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

研究方向：生物统计、高维数据统计、贝叶斯统计、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　必赢线路检测3003，管理科学与工程，博士后

2003.06－2006.06　华中科技大学必赢3003no1线路检测中心，概率论与数理统计，博士

2000.09－2003.06　华中科技大学必赢3003no1线路检测中心，概率论与数理统计，硕士

（2）工作经历：

2024.06－至今　 必赢线路检测3003，必赢3003no1线路检测中心统计学系，教授，博士生导师

2016.09－2024.06　 必赢线路检测3003，理学院统计学系，教授，博士生导师

2008.09－2016.09　必赢线路检测3003，理学院统计学系，副教授，硕士生导师

2006.06－2008.09　必赢线路检测3003，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，必赢线路检测3003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，必赢线路检测3003出版社，2022．

3．主编出版《应用数理统计》研究生公共课教材，必赢线路检测3003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] Zihao Yuan, Jiaqing Chen*, Han Qiu, Houxiang Wang, Yangxin Huang, Fuchun Lin. Co-activation pattern analysis based on hidden semi-markov model for brain spatiotemporal dynamics. IEEE transactions on medical imaging, 2025, doi10.1109/TMI.2025.3607113

[2] Feng Gu, Jiaqing Chen*, Jinjing Wang, Yibo Long, Xiaofan Wang, Yangxin Huang. Bayesian expectile joint model with varying coefficient for longitudinal and semi-competing Risks Data. Statistics in Medicine, 2025, doi10.1002/sim.70219

[3] Jiaxi Xie, Jiaqing Chen*, Yunjing Wang and Yangxin Huang. Bayesian double penalized quantile regression based on linear mixed effects model for longitudinal count data. Journal of Statistical Computation and Simulation. 2025, 95(15): 3175–3208

[4] Yunjing Wang, Jiaqing Chen*, Jiaxi Xie and Yangxin Huang. Bayesian weighted quantile joint model for longitudinal and semi-competing risks data. Journal of Statistical Computation and Simulation. 2025, doi10.1080/ 0094 9655. 2025. 2 591479

[5] Jiaqing Chen, Fangyi Wan, HanQiu, and Zihao Yuan. Linear mixed effects double penalized Lp-quantile regression model for longitudinal data. Communications in Statistics - Theory and Methods, 2025, doi10.1080/03610 926. 2025. 253 1411

[6] Jinjing Wang, Jiaqing Chen*, Feng Gu, Yibo Long, Xiaofan Wang, and Yangxin Huang. Bayesian weighted composite quantile regression for multivariate semi-continuous longitudinal data. Communications in Statistics -Theory and Methods, 2025, doi10.1080/03610926.2025.2517285  

[7] Mingyu Zhang, Jiaqing Chen*. SST-YOLOv5s: advancing real-time blood cell object detection through multi-headed attention mechanism. Signal, Image and Video Processing, 2025, 19(3): 219.

[8] Houxiang Wang#, Jiaqing Chen#, Zihao Yuan, Yangxin Huang, Fuchun Lin. NHSMM-MAR-sdNC: A novel data-driven computational framework for state-dependent effective connectivity analysis. Medical Image Analysis, 2024, 97(2024): 103290.

[9] Zihao Yuan, Jiaqing Chen*, Han Qiu, Houxiang Wang, Yangxin Huang. Adaptive sufficient sparse clustering by controlling false discovery. Statistics and Computing, 2024, 34(6): 193.

[10] Han Qiu, Jiaqing Chen*, Zihao Yuan. Quantile correlation‐based sufficient variable screening by controlling false discovery rate. Advanced Theory and Simulations, 2024, 7(5): 2301099.

[11] Houxiang Wang, Jiaqing Chen*, Zihao Yuan, Yangxin Huang, Fuchun Lin*. A novel method for sparse dynamic functional connectivity analysis from resting-state fMRI. Journal of Neuroscience Methods, 2024, 411 (2024): 110275.

[12] Jiaqing Chen, Yangxin Huang, Qing Wang. Semiparametric multivariate joint model for skewed-longitudinal and survival data: A Bayesian approach. Statistics in Medicine, 2023, 42: 4972-4989.

[13] Zihao Yuan, Jiaqing Chen*, Han Qiu, Yangxin Huang. Quantile adaptive sufficient variable screening by controlling false discovery. Entropy, 2023, 25(3): 524.

[14] Jiaqing Chen, Yangxin Huang, Nian-Sheng Tang. Bayesian change-point joint models for multivariate longitudinal and time-to-event data. Statistics in Biopharmaceutical Research, 2022, 14(2): 227-241.

[15] Yangxin Huang#, Jiaqing Chen#, Lan Xu, Nian-Sheng Tang. Bayesian joint modeling of multivariate longitudinal and survival data with an application to Diabetes Study. Frontiers in Big Data, 2022, 5: Article 812725.

[16] Yuxia Zhao, Hong Mei, Yangxin Huang, Jiaqing Chen*. 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.

[17] Yangxin Huang, Nian-Sheng Tang, Jiaqing Chen. Multivariate piecewise joint models with random change-points for skewed-longitudinal and survival data. Journal of Applied Statistics, 2022, 49(12): 3063-3089.

[18] Yangxin Huang, Jiaqing Chen*, Lan Xu, Hanze Zhang, Yuanyuan Lu. Bayesian MLIRT-based joint models for multivariate longitudinal and survival data with multiple features. Journal of Medical Statistics and Informatics, 2021, 9: Article 4.

[19] Xiaosun Lu, Yangxin Huang, Jiaqing Chen, Rong Zhou, Shuli Yu, Ping Yin. 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.

[20] Yangxin Huang, Xiaosun Lu, Jiaqing Chen, Juan Liang, Miriam Zangmeister. 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.

[21] Yangxin Huang, Jiaqing Chen*, Huahai Qiu. 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.

[22] Yangxin Huang, Jiaqing Chen*, Ping Yin. Hierarchical mixture models for longitudinal immunologic data with heterogeneity, non-normality, and missingness. Statistical Methods in Medical Research, 2017，26(1): 223-247.

[23] Yangxin Huang, Jiaqing Chen*. 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.

[24] Jiaqing Chen, Yangxin Huang. 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经济与金融统计分会常务理事；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；中国现场统计研究会多元分析应用专业委员会常务理事；湖北省统计学会常务理事等。