王磊，男，副研究员，博导，南开大学百名青年学科带头人。研究方向是统计学习和复杂数据分析，已在Biometrika、Bernoulli、Statistica Sinica、Scandinavian Journal of Statistics、Statistics in Medicine、Computational Statistics and Data Analysis等统计学杂志发表学术论文40多篇，主持国家自然科学基金青年、面上项目及天津市自然科学基金各一项。现任中国现场统计研究会生存分析分会副秘书长，Journal of Nonparametics Statistics的Associate Editor，泛华统计协会永久会员, 荣获上海市优秀博士学位论文等。

教育背景 2008.9-2014.6 博士，华东师范大学，概率论与数理统计，导师：濮晓龙 教授 2012.9-2013.9 联合培养博士，加拿大英属哥伦比亚大学，数理统计，导师：陈家骅 教授 2004.9-2008.6 本科，南开大学，数学与应用数学

工作经历 2018.12- 南开大学统计与数据科学学院，副研究员 2017.9-2018.12 南开大学统计研究院 & 统计与数据科学学院，讲师 2014.9-2017.9 美国威斯康辛大学麦迪逊分校，博士后, 导师：Prof. Jun Shao, Prof. Menggang Yu

获奖情况 2018年, 天津市131创新型人才第三层次 2017年, 南开大学百名青年学科带头人培养计划 2016年，上海市优秀博士学位论文 2014年, 华东师范大学优秀博士学位论文 2012年, 博士研究生国家奖学金 2011年, 泛长三角应用统计学术年会论文竞赛一等奖 2010年, 全国统计建模大赛二等奖

研究兴趣 统计学习：分布式计算、最优子抽样、张量分析 复杂数据分析：缺失数据，经验似然，纵向数据，因果分析、分位数回归

主持项目 2019.9-2020.12 2019年度国家高端外国专家引进计划，医药大数据统计分析研究（战略科技发展类）. 2019.1-2022.12 国家自然科学基金面上项目，不可忽略缺失数据的若干理论研究及其应用. 2018.10-2021.10 天津市自然科学基金绿色通道项目，不可忽略缺失医疗大数据的若干理论研究及其应用. 2018.1-2023.12 南开大学百名青年学科带头人培养计划，不可忽略缺失数据：方法、理论与应用研究. 2018.1-2019.12 中央高校基本科研业务费，带有不可忽略缺失数据的若干问题研究. 2015.1-2018.12 国家自然科学基金青年项目，不可忽略缺失机制下的广义矩方法和调整经验似然方法研究.

参与项目 2018.1-2021.12 国家自然科学基金面上项目，密度比模型下的半参数经验似然推断. 2018.1-2021.12 国家自然科学基金面上项目，有限混合模型中的若干理论研究及其应用. 2016.1-2019.12 国家自然科学基金面上项目，多维因变量充分降维与多总体共同充分降维方法研究. 2015.1-2018.12 国家自然科学基金面上项目，近似周期时间序列分析及其在程序化交易中的应用. 2014.1-2017.12 国家自然科学基金面上项目，基于参数和半参数回归模型的小区域估计问题研究. 2013.1-2016.12 国家自然科学基金面上项目，序贯混合似然比检验和快速变点检测方法及其在控制图中的应用研究. 2012.1-2014.12 国家自然科学基金青年项目，关于序贯检验和序贯试验设计的若干问题研究. 2011.1-2013.12 国家自然科学基金青年项目，基于经验似然的非参数方法及其应用.

主要是统计学习（分布式计算、最优子抽样、张量分析等）和复杂数据分析（缺失数据，纵向数据，因果推断、高维数据等）

[50] Fengrui Di#(硕士), Lei Wang* and Heng Lian. Communication-efficient estimation and inference for high-dimensional quantile regression based on smoothed decorrelated score. Statistics in Medicine, revised.

[49] Yujing Shao#(博士), Wei Ma#(博士) and Lei Wang*. Robust statistical inference for longitudinal data with nonignorable dropouts. Statistics, revised.

[48] Yaohong Yang#(硕士) and Lei Wang*. Communication-efficient sparse composite quantile regression for distributed data. Metrika, revised.

[47] Yingsi Sun#(博士), Yaohong Yang#(硕士) and Lei Wang*. Dimension-reduced empirical likelihood estimation and inference for M-estimator with nonignorable nonresponse. Statistics, to appear.

[46] Xiaohong He#(硕士), Yaohong Yang#(硕士) and Lei Wang*. Generalized regression estimators for average treatment effect with multicollinearity in high-dimensional covariates. Journal of Nonparametric Statistics, to appear.

