Education

2012.09-2016.07, Ph.D. in Management, Guanghua School of Management, Peking University

2008.09-2012.07, B.A. in Management, Central University of Finance and Economics

 

Work Experience

2025.08-Present, Professor, School of Statistics, Renmin University of China

2020.08-2025.07, Associate Professor, School of Statistics, Renmin University of China

2018.08-2020.08, Lecturer, School of Statistics, Renmin University of China

2016.09-2018.08, Postdoctoral Fellow, School of Statistics, Renmin University of China

 

Research Interests

Medical image analysis; AI in healthcare; Healthcare big data analytics; Complex network data modeling.

Honors & Awards

1. Selected for Beijing Young Talent Cultivation Project, Independent Award Recipient, Beijing Association for Science and Technology, Feb 2024

2. Best Paper Award of Journal of Economics and Management (2022-2023), First Award Recipient, Editorial Office of Journal of Economics and Management, Jul 2024

3. Outstanding Instructor for Undergraduate Extracurricular Teaching, Renmin University of China; Independent Award Recipient; Renmin University of China, Sep 2023

4. Outstanding Instructor Award of the 13th Zhengda Cup National College Students Market Research and Analysis Competition, Independent Award Recipient, China Commercial Statistics Society, May 2023

5. Excellent Paper Award of the Academic Symposium of Beijing Applied Statistics Society, Independent Award Recipient, Beijing Applied Statistics Society, Sep 2022

 

Funding

1. Project Title: A Large-Scale CT Imaging Data-Driven Framework for Precision Diagnosis of Early-Stage Lung Cancer: Model Development and Application, General Program of the National Natural Science Foundation of China, Project Code: 72571275, 2026.01-2029.12, Principal Investigator, Ongoing

2. Project Title: Theoretical and Applied Research on Statistical Models for 3D Reconstruction and Lesion Assessment Based on CT Imaging Data, Major Project of the National Statistical Science Research Program, Project Code: 2023LD008, 2023.11-2025.11, Principal Investigator, Completed.

3. Project Title: Complex Network Data Modeling and Applications under the Background of Artificial Intelligence, General Program of the National Natural Science Foundation of China, Project No.: 72171226, 2022.1-2025.12, Principal Investigator, Ongoing

4. Project Title: Research on Optimization Algorithms for Deep Learning from a Statistical Perspective, General Program of the Scientific Research Fund of Renmin University of China, Project No.: 21XNA027, 2021.1-2023.12, Principal Investigator, Completed

5. Project Title: Research on Deep Learning Algorithms for Network-Structured Data, Key Project of the National Statistical Science Research Program, Project No.: 2020LZ38, 2020.5-2022.5, Principal Investigator, Completed

6. Project Title: Business Models of Emerging Cultural Industries under the Background of Artificial Intelligence: The Case of Live-Streaming Platforms, Young Scholars Program of the Beijing Social Science Foundation, Project Code: 19GLC052, 2019.7-2022.12, Principal Investigator, Completed

7. Project Title: Original or Repost? Motivations for UGC Creation from the Perspective of Social Networks, Young Scientists Fund of the National Natural Science Foundation of China, Project No.: 71702185, 2018.7-2020.12, Principal Investigator, Completed

8. Project Title: Network Data Analysis and Related Modeling Research, New Faculty Startup Fund of Renmin University of China, Project No.: 17XNLF08, 2017.1-2018.12, Principal Investigator, Completed

9. Project Title: Modeling of Complex Network Data and Efficient Computational Methods, General Program of the 60th China Postdoctoral Science Foundation, Project No.: 2016M600155, 2016.10-2018.5, Principal Investigator, Completed

 

Teaching Reform Projects

1. Establishing a Classroom Paradigm of Two-Way Interaction Between Research and Teaching: A Case Study of a Deep Learning Course, Beijing Higher Education Society, MS2024176, Project Leader,2024

 

Publications

1. Zhang, D., Feng, L., Wu, Y., Lan, W., and Zhou, J*., (2025), Temporal Network Influence Model with Application to the COVID-19 Population Flow Network, The Annals of Applied Statistics, 19(2), 1382-1402

2. Li, X., Zhou, J*., and Wang, H., (2024), Gaussian Mixture Model with Rare Events, Journal of Machine Learning Research. //jmlr.org/papers/volume25/23-1245/23-1245.pdf

3. Zhou, J., Guo, C., and Ji, Y*., (2024), RFDFM: A Deep Factorization Machine Network Model for Invasive Lung Adenocarcinoma Screening in CT Images, In Proceedings of the 27th European Conference on Artificial Intelligence (ECAI 2024) (pp. 338–345). IOS Press.

