王江峰，男，博士(后)，浙江工商大学统计学教授，博士生导师，校西湖学者拔尖人才，全国工业统计学教学研究会第九界、第十届理事(国家一级协会)，教育部学位委员会学位论文评审专家，国家社会科学基金评审和成果鉴定专家。2004 年浙江大学概率统计专业毕业，获硕士学位；2010 年同济大学数理统计专业毕业，获博士学位；2012 年同济大学经管学院博士后出站；2018 年在加拿大滑铁卢大学统计与精算系访问一年；2023年在华东师范大学统计学院访问一年。

研究方向：时空数据分析、复杂生存数据分析、高维数据分析、分位数回归方法、非参和半参数方法等。主持国家社科基金一般项目3项，以及教育部人文社科基金等省部级一般或重点项目5项；在《中国科学》、《数学学报》(中，英文版)、《数学进展》、《IEEE Trans. Cybern》、《Front. Math. China》、《Statistics》、《J. Statist. Plann. Inference》、《Statist. Papers》、《Adv. Statist. Anal》、《Statist. Probab. Lett》等期刊上发表论文50余篇，其中特级、一级以及 SCI/SSCI收录的论文40余篇。

时空数据分析、复杂生存数据分析、高维数据分析、分位数回归方法、非参和半参数方法等

l  2007/03-2010/06， 同济大学，   数学科学学院， 数理统计方向，   博士， 导师：梁汉营教授

l  2001/09-2004/03， 浙江大学，   数学科学学院， 概率统计专业，   硕士， 导师：张立新教授

l  1997/09-2001/06， 江西师范大学， 数学与统计学院，数学教育专业，   学士

 2023/09-2024/06,  华东师范大学，   统计学院，    访问学者

 2019/12-至今，   浙江工商大学，   统计与数学学院， 教师，   教授、系副主任、研究所所长

 2018/01-2019/01， 加拿大滑铁卢大学， 统计与精算系，  访问学者， 合作导师：Grace.Y.Yi教授

 2013/04-2019/12， 浙江工商大学，   统计与数学学院， 教师，    副教授

 2010/06-2012/10， 同济大学，      经济与管理学院， 博士后，  合作导师：马卫民教授

 2004/03-2013/04, 杭州师范大学，   数学学院，    教师，    讲师

l全国工业统计学教学研究会第十届理事会理事(国家一级学会), 2023.01-2026.12

l国家社科基金通讯评审专家、成果鉴定专家

l教育部学位委员会学位论文评审专家

研究生的课程：《生存数据下的统计推断》、《统计学理论方法》、《论文写作指导》

博士生的课程：《概率极限理论基础》、《统计学理论前沿B》、《生存数据统计分析B》

[41].Xin Wang, Jiang-Feng Wang*, Jun Cheng, Michael V. Basin*, Dan Zhang and Yu Fu. NN-Based Event-Triggered Protocol for NCSs Under DoS and Unknown Deception Attacks. IEEE Transactions on Cybernetics, Accepted (Corresponding author)

[40]. Ke-Ang Fu, Hao Chen and Jiang-Feng Wang*. Asymptotic properties of the global self-weighted M-estimator for ARMA(p, q) models with infinite variance. Communications in Statistics –Theory and Methods, Accepted (Corresponding author)

[39]. Xinyi Xu, Jiangfeng Wang*, Kang Hu, Shan He and Yu Xia. Spatial local linear quantile regression under association，Statistics and probability Letters, 2026，228：110573

[38]. Zhenmin Rao, Jiang-Feng Wang*, Kang Hu and Shan He. Least squares estimators of general linear model with censoring indicators missing at random. Acta Mathematica Scientia (Chinese), 2025, 45A(3): 919–933

[37]. Ke-Ang Fu, Yang Liu and Jiang-Feng Wang*. Precise large deviations in a non-stationary risk model with arbitrary dependence between subexponential claim sizes and waiting times. Communications in Statistics –Theory and Methods, 2024, 53(11): 4116-4126 (Corresponding author)

[36]. Ke-Ang Fu and Jiang-Feng Wang*. Moderate deviations for a Hawkes-type risk model with arbitrary dependence between claim sizes and waiting times. Communications in Statistics –Theory and Methods, 2023, 52(17): 6266-6274  (Corresponding author)

[35]. Zhen-Min Rao, Jiang-Feng Wang*, Ding-Kai Chen and Lei Wang. Robust estimators and variable selection for partially linear models with censoring indicators missing at random. Applied Mathematics A Journal of Chinese Universities (Chinese), 2023,38(1):1-17 (Corresponding author)

[34].Hong-Xia Xu, Guo-Liang Fan and Jiang-Feng Wang. Jackknife empirical likelihood for the error variance in linear errors-in-variables models with missing data. Communications in Statistics –Theory and Methods. 2022, 51(14): 4827-4840. 

