陈家清
发布日期:2023-09-21一、个人基本情况
姓名:陈家清
性别:男
职称/职务:教授/学院副院长
学位/学历:博士/研究生
硕/博生导师:博导
所在系: 统计学系
研究方向:生物统计、贝叶斯统计、高维数据统计、数据科学及其应用
电子邮箱:jqchenwhut@163.com, 9523@whut.edu.cn
二、教育背景与工作经历
(1)教育背景:
2009.04-2012.04 武汉理工大学,管理科学与工程,博士后
2003.06-2006.06 华中科技大学数学与统计学院,概率论与数理统计,博士
2000.09-2003.06 华中科技大学数学与统计学院,概率论与数理统计,硕士
(2)工作经历:
2024.06-至今 武汉理工大学,数学与统计学院统计学系,教授,博士生导师
2016.09-2024.06 武汉理工大学,理学院统计学系,教授,博士生导师
2008.09-2016.09 武汉理工大学,理学院统计学系,副教授,硕士生导师
2006.06-2008.09 武汉理工大学,理学院统计学系,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
三、教学研究
1.主编出版《随机过程基础》(第二版)统计专业教材,武汉理工大学出版社,2022.
2.主编出版《应用随机过程》(第二版)研究生公共课教材,武汉理工大学出版社,2022.
3.主编出版《应用数理统计》研究生公共课教材,武汉理工大学出版社,2013.
四、科学研究
(1)科研项目:
1.国家自然科学面上基金项目: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.湖北隆中实验室开放基金项目:面向新型陶瓷与智能复合材料的数据建模与分析技术研究,2024/01-2025/12,主持
5.湖北省自然科学基金面上项目: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
6.湖北省统计局重点科研项目: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
7.中国博士后基金面上项目:非线性门限自回归模型族贝叶斯分析及其在经济学中的应用,2010/ 04-2012/02,主持
8.湖北省统计局科研项目:对数伽玛分布参数的经验贝叶斯估计问题研究,2008/05-2009/05,主持
9.横向课题项目:非线性经济数据建模及数据挖掘技术研究,2016/04-2017/03,主持
10.横向课题项目:基于复杂纵向数据统计深度学习技术研究,2016/09-2018/07,主持
11.横向课题项目:基于贝叶斯统计的新药监测技术开发研究,2013/03-2014/12,主持
12.横向课题项目:水产E通系统软件开发,2013/03-2014/02,主持
13.横向课题项目,定海大桥引桥抗震性能分析与研究,2013/01- 2013/10,主持
(2)学术论文:
[1] Chen, J. et al. NHSMM-MAR-sdNC: A novel data-driven computational framework for state-dependent effective connectivity analysis. Medical Image Analysis, 2024, 97: 103290.
[2] Chen, J. et al. Adaptive sufficient sparse clustering by controlling false discovery. Statistics and Computing, 2024, 34 (6):193.
[3] Chen, J. et al. Quantile Correlation‐Based Sufficient Variable Screening by Controlling False Discovery Rate. Advanced Theory and Simulations, 2024, 7(5): 202301099.
[4] Chen, J. et al. A novel method for sparse dynamic functional connectivity analysis from resting-state fMRI. Journal of Neuroscience Methods, 2024, 411: 110275.
[5] Chen, J. et al. Bayesian Inference of Recurrent Switching Linear Dynamical Systems with Higher-Order Dependence.
Symmetry-Basel, 2024, 16(4): 474.
[6] Chen, J. et al. Semiparametric multivariate joint model for skewed-longitudinal and survival data: A Bayesian approach. Statistics in Medicine, 2023, 42: 4972-4989.
[7] Chen, J. et al. Quantile adaptive sufficient variable screening by controlling false discovery. Entropy, 2023, 25(3): 524.
[8] Chen, J. et al. Empirical Bayes decision for a generalized exponential distribution with contaminated data. Symmetry-Basel, 2023, 15(2): 511.
[9] 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.
[10] 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.
[11] 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.
[12] Chen, J. et al. Double penalized expectile regression for linear mixed effects model. Symmetry-Basel, 2022, 14(8): 1538.
[13] Chen, J. et al. The estimation of bent Line expectile regression model based on a smoothing technique, Symmetry-Basel, 2022, 14(7): 1320.
[14] 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.
[15] 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.
[16] 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.
[17] 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.
[18] 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.
[19] 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.
[20] 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.
[21] 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.
[22] 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.
[23] 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.
[24] 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.
(3)学术兼职:
中国现场统计研究会理事;全国工业统计学教学研究会理事;中国商业统计学会理事;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多元分析应用专业委员会常务理事;中国现场统计研究会旅游大数据分会常务理事;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;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;湖北省统计学会常务理事;湖北省工业与应用数学学会理事等。