine. In press. Cui, Y., Hannig, J. (2025) Demystifying inferential models and confidence curves: A fiducial perspective. Statistical Science, 40(2), 211–218. Cui, Y.*, Moyo, S.*, et al. (2025) Predictors of HIV seroconversion in Botswana: machine learning analysis in a representative, population-based HIV incidence cohort. AIDS, 39(3), 290-297. Cui, Y., Hannig, J., Kosorok, M. R. (2024) A unified fiducial approach to interval-censored data. Journal of the American Statistical Association, 119(547), 2230-2241. Tchetgen Tchetgen, E. J., Ying, A., Cui, Y., Shi, X., Miao, W. (2024) An introduction to proximal causal inference. Statistical Science, 39(3), 375-390. Cui, Y., Pu, H., Shi, X., Miao, W., Tchetgen Tchetgen, E. J. (2024) Semiparametric proximal causal inference. Journal of the American Statistical Association, 119(546), 1348-1359. Cui, Y., Hannig, J. (2024) A fiducial approach to nonparametric deconvolution problem: discrete case. Science China Mathematics, 67(11), 2653-2670. Michael, H., Cui, Y., Lorch, S., Tchetgen Tchetgen, E. J. (2024) Instrumental variable estimation of marginal structural mean models for time-varying treatment. Journal of the American Statistical Association, 119(546), 1240-1251. Cui, Y., Tchetgen Tchetgen, E. J. (2024) Selective machine learning of doubly robust functionals. Biometrika, 111(2), 517-535. Ogbagaber, S., Cui, Y., Li, K., Iannotti, R. J., Albert, P. S. (2024) A hidden Markov modeling approach combining objective measures of activity and self-reported sleep to estimate the sleep-wake cycle. Journal of Applied Statistics, 51(2), 370-387. Shen, T., Cui, Y. (2023) Optimal treatment regimes for proximal causal learning. NeurIPS. Yang, H., Qi, Z., Cui, Y., Chen, P. (2023) Pessimistic model selection for offline deep reinforcement learning. UAI. Sverdrup, E., Cui, Y. (2023) Proximal causal learning of conditional average treatment effects. ICML. Cui, Y., Gong, R., Hannig, J., Hoffman, K. (2023) Technical Comment on "Policy impacts of statistical uncertainty and privacy". Science, 380(6648). Han, S., Wu, P., Wang, Z., Cui, Y., Yang, H., Zhou, Z., Han, L., Yang, L., Jia, J., Shao, R., Wang, C. (2023) Reporting Studies Involving Cluster Data: Interpretation and Extension of the TRIPOD-Cluster Checklist. (in Chinese) Digital Medicine and Health, 1(1), 12-21. Cui, Y., Kosorok, M. R., Sverdrup, E., Wager, S., Zhu, R. (2023) Estimating heterogeneous treatment effects with right-censored data via causal survival forests. Journal of the Royal Statistical Society: Series B, 85(2), 179-211. Cui, Y., Michael, H., Tanser, F., Tchetgen Tchetgen, E. J. (2023) Instrumental variable estimation of the marginal structural Cox model for time-varying treatments. Biometrika, 110(1), 101-118. Loyal J. D., Zhu, R., Cui, Y., Zhang, X. (2022) Dimension reduction forests: local variable importance using structured random forests. Journal of Computational and Graphical Statistics, 31(4), 1104-1113. Sun, B., Cui, Y., Tchetgen Tchetgen, E. J. (2022) Selective machine learning of average treatment effect with an invalid instrumental variable. Journal of Machine Learning Research, 23(204), 1-40. Cui, Y., Zhu, R., Zhou, M., Kosorok, M. R. (2022) Consistency of survival tree and forest models: splitting bias and correction. Statistica Sinica, 32(3), 1245-1267. Cui, Y. (2021) Individualized decision making under partial identification: three perspectives, two optimality results, and one paradox. Harvard Data Science Review, 3(3), 1-19. Cui, Y., Tchetgen Tchetgen, E. J. (2021) On a necessary and sufficient identification condition of optimal treatment regimes with an instrumental variable. Statistics and Probability Letters, 178, 109180. Cui, Y., Tchetgen Tchetgen, E. J. (2021) Machine intelligence for individualized decision making under a counterfactual world: A rejoinder. Journal of the American Statistical Association, 116(533), 200-206. Cui, Y., Tchetgen Tchetgen, E. J. (2021) A semiparametric instrumental variable approach to optimal treatment regimes under endogeneity (with discussion). Journal of the American Statistical Association, 116(533), 162-173. Cui, Y., Hannig, J. (2019) Rejoinder to "Nonparametric generalized fiducial inference for survival functions under censoring". Biometrika, 106(3), 527-531. Cui, Y., Hannig, J. (2019) Nonparametric generalized fiducial inference for survival functions under censoring (with discussion). Biometrika, 106(3), 501-518. Cui, Y., Ogbagaber, S., Hung, H. M. (2019) Rejoinder to "Statistical inference problems in sequential parallel comparison design". Journal of Biopharmaceutical Statistics, 29(6), 1134-1136. Cui, Y., Ogbagaber, S., Hung, H. M. (2019) Statistical inference problems in sequential parallel comparison design (with discussion). Journal of Biopharmaceutical Statistics, 29(6), 1116-1129. Beyhaghi, H., Lich, K. H., Cui, Y., Kosorok, M. R. (2018) Recursively imputed survival trees for extrapolating survival beyond clinical trial follow up: A simulation study. Value in Health, 21, S223. Rieger, T. R., Allen, R. J., Bystricky, L., Chen, Y., Colopy, G., Cui, Y., Gonzalez, A., Liu, Y., White, R., Everett, R., Banks, H. T., Musante, C. J. (2018) Improving the generation and selection of virtual populations in quantitative systems pharmacology models. Progress in Biophysics and Molecular Biology, 139: 15-22. Lawson, M. T., Cho, H., Choudhury, A., Cui, Y., Jiang, X., Pokaprakarn, T., Kosorok, M. R. (2018) Discussion of Laber et al. “Optimal treatment allocations in space and time for on-line control of an emerging infectious disease”. Journal of the Royal Statistical Society Series C, 67: 779-780. Cui, Y., Zhu, R., Kosorok, M. R. (2017) Tree based weighted learning for estimating individualized treatment rules with censored data. Electronic Journal of Statistics, 11(2): 3927-3953. Book Chapters: Yan, X., Cui, Y., Chakraborty, B. (2025+) The Sequential Multiple Assignment Randomized Trial (SMART) design. in Handbook of Research Methods in Developmental Science, Wiley. Hannig, J., Iyer, H., Lee, T., Cui, Y. (2025) On fiducial inference. in International Encyclopedia of Statistical Science, 2nd ed, Springer. Shen, T., Cui, Y. (2024) Statistical reinforcement learning and dynamic treatment regimes. in Statistics in Precision Health: Theory, Methods and Applications, Springer. Cui, Y., Xie, M. (2023) Confidence distribution and distribution estimation for modern statistical inference. in Handbook of Engineering Statistics, 2nd ed, Springer. Zhu, R., Formentini, S., Cui, Y. (2023) Random forests for survival analysis and high-dimensional data. in Handbook of Engineering Statistics, 2nd ed, Springer.