[33]. Jiang-Feng Wang*, Yang-Cheng Zhou and Ju Tang. Weighted local polynomial estimations of a non-parametric function with censoring indicators missing at random and its application.  Front. Math. China, 2022, 17(1): 117-139.  SCI

[32]. Ke-Ang Fu, Yang Liu and Jiang-Feng Wang*. Precise large deviations in a bidimensional risk  model with arbitrary dependence between claim-size vectors and waiting times. Statistics and probability Letters, 2022, 184: 109365. SCI和SSCI双检索(通讯作者)

[31]. Guo-Liang Fan, Shi-Wen Rao and Jiang-Feng Wang*. Empirical likelihood estimation for partially nonlinear varying coefficient errors-in-variables models with missing data. Journal of System Science and Mathematical Science (Chinese),2021, 41(9): 2643-2659. 国内一级

[30]. Jiang-Feng Wang*, Guo-Ding Li, Ying-Lei Li and Yi Xiong. Weighted double-kernel local linear estimators of conditional quantiles with censoring indicators missing at random. Journal of System Science and Mathematical Science (Chinese),2021, 41(9): 2621-2642. 国内一级

[29]. Jiang-Feng Wang*, Wei-Jun Jiang, Fang-Yin Xu and Wu-Xin Fu. Weighted composite quantile regression with censoring indicators missing at random. Communications in Statistics –Theory and Methods，2021, 50(12): 2900-2917.  SCI

[28]. Yang-Cheng Zhou,Jiang-Feng Wang*, Wen-Wen Yuan and Hui-Li Zhang. Weighted kernel estimators of conditional quantiles with censoring indicators missing at random. Applied Mathematics A Journal of Chinese Universities (Chinese), 2020, 35(4): 379-392. 国内一级 

[27]. Jiang-Feng Wang*, Yang-Cheng Zhou and Ju Tang. Weighted local polynomial estimations of a non-parametric function with censoring indicators missing at random and its application.  Advances in Mathematics (Chinese), 2020, 49(4): 463-480.  国内一级

[26]. Ke-ang Fu, Meng-xue Wu, Wei Huang and Jiang-Feng Wang*. Asymptotics for the self-weighted LAD estimator of ACD models. Applied Mathematics A Journal of Chinese Universities (Chinese), 2020, 35(3): 253-264.   国内一级

[25]. Hong-Xia Xu, Zhen-Long Chen and Jiang-Feng Wang. Quantile regression and variable selection for partially linear model with randomly truncated data. Statistical Papers. 2019, 60(4): 1137–1160. SCI 

[24]. Jiang-Feng Wang*, Liang-Hua Qiu and Hui-Zeng Zhang. Weighted local composite quantile regression estimation in non-parametric regression model under right-censored data. Applied Mathematics A Journal of Chinese Universities (Chinese), 2019, 34(1): 11-24.  国内一级

[23] Jiang-Feng Wang*, Guo-Liang Fan and Li-Min Wen. Composite quantile regression estimators of regression function with censoring indicators missing at random. Journal of System Science and Mathematical Science (Chinese), 2018, 38(11): 1347-1362.  国内一级

[22]. Mei Yao, Jiang-Feng Wang* and Lu Lin. Double-kernel local linear estimator of conditional quantile under left-truncated and dependent data. Acta Mathematica Sinica (Chinese), 2018,61(6): 963-980.  国内一级 

[21].Hong-Xia Xu, Guo-Liang Fan, Zhen-Long Chen and Jiang-Feng Wang.Weighted quantile regression and testing for varying-coefficient models with randomly truncated data. Advances in Statistical Analysis. 2018,102(4)：565–588.  SCI 

[20]. Mei Yao, Jiang-Feng Wang*, Lu Lin and Yu-Xin Wang. Variable selection and weighted composite quantile estimation of regression parameters with left-truncated data. Communications in Statistics –Theory and Methods. 2018, 47(18):4469-4482.  SCI  

[19].Guo-Liang Fan, Zhi-Qiang Jiangand Jiang-Feng Wang*. Empirical likelihood for high-dimensional partially linear model with martingale difference errors. Communications in Statistics – Theory and Methods. 2017, 46(22):11228-11242.  SCI  

[18]. Lin-Na Zhang, Li-Min Wen, Jiang-Feng Wang and Wei Wang. Evaluation of individual RBNS loss reserving based on generalized linear model. Acta Mathematicae Applicatae Sinica (Chinese)，2017,40(4): 573-593.  国内一级

[17]. Mei Yao, Jiang-Feng Wang* and Lu Lin. Asymptotic normality for a nonparametric estimator of conditional quantile with left-truncated data. Communications in Statistics – Theory and Methods. 2017, 46(13): 6280-6292.  SCI  

[16]. Yi Zhang, Li-Min Wen, Jiang-Feng Wang and Wei Wang. The Credibility Estimation of Accident Year Mean in the Model of Stochastic B-F Reserve. Acta Mathematicae Applicatae Sinica (Chinese)，2016, 39(2): 306-320.  国内一级