[45] Wei Ma#(博士), Ting Zhang and Lei Wang*. Improved multiple quantile regression estimation with nonignorable dropouts. Journal of the Korean Statistical Society, to appear.

[44] Fengrui Di#(硕士) and Lei Wang*. Multi-round smoothed composite quantile regression for distributed data, Annals of the Institute of Statistical Mathematics, to appear.

[43] Wei Ma#(博士) and Lei Wang*. Improved smoothing quantile regression estimation and variable selection with nonignorable dropouts. Analysis and Applications, to appear.

[42] Dongyu Li#(硕士), Lei Wang* and Weihua Zhao. Estimation and inference for multi-kink expectile regression with longitudinal data. Statistics in Medicine, to appear.

[41] Yujing Shao#(博士) and Lei Wang*. Optimal subsampling for composite quantile regression model in massive data. Statistical Papers,to appear.

[40] Ting Zhang#(博士) and Lei Wang*. Smoothed partially linear quantile regression with nonignorable missing response. Journal of the Korean Statistical Society, to appear.

[39] Xiaohong He#(硕士) and Lei Wang*. Ensemble and calibration multiply robust estimation for quantile treatment effect. Journal of Applied Statistics, to appear.

[38] Yujing Shao#(博士) and Lei Wang*. Generalized partial linear models with nonignorable dropouts. Metrika, to appear.

[37] Dongyu Li#(硕士) and Lei Wang*. Improved kth power expectile regression with nonignorable dropouts. Journal of Applied Statistics, to appear.

[36] Wei Ma#(博士) and Lei Wang*. Improved composite quantile regression and variable selection with nonignorable dropouts. Random Matrices: Theory and Applications, to appear.

[35] Lei Wang*. Identifiability and estimation of two-sample data with nonignorable missing response. Communications in Statistics – Theory and Methods, to appear.

[34] Lei Wang, Puying Zhao* and Jun Shao. Dimension-reduced semiparametric estimation of distribution functions and quantiles with nonignorable nonreponse. Computational Statistics and Data Analysis, to appear.

[33] Puying Zhao, Lei Wang* and Jun Shao. Sufficient dimension reduction for instrument search and estimation efficiency with nonignorable nonresponse. Bernoulli, to appear.

[32] Lei Wang* and Heng Lian. Communication-efficient estimation of high-dimensional quantile regression. Analysis and Applications, to appear.

[31] Lei Wang* and Wei Ma#(博士). Improved empirical likelihood inference and variable selection for generalized linear models with longitudinal nonignorable dropouts. Annals of the Institute of Statistical Mathematics, to appear.

[30] Feng Guo#, Wei Ma#(博士) and Lei Wang*. Semiparametric estimation in copula models with nonignorable missing data. Journal of Nonparametric Statistics, to appear.

[29] Ying Zhang#, Lei Wang*, Menggang Yu and Jun Shao. Quantile treatment effect estimation with many possible confounders. Statistical Theory and Related Fields, to appear.

[28] Lei Wang, Siying Sun#(博士) and Zheng Xia#. An efficient multiple imputation approach for estimating equations with response missing at random. Journal of Systems Science and Complexity, to appear.

[27] Ting Zhang#(博士) and Lei Wang*. Smoothed empirical likelihood inference and variable selection for quantile regression with nonignorable missing response. Computational Statistics and Data Analysis, to appear.

[26] Jun Shao and Lei Wang*. (2019) Nearest neighbor imputation under single index models. Statistical Theory and Related Fields, 3 (2): 208-212.

[25] Lei Wang, Jun Shao, Fang Fang*. Simultaneous propensity and instrument selection with nonignorable nonresponse. Statistica Sinica Doi:10.5705/ss.202019.0025, to appear.

[24] Puying Zhao, Lei Wang* and Jun Shao. (2019) Empirical likelihood and Wilks phenomenon for data with nonignorable missing values. Scandinavian Journal of Statistics, 46 (4), 1003-1024. (共同一作)

[23] Lei Wang*. (2019) Multiple robustness estimation in causal inference. Communications in Statistics–Theory and Methods, 48 (23): 5701-5718.

[22] Tram Ta, Jun Shao, Quefeng Li and Lei Wang*. Generalized regression estimators with high-dimensional covariates. Statistica Sinica, Doi:10.5705/ss.202017.0384, to appear.

[21] Lei Wang*. (2019) Dimension reduction for kernel-assisted M-estimators with missing response at random. Annals of the Institute of Statistical Mathematics, 71 (4): 889-910.