4. Wu, S., Zhou, J*., Xu, K., and Wang, H., (2024), Class-Distributed Learning for Multinomial Logistic Regression with a High Dimensional Feature and Numerous Classes, Journal of Computational and Graphical Statistics, //doi.org/10.1080/10618600.2024.2362230.

5. Zeng, Q., Zhou, J*., Ji, Y., Wang, H., (2024), A Semiparametric Gaussian Mixture Model for Chest CT Based 3D Blood Vessel Reconstruction, Biostatistics, 2024 Apr 19: kxae013. doi: 10.1093/biostatistics/kxae013.

6. Fu, X#., Meng, X#., Zhou, J*., and Ji, Y., (2023), High-risk Factor Prediction in Lung Cancer Using Thin CT Scans: An Attention-Enhanced Graph Convolutional Network Approach. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2023), (pp. 1905-1910). IEEE

7. Zhou, J., Hu, B., Feng, W., Zhang, Z., Fu, X#., Shao, H#., Wang, H., Jin, L., Ai, S., Ji, Y*., (2023), An Ensemble Deep Learning Model for Risk Stratification of Invasive Lung Adenocarcinoma Using Thin-Slice CT, Npj digital medicine, 6, 119, //doi.org/10.1038/s41746-023-00866-z

8. Liu, J., Zhou, J.*, Lan, W., and Wang, H., (2023), Spatial Dynamic Panel Models with Missing Data. Stat, 12: e585.

9. Qi, H., Cao, J#., Chen, S#., and Zhou, J*., (2023), Compressing Recurrent Neural Network Models through Principal Component Analysis. Statistics and its Interface. 16(3), 397-407.

10. Luo, R., Zhao, S.*, and Zhou, J., (2023), Information Network, Public Announcements and Asset Prices. Pacific-Basin Finance Journal, Volume 77, 101882

11. Zhang, R., Zhou, J.*, Lan, W., and Wang, H., (2022), A Case Study on the Shareholder Network Effect of Stock Market Data: A SARMA Approach. Science China Mathematics. 65(11)，2219-2242

12. Zhou, J., Lan, W.*, and Wang, H., (2022), Asymptotic Covariance Estimation by Gaussian Random Perturbation, Computational Statistics and Data Analysis, 171, 107459

13. Zhou, J., Liu, J.*, Wang, F., and Wang H., (2022), Autoregressive model with spatial dependence and missing data, Journal of Business & Economic Statistics, 40(1): 28-34

14. Zhou, J., Qi, H.*, Chen, Y., and Wang, H., (2021), Progressive principal component analysis for compressing deep convolutional neural networks. Neurocomputing, 440(2021),197-206.

15. Zhou, J., Li, D*, Pan,R., and Wang, H., (2020) , Network GARCH Model, Statistica Sinica, 30(4), 1723-1740.

16. Zhou, J., Zhou, J.*, Ding, Y, and Wang, H. (2019), The Magic of Danmaku: A Social Interaction Perspective in the Motivation of Gift Sending on Live Streaming Platforms, Electronic Commerce Research and Applications. Vol 34, 1-7.

17. Zhou, J., Huang,D.*, and Wang, H., (2018), A note on estimating spatial autocorrelation in a discrete choice model, Statistics and Its Interface, Vol. 11, No. 3, 433-439.

18. Huang. D, Zhou, J.*, and Wang, H., (2018), RFMS method for credit scoring based on bank card transaction data, Statistica Sinica, Vol. 28, No.4, 2903-2919.

19. Huang, D., Guan, G*., Zhou, J. and Wang, H. (2018), Network-based Naive Bayes Model for Social Network, Science China Mathematics, 61 (4): 627-640

20. Zhou, J, Tu, Y, Chen, Y., and Wang, H., (2017). Estimating Spatial Autocorrelation with Sampled Network Data, Journal of Business and Economic Statistics, 35(1)., 130~138.

21. Zhou J., Huang D.*, and Wang, H. (2017), A Dynamic Logistic Regression for Network Link Prediction, Science China Mathematics, Vol.60, No.1, 165-176.