职 称：副教授
研究方向：精准医疗,生物统计
教授课程：高等生存分析，数据挖掘
E - mail：zhang.baqun@mail.shufe.edu.cn；电话：
研究项目
| 序号 | 项目名称 | 项目编号 | 项目来源 | 起止时间 | 项目经费 |
| 1 | 个性化医疗中在分类框架下估计最佳治疗方案的统计方法研究 | 71701120 | 国家自然科学基金青年项目 | ||
| 2 | 基于流量的个性化优惠劵机制设计 | 北京百度网讯科技有限公司 |
2016/10-至今， 上海财经大学 统计与管理学院，副教授
2014/06-2014/09， 美国密歇根大学 生物统计系，访问学者
2013/08-2016/09， 中国人民大学 统计学院，助理教授；
2012/08－2013/06，美国西北大学 医学院，博士后
Yang Guangyu，Zhang Baqun and Zhang Min (2025) Statistical inference on changepoints in generalized semiparametric segmented models, Biometrics, Volume 81,Issue 1
Xingdong Feng; Yuling Jiao; Lican Kang; Baqun Zhang; Fan Zhou (2023),Over-parameterized deep nonparametric regression for dependent data with itsapplications to reinforcement learning, Journal of Machine Learning Research,24,1-40
Yang Guangyu，Zhang Baqun and Zhang Min (2023). Estimation of Knots in LinearSpline Models. JASA, .118(541), 639–650
Guangyu Yang; Baqun Zhang; Jonathan W. Haft; Robert B. Hawkins; David Sturmer;Donald S. Likosky; Min Zhang (2023) Modeling and estimating a threshold effect: Anapplication to improving cardiac surgery practices, Statistical Methods in Medical Research, 32(12), 2318-2330
Zhishuai Liu; Zishu Zhan; Cunjie Lin; Baqun Zhang (2023), Estimation in optimal treatment regimes based on mean residual lifetimes with right‐censored data,Biometrical Journal, 65(8), 2200340
王言覃; 张拔群; 李秋; 徐铣明 (2023), 真实世界研究在儿科人群中的应用现状与挑战, 中华儿科杂志, 61(4), 377-380
Zhang Baqun and Zhang Min (2022). Subgroup identification and variable selectionfor treatment decision making. The Annals of Applied Statistics, 16(1), 40-59
Zhang Min and Zhang Baqun(2022). Astable and more efficient doubly robustestimator. Statistica Sinica, 32(12), 1143-1163
Fang, Yuexin, Zhang, Baqun, Zhang, Min(2021). Robust Method for OptimalTreatment Decision Making Based on Survival Data, Statistics in Medicine,40(29), 6558-6576
Zhang Min and Zhang Baqun (2021). Discussion of “Improving precision and powerin randomized trials for COVID-19 treatments using covariate adjustment, for binary,ordinal, and time-to-event outcomes”. Biometrics, 77(12), 1485-1488
Zhang Baqun and Zhang, Min(2018). Clearning: a New Classification Framework to Estimate Optimal Dynamic Treatment Regimes, Biometrics, 74(3), 891-899.
Zhang Baqun and Zhang, Min(2018). Variable selection for estimating the optimal treatment regimes in the presence of a large number of covariates. The Annals of Applied Statistics, 12(4), 2335-2358
Xu Z, Zhang G, Duan Q, Chai S, Baqun Zhang, Wu C, Jin F, Yue F,Li Y, Hu M(2016)HiView: an integrative genome browser to leverage HiC results for the interpretation of GWAS variants, BMC Research Notes, 9(1):159
Yan S, Yuan S, Xu Z，Baqun Zhang，Zhang B，Kang G，Byrnes A，Li Y(2015) Likelihood Based Complex Trait Association Testing for Arbitrary Depth Sequencing Data，Bioinformatics，31（18）：2955-2962
Zhang, B., Tsiatis, A.A., Laber, E.B., and Davidian, M.(2015) Response to reader reaction to "A robust method for estimating optimal treatment regimes” by Zhang et al. (2012), Biometrics，71（1）：271-273.
Zhang, B., Tsiatis, A.A., Laber, E.B., and Davidian, M. (2013) Robust Estimation of Optimal Dynamic Treatment Regimes for Sequential Treatment Decisions. Biometrika, 100, 681-694.
Zhang, B., Tsiatis, A.A., Laber, E.B., and Davidian, M.(2012) A Robust Method for Estimating Optimal Treatment Regimes. Biometrics, 68, 1010–1018.
Zhang, B.,Tsiatis, A.A., Davidian, M, Zhang, M, and Laber, E.B., (2012)Estimating Optimal Treatment Regimes from a Classification Perspective. Stat, 1, 103-114.