[15]. Jiang-Feng Wang, Xiao-Min Tian, Hui-Zeng Zhang and Li-Min Wen. Composite quantile regression estimation in non-parametric regression model under left-truncated data.Applied Mathematics A Journal of Chinese Universities (Chinese), 2015, 30: 71-83. 国内一级

[14] .Jiang-Feng Wang, Wei-Min Ma, Guo-Liang Fan and Li-Min Wen. Local linear quantile regression with truncated and dependent data. Statistics and probability Letters, 2015, 96 (1): 232-240.  SCI

[13]. Jiang-Feng Wang, Wei-Min Ma, Hui-Zeng Zhang and Li-Min Wen. Asymptotic normality for a local

composite quantile regression estimator of regression function with truncated data.Statistics and Probability

Letters. 2013，83: 1571-1579.  SCI

[12]. Guo-Liang Fan, Han-Ying Liang and Jiang-Feng Wang. Statistical inference for partially time-varying coefficient errors-in-variables models. Journal of Statistical Planning and Inference. 2013,143(3): 505-519. SCI   

[11]. Jiang-Feng Wang, Han-Ying Liang and Guo-Liang Fan. Local polynomial quasi-likelihood regression with truncated and dependent data. Statistics.2013, 47(4): 744-761.  SCI

[10]. Guo-Liang Fan, Han-Ying Liang and Jiang-Feng Wang. Empirical likelihood for heteroscedastic partially linear errors-in-variables model with a-mixing errors. Statistical Papers. 2013, 54(1): 85-112.  SCI

[9]. Li-Min Wen,Jiang-Feng Wang and Xian-Yi Wu.  A new class of credibility estimators under the generalized weighted premium principle. Communications in Statistics – Theory and Methods. 2013,42(3): 447–465. SCI 

[8]. Jiang-Feng Wang, Han-Ying Liang and Guo-Liang Fan. Local M-estimation of nonparametric regression with left-truncated and dependent data. Science China, Mathematics, (Chinese), 2012, 42(10): 995-1015. 特级期刊

[7]. Jiang-Feng Wang and Han-Ying Liang. Asymptotic properties for an M-estimator of regression function with truncation and dependent data. Journal of the Korean Statistical Society. 2012, 41(3): 351-367.  SCI

[6].Guo-Liang Fan, Han-Ying Liang and Jiang-Feng Wang. Empirical likelihood for heteroscedastic partial linear errors-in-variables model.  Communications in Statistics – Theory and Methods.  2012,41:108-127. SCI

[5].Jiang-Feng Wang, Han-Ying Liang and Guo-Liang Fan. Asymptotic properties of conditional quantile estimator under left truncated and a-mixing conditions. Communications inStatistics – Theory and Methods.  2011,40: 2462-2486.  SCI

[4]. Guo-Liang Fan, Han-Ying Liang, Jiang-Feng Wang and Hong-Xia Xu. Asymptotic properties for LS estimators in EV regression model with dependent errors. Advances in Statistical Analysis. 2010,94:89-103. SCI

[3].Jiang-Feng Wang and Han-Ying Liang. A note on the almost sure central limit theorem for negatively associated fields. Statistics and Probability Letters. 2008, 78: 1964–1970. SCI 

[2]. Jiang-Feng Wang* and Feng-Bin Lu. Inequalities of maximum of partial sums and weak convergence for a class weak dependent random variables. Acta Mathematica Sinica, English Series. 2006, 22(3): 693-700. SCI   

[1]. Li-Xin Zhang and Jiang-Feng Wang*.A note on complete convergence of pairwise NQD random sequence. Applied Mathematics A Journal of Chinese Universities (Chinese). 2004, 19(2): 203-208. 

王江峰著. 左截断数据下的统计推断. 浙江工商大学出版社, 2022.（学校认定A类专著）

[1]. 大数据背景下统计学专业博士研究生创新人才培养模式的改革与实践，浙江省高等教育“十四五”研究生教学改项目,

   2025年1月——2026年12月，正主持

[2]. 思政理念下《概率论》课程教学改革思路及实现机制的探索与实践，浙江省高等学校课程思政教学研究项目, 

    2022.9—2024.8. 已结题，主持

[3]. 基于MOOC的《概率论》混合式教学模式研究, 省级平台校级教学项目，已结题，主持，2020.

[4].《概率论》课程思政课堂教学改革的探索与研究，校级本科教学改革项目，已结题，主持，2021.

[1]. 浙江省“十三五”新形态教材《概率论与数理统计》，共同主编，浙江工商大学出版社，2021.

[2]. 浙江省普通本科高校“十四五”重点教材《概率论与数理统计》，共同主编，浙江工商大学出版社，2024.

[3]. 浙江省“十四五”普通高等教育本科规划教材《概率论与数理统计》(第三版)，共同主编，浙江工商大学出版社，2024.

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[2].基于BSP理念的统计学研究生应用能力培养模式探索与实践，浙江省教学成果奖二等奖，参与，2022.

[3].主讲课程《概率论》获得国家首批一流课程建设项目，2020   

[4].主讲课程《概率论》获得浙江省首批思政示范课程建设项目，2021