王磊

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

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

王磊，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Current Biology（Cell子刊）、Biometrika（1）、SCIENCE CHINA Mathematics（3）、Bernoulli（1）、Statistica Sinica（6）、Scandinavian Journal of Statistics（3）、Statistics in Medicine（2）、Information Science (2)、Test (1)、Applied Mathematical Modelling (1)、Applied Intelligence（1）、Computational Statistics and Data Analysis（6）等统计学杂志发表学术论文60多篇，其中1篇为ESI高被引论文，主持3项国家自科学基金（面上项目2项和青年项目1项）和1项天津市自然科学基金项目。现任中国场统计研究会生存分析分会副秘书长，Journal of Nonparametric StatisticsAssociate Editor，泛华统计协会永久会员, 2016年荣获上海市优秀博士学位论文荣誉称号，2018年入选天津市131创新型人才培养工程第三层次，2019年获得南开大学五年奖章，第四、五届全国应用统计专业学位研究生教育教学成果奖、南开大学研究生创新实践“优秀指导教师”，2023年荣获南开大学优秀硕士学位论文指导教师。

研究方向主要是统计学习（分布式计算、最优子抽样、迁移学习、在线学习、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）

招收1名博士和多名硕士研究生(有扎实的数学及统计学基础和编程能力，能踏实做科研，学硕需录用或者发表至少1篇SCI论文，已指导研究生发表SCI论文40余篇)，由于名额紧张，请有意者通过邮件咨询lwangstat@nankai.edu.cn

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News

国家自然科学基金面上项目《几类复杂高维大数据的稀疏学习与融合分析》（2023.01-2026.12）获批。

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代表论文 (其它论文请见“论文专著”)

[33]Zhaohan  Hou#(硕士) and Lei Wang*.Statistica Sinica, revised.  

[32]Xing Li#(硕士) and Lei Wang*. Test, revised. 

[31]Chunyang Zhu,  Lei Wang*, Weihua Zhao* and Heng Lian. Applied Intelligence, revised. 

[30]Yujing Shao#(博士) and Lei Wang*. Journal of Computational and Graphical Statistics, revised.  

[29]Wei  Ma#(博士)，Lei Wang* and Heng Lian. Journal of Business and Economic Statistics, revised. 

[28]Xudong Zhang#(硕士) and Lei Wang*. Computational Statistics and Data Analysis, revised.  

[27]Ziyuan Wang#(硕士) and Lei Wang*. Scandinavian Journal of Statistics, to appear.  

[26]Mengyi Wang, Xueling Wang, Ling Wang, Li Zheng,  Shuang Meng, Nan Zhu, Xingwei An, Lei Wang*, Jiajia Yang*, Chengguang Zheng* and Dong Ming*. Current Biology, to appear. 

[25]Zhaohan  Hou#(硕士) and Lei Wang*. Computational Statistics and Data Analysis, to appear.  

[24]Xudong Zhang#(硕士) and Lei Wang*. Information Sciences, to appear.  

[23]Dongyu Li#(硕士) and Lei Wang*. SCIENCE CHINA Mathematics, to appear.  

[22]Wei  Ma#(博士)，Junzhuo Gao#(硕士)，Lei Wang* and Heng Lian. Statistica Sinica, to appear.  

[21]Yue Wang, Wenqi Lu, Lei Wang, Zhongyi Zhu,  Hongmei Lin and Heng Lian. Statistica Sinica, to appear.  

[20]Zihao Song,  Lei Wang*and Weihua Zhao*. Applied Mathematical Modelling, to appear.  

[19]Yaohong Yang#(硕士)，Lei Wang* and Heng Lian. Computational Statistics and Data Analysis, to appear.  

[18]Ly Ni,  Jinyi Wang, Jun Shao and Lei Wang*. Statistica Sinica, to appear.  

[17]Junzhuo Gao#(硕士) and Lei Wang*. Communication-efficient low-dimensional parameter estimation and inference for high-dimensional $L^p$-quantile regression. Scandinavian Journal of Statistics, to appear.

[16]Yaohong Yang#(硕士)，Lei Wang* and Weihua Zhao. Computational Statistics and Data Analysis, to appear.  

[15]Zhaohan  Hou#(硕士)，Wei  Ma#(博士) and Lei Wang*. TEST, to appear.

[14]Junzhuo Gao#(硕士) and Lei Wang* (2023).Communication-efficient distributed estimation of partially linear models for large-scale data. Information Sciences, 631, 185-201. 

