教育背景

2002.09-2005.06，中国科学院研究生院概率论与数理统计专业，理学博士学位

1999.09-2002.06，中国人民大学概率论与数理统计专业，理学硕士学位

1992.09-1996.06，南开大学概率论与数理统计专业，理学学士学位

 

工作经历

2013.08至今，中国人民大学统计学院，教授

2008.08-2013.08，中国人民大学统计学院，副教授

2005.08-2008.08，中国人民大学统计学院，讲师

 

研究方向

函数型数据分析，多模态数据融合分析，单细胞测序及空间转录组数据分析

 

科研项目

1.基于多模态数据构建心脏骤停患者神经功能预后预测模型研究 子课题 （国家自然科学基金项目）2023-2026

 

科研发表

19，Zhou Rou,Wang Dongxue, Zhang Jingxiao, Kernel partial least squares regression for functional nonlinear models, Journal of Multivariate Analysis(2026,accepted)

18, Zichang Li,Xiangjie Li, Jingxiao Zhang,Xinyi Xu,  SpaJoint: a transfer learning method folspatial transcriptomics deconvolution,Briefings in Bioinformatics(2026,accepted)

17，Qiao nan, Li, W., Zhang, J., and Chen, C. (2026). Scalable and distributed indi

vidualized treatment rules for multicenter datasets. Biometrics,（2026，82(1)）

16，Sheng Fang, Xiaokang Yu, Xinyi Xu, Jingxiao Zhang,, Xiangjie Li, scHSC: enhancing single-cell RNA-seq clustering via hard sample contrastive learning,Briefings in Bioinformatics, （2025, 26(5)）

15. Xinran Chen, Jingxiao Zhang, Rou Zhong, Nonlinear Principal Component Analysis for Two-Dimensional Functional Data Using Neural Networks, Statistics and Computing (2025）

14. Rou Zhong, Jingxiao Zhang, Chunming Zhang, Nonlinear functional principal component analysis using neural networks, Journal of Multivariate Analysis. (2025)

13. Shishi Liu, Chunming Zhang, Hao Zhang, Rou Zhong and Jingxiao Zhang, Model Averaging Estimation for Partially Linear Functional Score Models , Statistica Sinica（2021, online）

12. Xia Junwen, Zhan Zishu , Zhang Jingxiao ,Doubly robust estimation of optimal treatment regimes for survival data using an instrumental variable, Statistics and Computing (2024， 34:96）

11. Zishu Zhan，Xiangjie Li，Jingxiao Zhang，Partial replacement imputation estimation for partially linear models with complex missing pattern covariates，Statistics and Computing (2023， 33:88）

10. Rou Zhong, Chunming Zhang, Jingxiao Zhang，LOCALLY SPARSE ESTIMATOR OF GENERALIZED VARYING COEFFICIENT MODEL FOR ASYNCHRONOUS LONGITUDINAL DATA，Statistica Sinica（2023,online）

9. Xiaokang Yu, Xinyi Xu, Jingxiao Zhang，Xiangjie Li， Batch alignment of single-cell transcriptomics data using deep metric learning，Nature Communications (2023 )

8. Rou Zhong , Shishi Liu , Haocheng Li , Jingxiao Zhang，Sparse logistic functional principal component analysis for binary data，Statistics and Computing (2023， 33:15）

7. Xinyi Xu, Xiaokang Yu, Gang Hu, Kui Wang, Jingxiao Zhang and Xiangjie Li，Propensity score matching enables batch-effectcorrected imputation in single-cell RNA-seq analysis，Briefings in Bioinformatics（2022, 23(4)）

6. Rou Zhong , Shishi Liu , Haocheng Li , Jingxiao Zhang，Robust functional principal component analysis for non-Gaussian longitudinal data，Journal of Multivariate Analysis （2022，189）

5. Xiangjie Li, Kui Wang, Yafei Lyu, Huize Pan, Jingxiao Zhang, Dwight Stambolian, Katalin Susztak, Muredach P. Reilly, Gang Hu, Mingyao Li. Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis, Nature Communications (2020) 

4. Xinyi Xu, Xiangjie Li, Jingxiao Zhang， Regularization Methods for High-Dimensional Sparse Control Function Models， Journal of Statistical Planning and Inference (2020（206）111-126)

3. Lei Wang, Xuejun Ma, Jingxiao Zhang, Feature Screening for Ultrahigh-dimensional Additive Logistic Models, Journal of Statistical Planning and Inference (2020（205）306-317)

2. Xiangjie Li, Xuejun Ma, Jingxiao Zhang, Conditional Quantile Correlation Screening Procedure For Ultrahigh-dimensional Varying Coefficient Models, Journal of Statistical Planning and Inference, (2018)

1. Xuejun Ma,Jingxiao Zhang, Robust model-free feature screening via quantile correlation, Journal of Multivariate Analysis(2016,Vol.143,page 472-480)

 

著作教材

1.张波、张景肖编著，《应用随机过程》，清华大学出版社，2004；

2.张景肖编著，《概率论》，清华大学出版社，2012；

3.张景肖著，《随机最优控制及其在保险中的应用》，科学出版社，2013；

4.肖宇谷、张景肖，《应用随机过程》，高等教育出版社，2017；

5.肖宇谷、张景肖编著，《寿险随机精算模型》，清华大学出版社，2016；

6.张波、张景肖、肖宇谷编著，《应用随机过程（第二版）》，清华大学出版社，2019；

7.张景肖、张波、殷弘编著，《概率论与数理统计》，中国人民大学出版社，2025。

 

教学课程

本科课程：统计学