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。

研究方向：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。主持国家社科基金面上项目2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》、《系统科学与数学》、《Front. Math. China》、《Statistics》、《J. Statist. Plann. Inference》、《Statist. Papers》、《Adv. Statist. Anal》、《Statist. Probab. Lett》等期刊上发表论文40余篇，其中特级、一级以及 SCI/SSCI收录的论文近40篇。

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

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

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

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

l  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

l  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九届理事会理事(国家一级学会),  2018.12-2022.12

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美国数学学会评论员    评论号: 092654

l教育部学位委员会学位论文评审专家

[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, Accepted. SCI  

[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. Accepted.  SCI  (通讯作者)

[35].  Zhen-Min Rao, Jiang-Feng Wang*, Ding-Kai Chen and Lei Wang.Robust estimators and variabe selection for partially linear modelswith censoring indicators missing at random. Applied Mathematics A Journal of Chinese Universities (Chinese), 2023，38(1):1-17. 国内一级

[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.  SCI 

[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]. 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. 在研，主持

[2]. 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，在研，主持，2020.

[3].《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，在研，主持，2021.

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.

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.