[13]Jun Shao, Jinyi Wang and Lei Wang* (2023).SCIENCE CHINA Mathematics, to appear.  

[12]Junzhuo Gao#(硕士), Lei Wang* and Heng Lian (2023).Optimal decorrelated score subsampling for generalized linear models with massive data.SCIENCE CHINA Mathematics, to appear.  

[11]Baofang Ke#(博士), Lei Wang* and Weihua Zhao (2023).Smoothed tensor quantile regression estimation for longitudinal data. Computational Statistics and Data Analysis, 178, 10709. 

[10]Fengrui Di#(硕士), Lei Wang* and Heng Lian (2022). Communication-efficient estimation and inference for high-dimensional quantile regression based on smoothed decorrelated score. Statistics in Medicine, 41 (25), 5084-5101. 

[9]Dongyu Li#(硕士), Lei Wang* and Weihua Zhao (2022). Estimation and inference for multi-kink expectile regression with longitudinal data. Statistics in Medicine, 41 (7), 1296-1313. 

[8]Lei Wang, Puying Zhao* and Jun Shao (2021). Dimension-reduced semiparametric estimation of distribution functions and quantiles with nonignorable nonreponse. Computational Statistics and Data Analysis, 156, 107142. 

[7]Puying Zhao, Lei Wang* and Jun Shao (2021).. Sufficient dimension reduction for instrument search and estimation efficiency with nonignorable nonresponse. Bernoulli, 27 (2), 930-945. 

[6]Ting Zhang and Lei Wang*(2020). Smoothed empirical likelihood inference and variable selection for quantile regression with nonignorable missing response. Computational Statistics and Data Analysis, 144, 106888. 

[5]Lei Wang, Jun Shao, Fang Fang* (2021). Simultaneous propensity and instrument selection with nonignorable nonresponse. Statistica Sinica, 31 (2), 647-672. 

[4]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)

[3]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.

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

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

其它论文 

[48] Yajie Mi#(硕士) and Lei Wang*. Journal of Applied Statistics, revised.

[47] Ting Zhang, Yanan Wamg#(硕士)  and Lei Wang*. Journal of the Korean Statistical Society, revised.

[46] Jun Shao and Lei Wang*. Chinese Journal of Applied Probability and Statistics, revised.

[45] Dongyu Li#(硕士) and Lei Wang*. Statistical Theory and Related Fields, to appear.

[44] Junhao Shan#(博士) and Lei Wang*. Journal of Applied Statistics, to appear.

[43] Yaohong Yang#(硕士) and Lei Wang*. Journal of the Korean Statistical Society, to appear.

[42] Yanjing Peng#(硕士) and Lei Wang*. Journal of Systems Science and Complexity, to appear. 

[41] Xudong Zhang#(硕士)，Ting Zhang and Lei Wang*. Statistics, to appear.  

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

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

[38] 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.

[37] 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.

[36] 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.

[35] 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.

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

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

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

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

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

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

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

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

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

[25] 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.

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

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

[22] 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.

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

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

[19] 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.

[18] 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.

[17] 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.

[16] 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.

[15] 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.

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

[13] 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).

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

[11] 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.

[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.

