教育背景

2011.08-2015.06 中国海洋大学，信息与计算科学，理学学士

2015.09-2021.06 厦门大学，统计学，理学博士

工作经历

2021.07-2023.09 山东大学，特别资助类博士后

2022.02-2023.02 Hong Kong Baptist University，Post-Doctoral Research Fellow

2023.09-至今 北京师范大学珠海校区，讲师

研究方向

高维数据分析、函数型数据分析、迁移学习、多源数据分析、Meta 分析等

科研项目

1. 中国博士后科学基金面上资助，带样本网络先验信息的函数型数据回归方法, 2021.11-2023.09，主持

2. 山东省自然科学基金青年项目，异质高维数据分析方法及其应用研究, 2023.01-2025.12，主持

发表论文

[1] Xiaochen Zhang, Qingzhao Zhang, and Kuangnan Fang. (2024). Functional linear model with prior information of subjects’ network[J]. Journal of Computational and Graphical Statistics, in press.

[2] Xiaochen Zhang, Qingzhao Zhang, Shuangge Ma, and Kuangnan Fang. (2022). Subgroup analysis for high-dimensional functional regression. Journal of Multivariate Analysis, 192: 105100.

[3] Xiaochen Zhang, Kuangnan Fang, and Qingzhao Zhang. (2022). Multivariate functional generalized additive models. Journal of Statistical Computation and Simulation, 92(4): 875-893.

[4] Xiaochen Zhang, Qingzhao Zhang, Xiaofeng Wang, Shuangge Ma, and Kuangnan Fang.  (2020). Structured sparse logistic regression with application to lung cancer prediction using breath volatile biomarkers. Statistics in Medicine, 39(7), 955-967.

[5] Kuangnan Fang, Xiaochen Zhang, Shuangge Ma, and Qingzhao Zhang. (2020). Smooth and locally sparse estimation for multiple-output functional linear regression. Journal of Statistical Computation and Simulation, 90(2), 341-354.

[6] Kuangnan Fang, Peng Wang, Xiaochen Zhang, and Qingzhao Zhang. (2022). Structured sparse support vector machine with ordered features. Journal of Applied Statistics, 49(5), 1105-1120.