姓名: 陈家清

性别: 男

出生年月:1972.11

职称/职务: 教授/统计学系主任

学位/学历: 博士/研究生

所在系: 统计学系

联系方式:jqchenwhut@163.com

个人简历

(一)教育经历

2009～2011 ok138cn太阳集团古天乐，管理科学与工程，博士后

2003～2006 华中科技大学数学与统计学院，概率论与数理统计，博士

2000～2003 华中科技大学数学与统计学院，概率论与数理统计，硕士

(二)工作经历

2016至今 ok138cn太阳集团古天乐ok138cn太阳集团古天乐，统计学系，教授，博士生导师

2008～2016 ok138cn太阳集团古天乐ok138cn太阳集团古天乐，统计学系，副教授，硕士生导师

2006～2008 ok138cn太阳集团古天乐ok138cn太阳集团古天乐，统计学系，讲师

2012.02～2013.02 University of South Florida公共卫生学院流行病与生物统计系访问学者

研究方向

生物统计、流行病与卫生统计、统计学习、贝叶斯统计

主要教学成果

1. 主编出版《随机过程基础》(第二版)统计专业教材，ok138cn太阳集团古天乐出版社，2022.

2. 主编出版《应用随机过程》研究生公共课教材，ok138cn太阳集团古天乐出版社，2014.

3. 主编出版《应用数理统计》研究生公共课教材，ok138cn太阳集团古天乐出版社，2013.

主要科研项目

1.国家自然科学面上基金项目(81671633):面向多特征纵向-生存数据建模及BFH推断研究，2017/01-2020/12,主持

2.横向课题项目:复杂纵向磁共振成像数据统计建模与分析技术研究，2022/08-2027/08，主持

3.中国科学院国家重点实验室开放基金项目:基于统计学习的大脑状态的静息态功能磁共振成像研究，2023/01-2025/12，主持

4.湖北省自然科学基金面上项目(2014CFB863):混合效应联合偏斜分布模型的HIV动力学及免疫抑制研究，2014/01-2015/12，主持

5.湖北省统计局重点科研项目(20132s0201):污染数据情况清形下刻度分布族参数的经验贝叶斯检验问题研究，2013/05-2014/04，主持

主要学术论文

[1] Chen, J. et al. Semiparametric multivariate joint model for skewed-longitudinal and survival data: A Bayesian approach. Statistics in Medicine, 2023, 42: 4972-4989.

[2] Chen, J. et al. Quantile adaptive sufficient variable screening by controlling false discovery. Entropy, 2023, 25(3): Article 524.

[3] Chen, J. et al. Empirical Bayes decision for a generalized exponential distribution with contaminated data. Symmetry-Basel, 2023, 15(2): Article 511.

[4] Chen, J. et al. Bayesian change-point joint models for multivariate longitudinal and time-to-event data. Statistics in Biopharmaceutical Research, 2022, 14(2): 227-241.

[5] Chen, J. et al. Multivariate piecewise joint models with random change-points for skewed-longitudinal and survival data. Journal of Applied Statistics, 2022, 49(12): 3063-3089.

[6] Chen, J. et al. Bayesian joint modeling of multivariate longitudinal and survival data with an application to Diabetes Study. Frontiers in Big Data, 2022, 5: Article 812725.

[7] Chen, J. et al. Double penalized expectile regression for linear mixed effects model. Symmetry-Basel, 2022, 14: Article 1538.

[8] Chen, J. et al. The estimation of bent Line expectile regression model based on a smoothing technique, Symmetry-Basel, 2022, 14: Article 1320.

[9] Chen, J. et al. Impairment of a NIK-SIX feedback axis results in dysregulation of intestinal immune homeostasis and promotes early-onset fatal spontaneous colitis. Iranian Journal of Immunology, 2022, 19(3): 263-277.

[10] Chen, J. et al. Bayesian MLIRT-based joint models for multivariate longitudinal and survival data with multiple features. Journal of Medical Statistics and Informatics, 2021, 9: Article 4.

[11] Chen, J. et al. Supervised functional data discriminant analysis for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(2): 841-851.

[12] Chen, J. et al. Bayesian joint analysis of heterogeneous- and skewed-longitudinal data and a binary outcome, with application to AIDS clinical studies. Statistical Methods in Medical Research，2018, 27(10): 2946–2963.

[13] Chen, J. et al. Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies. Lifetime Data Analysis, 2018, 24: 699–718.

[14] Chen, J. et al. Bayesian quantile regression for nonlinear mixed-effects joint models for longitudinal data in presence of mismeasured covariate errors. Journal of Biopharmaceutical Statistics. 2017, 27(5): 741–755.

[15] Chen, J. et al. Hierarchical mixture models for longitudinal immunologic data with heterogeneity, non-normality, and missingness. Statistical Methods in Medical Research，2017，26(1): 223-247.

[16] Chen, J. et al. Simultaneous Bayesian inference on a finite mixture of mixed-effects Tobit joint models for longitudinal data with multiple features. Statistics and Its Interface, 2017, 10:557–573.

[17] Chen, J. et al. Bayesian quantile regression-based nonlinear mixed-effects joint models for time-to-event and longitudinal data with multiple features，Statistics in Medicine，2016, 35: 5666-5685.

[18] Chen, J. et al. Bayesian approach to nonlinear mixed-effects quantile regression models for longitudinal data with non-normality and left-censoring. Journal of Advanced Statistics, 2016, 3(1): 109-121.

[19] Chen, J. et al. A Bayesian mixture of semiparametric mixed-effects joint models for skewed-longitudinal and time-to-event data，Statistics in Medicine，2015，34(20): 2820-2843.

主要学术兼职

中国现场统计研究会理事;全国工业统计教学研究会数字经济与区块链技术协会常务理事;中国现场统计研究会资源与环境统计分会常务理事;中国现场统计研究会经济与金融统计分会常务理事;中国现场统计研究会大数据统计分会常务理事;中国商业统计学会理事等。