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学生获奖及荣誉

2023年12月，于小晗 齐思涵 赵星澎（专硕, 2023年9月-2025年6月）获第二十届中国研究生数学建模大赛二等奖，指导教师：王磊

2023年10月，邵雨静荣获第七届全国统计学博士研究生学术论坛二等奖

2023年10月，邸丰瑞荣获南开大学2023年优秀硕士学位论文

2023年10月，学硕高俊卓荣获姜立夫优秀学生奖学金特等奖

2023年10月，学硕高俊卓荣获国家奖学金

2023年，李冬雨 （学硕, 2020年9月-2023年6月）考入中科院科学与系统科学研究院攻读博士研究生，导师王启华研究员。

2023年，李冬雨 （学硕, 2020年9月-2023年6月）获南开大学“优秀毕业生”称号

2022年12月，王磊、李聪航、王晓楠、颜致远编写的案例被全国应用统计专业学位教育教学案例库收录。

2022年12月，学硕高俊卓荣获悟空投资高水平原创成果奖励计划二等奖

2022年12月，司马成晨 （专硕, 2022年9月-2024年6月）获第十九届中国研究生数学建模大赛二等奖，指导教师：王磊

2022年12月，王馨竹 （专硕, 2022年9月-2024年6月）获第十九届中国研究生数学建模大赛三等奖，指导教师：王磊

2022年11月，柯宝芳荣获第六届全国统计学博士研究生学术论坛三等奖

2022年10月，学硕邸丰瑞荣获国家奖学金

2022年09月，学硕李冬雨、邸丰瑞、高俊卓荣获校级研究生优秀学生

2022年09月，颜致远 （专硕, 2021年9月-2023年6月）获第五届全国应用统计专业学位研究生案例大赛二等奖，指导教师：王磊

2022年09月，李聪航 （专硕, 2021年9月-2023年6月）获第五届全国应用统计专业学位研究生案例大赛二等奖，指导教师：王磊

2022年，贺小红 （学硕, 2019年9月-2022年6月）获南开大学“优秀毕业生”称号

2022年，李冬雨 （学硕, 2020年9月-至今）获陈省身学术新人奖学金

2021年，李冬雨 （学硕, 2020年9月-至今）获国家奖学金

2020年，夏 政  （专硕, 2018年9月-2020年6月）获南开大学“优秀毕业生”称号

2020年，马维荣获第四届全国统计学博士研究生学术论坛优秀奖

2020年，吴凤婷 （专硕, 2019年9月-2021年6月）获第四届全国应用统计专业学位研究生案例大赛二等奖,指导教师：王磊

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学生境外学术交流

2023年1月-2024年1月，马维（直博生, 2019年9月-现在），赴新加坡国立大学联合培养博士1年

2019年9月-2020年9月，王慧宇（硕士生, 2018年9月-现在），赴英国伯明翰大学数学系联合培养1年（南开大学-伯明翰大学联合硕士培养项目）

2019年9月-2020年9月，高欣玥（硕士生, 2019年9月-现在），赴英国伯明翰大学数学系联合培养1年（南开大学-伯明翰大学联合硕士培养项目）

2020年9月-2021年9月，安雅婧（硕士生, 2019年9月-现在），赴英国伯明翰大学数学系联合培养1年（南开大学-伯明翰大学联合硕士培养项目）

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在学研究生

2023级：单君昊（直博) 李星（学硕） 费雨欣（学硕）王滋源（学硕） 于小晗（专硕） 齐思涵（专硕） 赵星澎（专硕）

2022级：杨继辰（直博) 张旭东（贯通） 彭燕襟（学硕）米雅洁（学硕） 司马成晨（专硕） 刘晓燕（专硕） 王馨竹（专硕）

2021级：柯宝芳（博直) 杨耀鸿（学硕） 高俊卓（学硕）侯召涵（学硕） 

2020级：邵雨静（直博) 

2019级：马维（直博) 

2018级：孙思颖（博士）

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毕业研究生

2023届：

李聪航（中国邮政储蓄银行），王佳（中国移动南京分公司），颜致远（中国交通银行），李冬雨（中科院读博），王雅楠（中国工商银行），邸丰瑞（北京市审计局）

2022届：

安雅婧（中国银行总行），高欣玥（出国）

2021届：

吴凤婷 （龙湖地产有限公司），贺小红（天津市统计局）

2020届：

苏嘉兴（中国建设银行股份有限公司河北省分行），孙晓涵（中国烟草总公司湖北省公司随州市局），夏 政（国家统计局安徽调查队），王慧宇 (美团科技有限公司)

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社会兼职

中国现场统计研究会统计调查分会理事(2023年--至今)

中国现场统计研究会因果推断分会常务理事(2022年--至今)

天津现场统计研究会常务理事(2022年--至今)

泛华统计学会永久会员(2019年--至今)

北京应用统计学会理事(2019年--至今)

全国工业统计学教学研究会青年统计学家协会理事(2019年--至今)

中国现场统计研究会生存分析分会副秘书长 (2018年--至今).

Associate Editor, Journal of Nonparametric Statistics (2017年--至今).

中国现场统计研究会生物统计分会理事  (2017年--至今).

担任美国《Mathematical Reviews》 特约评论员  (2015年--至今).

担任JASA, Biometrika, Statistica Sinica, SCIENCE CHINA Mathematics, Computational Statistics and Data Analysisa, Journal of Applied Statistics, Journal of Nonparametric Statistics, Statistical Theory and Related Fields,系统科学与数学,中国科学,Journal of Statistical Simulation and Computation, Computers and Industrial Engineering,Statistics and Probability Letters 等杂志的审稿人。

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

本科生课程

数理统计2，2021年秋季

数学分析3，2020年秋季

数学分析3，2019年秋季

研究生课程

统计模型，  2021年春季

高等统计II，2020年春季

高等统计II，2019年春季

统计推断，  2018年秋季

高等统计II，2018年春季

统计推断，  2017年秋季

主持项目

2023.1-2026.12  国家自然科学基金面上项目，几类复杂高维大数据的稀疏学习与融合分析.