[20] Lei Wang, Cuicui Qi# and Jun Shao*. (2019) Model-assisted regression estimators for longitudinal data with nonignorable dropout. International Statistical Review, 87 (S1): S121-S138.

[19] Cui Xiong, Jun Shao* and Lei Wang. (2019) Convex surrogate minimization in classification. Statistica Sinica, 29 (1): 353-369.

[18] Lei Wang* (2018) Some issues on longitudinal data with nonignorable dropout, a discussion of ``Statistical Inference for Nonignorable Missing-Data Problems: A Selective Review'' by Niansheng Tang and Yuanyuan Ju. Statistical Theory and Related Fields, 2 (2): 137-139.

[17] Lei Wang* and Dan Yang#. (2018) F-distribution calibrated empirical likelihood ratio tests for FDR control in multiple hypothesis testing. Journal of Nonparametric Statistics, 30 (3): 662-679.

[16] Ying Zhang#, Menggang Yu, Jun Shao and Lei Wang* . (2018) Impact of sufficient dimension reduction in nonparametric estimation of causal effect. Statistical Theory and Related Fields, 2 (1): 89-95.

[15] Ying Zhang# and Lei Wang*.（2018） Dimension reduction in estimating equations with covariates missing at random. Journal of Nonparametric Statistics, 30 (2): 491-504.

[14] Puying Zhao, Lei Wang* and Jun Shao.（2018）Analysis of longitudinal data under nonignorable nonmomotone nonresponse. Statistics and Its Interface, 11 (2): 265-279. (共同第一作者).

[13] Lei Wang*.(2017) Bartlett-corrected two-sample adjusted empirical likelihood via resampling. Communications in Statistics-Theory and Methods, 46(22):10941-10952 .

[12] Lei Wang and Guangming Deng. (2017) Dimension-reduced empirical likelihood inference for response mean with data missing at random. Journal of Nonparametric Statistics, 29 (3): 594-614.

[11] Jun Shao and Lei Wang*. (2016) Semiparametric inverse propensity weighting for nonignorable missing data. Biometrika, 103 (1): 175-187.

[10] Dongdong Xiang, Yan Li, Lei Wang and Xiaolong Pu*. (2016) Double stepwise likelihood ratio test for onesided composite Hypotheses. Quality Technology and Quantitative Management, 13 (3): 355-366.

[9] Lei Wang, Jiahua Chen* and Xiaolong Pu. (2015) Resampling calibrated adjusted empirical likelihood. Canadian Journal of Statistics , 43 (1): 42-59.

[8] Lei Wang*, Wendong Li, Guanfu Liu and Xiaolong Pu. (2015) Spatial median depth-based robust adjusted empirical likelihood. Journal of Nonparametric Statistics, 27 (4): 485-502.

[7] Lei Wang*, Xiaolong Pu and Yan Li. (2015) Asymptotic optimality of combined double sequential weighted probability ratio test for three composite hypotheses. Mathematical Problems in Engineering, 2015: 1-8.

[6] Lei Wang, Xiaolong Pu, Yan Li and Yukun Liu*. (2015) Sequential two-stage D-optimality sensitivity test for binary response data. Communications in Statistics-Simulation and Computation , 44 (7):1833-1849.

[5] Guanfu Liu, Xiaolong Pu, Lei Wang and Dongdong Xiang*. (2015) CUSUM chart for detecting range shifts when monotonicity of likelihood ratio is invalid. Journal of Applied Statistics , 42 (8): 1635-1644.

[4] Lei Wang, Xiaolong Pu, Donddong Xiang and Yan Li*. (2014) Asymptotic optimality of double sequential mixture likelihood ratio test. Journal of Statistical Computation and Simulation , 84 (4): 916-929.

[3] Lei Wang, Yukun Liu, Wei Wu and Xiaolong Pu*.(2013) Sequential LND sensitivity test for binary response data. Journal of Applied Statistics, 40 (11): 2372-2384.

[2] Lei Wang, Donddong Xiang, Xiaolong Pu and Yan Li*. (2013) A double sequential weighted probability ratio test for one-sided composite hypotheses. Communications in Statistics-Theory and Methods, 42 (20): 3678-3695.

[1] Dongdong Xiang, Xiaolong Pu, Lei Wang and Yan Li*.(2012) Degenerate-generalized likelihood ratio test for one-sided composite hypotheses. Mathematical Problems in Engineering , Volume 2012 (2012): 1–11.