Education

Sep. 2002 – Jun. 2005, Graduate University of the Chinese Academy of Sciences, Probability and Mathematical Statistics, Ph.D. in Science

Sep. 1999 – Jun. 2002, Renmin University of China, Probability and Mathematical Statistics, M.S. in Science

Sep. 1992 – Jun. 1996, Nankai University, Probability and Mathematical Statistics, B.S. in Science

Work Experience

Aug. 2013 – Present, Professor, School of Statistics, Renmin University of China

Aug. 2008 – Aug. 2013, Associate Professor, School of Statistics, Renmin University of China

Aug. 2005 – Aug. 2008, Lecturer, School of Statistics, Renmin University of China

Research Interests

Functional Data Analysis, Multimodal Data Fusion Analysis, Single-Cell Sequencing Data Analysis, Spatial Transcriptomics Data Analysis

Funding

1. Subproject of "Research on Prognostic Prediction Model of Neurological Function in Patients with Cardiac Arrest Based on Multimodal Data" (National Natural Science Foundation of China), 2023–2026

Publications

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 for spatial transcriptomics deconvolution. Briefings in Bioinformatics, 2026 (accepted).

17. Qiao Nan, Li W., Zhang J., Chen C. Scalable and distributed individualized 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, 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, Xiangjie Li. Propensity score matching enables batch-effect-corrected 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, 143:472–480.

Books and Textbooks

1. Bo Zhang, Jingxiao Zhang. Applied Stochastic Processes. Tsinghua University Press, 2004.

2. Jingxiao Zhang. Probability Theory. Tsinghua University Press, 2012.

3. Jingxiao Zhang. Stochastic Optimal Control and Its Application in Insurance. Science Press, 2013.

4. Yugu Xiao, Jingxiao Zhang. Applied Stochastic Processes. Higher Education Press, 2017.

5. Yugu Xiao, Jingxiao Zhang. Stochastic Actuarial Models for Life Insurance. Tsinghua University Press, 2016.

6. Bo Zhang, Jingxiao Zhang, Yugu Xiao. Applied Stochastic Processes (2nd Edition). Tsinghua University Press, 2019.

7. Jingxiao Zhang, Bo Zhang, Hong Yin. Probability and Mathematical Statistics. Renmin University of China Press, 2025.

Teaching

Undergraduate Course: Statistics