Baqun Zhang

Publisher:严继臧Release time:2019-04-01Viewer:16416

Name: Zhang Baqun

Title: Associate Professor
Research Area: Precision Medicine, Biostatistics
Courses Taught: Advanced Survival Analysis, Data Mining
E-mail: zhang.baqun@mail.shufe.edu.cn; Phone:



Research Project

Serial Number

Project Name

Project Number

Project Source

Start and End 

Time

Project 

funding

1

Research on   Statistical Methods for Estimating the Optimal Treatment Plan under a   Classification Framework in Personalized Medicine

71701120

National   Natural Science Foundation of China Youth Project



2

Design of a   Traffic-Based Personalized Coupon Mechanism


Beijing Baidu   Network Technology Co., Ltd.




Education Background

2008/12-2012/08 North Carolina State University, Statistics Major, PhD

2006/08-2008/12 North Carolina State University, Master's in Statistics

2002/09-2006/07 Nankai University, Statistics Major, Bachelor's

Work Experience

2016/10-Present, Shanghai University of Finance and Economics, School of Statistics and Management, Associate Professor

2014/06-2014/09, University of Michigan, Department of Biostatistics, Visiting Scholar

2013/08-2016/09, Renmin University of China, School of Statistics, Assistant Professor;

2012/08-2013/06, Northwestern University, Feinberg School of Medicine, Postdoctoral Fellow


Research Achievements

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.


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