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.

[64] Yajie Mi#(硕士) and Lei Wang*. Journal of Applied Statistics, revised.  

[63]   Ly Ni,  Jinyi Wang, Jun Shao and Lei Wang*. Statistica Sinica, revised.  

[61] Yaohong Yang#(硕士)，Lei Wang* and Weihua Zhao. Computational Statistics and Data Analysis, revised.  

[60] Zhaohan Hou#(硕士) and Lei Wang*. TEST, revised.  

[59] Wei  Ma#(博士)，Lei Wang* and Heng Lian. Statistica Sinica, revised.  

[58] Dongyu Li#(硕士) and Lei Wang*. TEST, revised.  

[56] Junzhuo Gao#(硕士) and Lei Wang* Communication-efficient distributed estimation of partially linear models for large-scale data. Information Sciences, revised.

[55] Yanjing Peng#(硕士) and Lei Wang*. Journal of Systems Science and Complexity, to appear. 

[54] Xudong Zhang#(硕士)，Ting Zhang and Lei Wang*. Statistics, to appear.  

[53] Jun Shao, Jinyi Wang and Lei Wang*. SCIENCE CHINA Mathematics, to appear. 

[52] Junzhuo Gao#(硕士), Lei Wang* and Heng Lian.  SCIENCE CHINA Mathematics, to appear.  

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

[50] Baofang Ke#(博士), Lei Wang* and Weihua Zhao. Smoothed tensor quantile regression estimation for longitudinal data. Computational Statistics and Data Analysis, to appear.

[49] 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,  to appear.

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

[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.

【2019年】

[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.

邀请报告,   华东师范大学,  上海, 中国, 2019.

邀请报告,   上海财经大学,  上海, 中国, 2019.

邀请报告,   复旦大学,  上海, 中国, 2019.

邀请报告,   首都师范大学,  北京, 中国, 2019.

邀请报告,   人民大学,  北京, 中国, 2019.

邀请报告,   首都经贸大学中国现场统计40周年纪念,  上海, 中国, 2019.

邀请报告,   IMS China,  大连, 中国, 2019.

邀请报告,   ICSA China,  天津, 中国, 2019.

邀请报告,   大数据与现代统计国际研讨会,  上海, 中国, 2019.

邀请报告,   北京大学,  北京, 中国, 2019.

邀请报告,   中国现场统计研究会生存分析分会,  临汾, 中国, 2019.

邀请报告,   中国现场统计研究会高维数据统计分会第五届学术研讨会,  杭州, 中国, 2019.

邀请报告,   ICSA Data Science,  西双版纳, 中国, 2019.

邀请报告,   第十届全国概率统计年会,  成都, 中国, 2018.

邀请报告,   统计学与数据科学青年学者论坛,  北京, 中国, 2018.

邀请报告,   有限混合模型及复杂模型,  桂林, 中国, 2018.

邀请报告,   ICSA focus on data science,  青岛, 中国, 2018.

邀请报告,   南开大学--伯明翰大学联合讨论会,  南开大学, 中国, 2018.

邀请报告,   现代统计学研讨会,  厦门大学, 中国, 2017.

邀请报告,   核心数学与组合数学教育部重点实验室汇报会,  南开大学, 中国, 2017.

邀请报告,   概率统计青年学者论坛,  南开大学, 中国, 2017.

邀请报告,   18th Meeting of New Researchers in Statistics and Probability,  威斯康辛麦迪逊大学, 美国, 2016.

NSF Conference: Statistics for Complex Systems, 威斯康辛麦迪逊大学, 美国, 2015.

邀请报告, 第三届统计概率年会, 江苏师范大学, 徐州, 2014.

41st Annual Meeting of the Statistical Society of Canada, 埃尔伯塔大学, 加拿大, 2013.

International Workshop on the Perspectives on High-dimensional Data Analysis II, 英属哥伦比亚大学, 加拿大, 2013.

邀请报告, 泛长三角应用统计学术年会, 华东师范大学, 上海, 2011.

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

王磊的个人主页

http://web.stat.nankai.edu.cn/lwang/