Education

2012.09-2017.07, Ph.D. in Statistics, Peking University

2008.09-2012.06, B.A. in Statistics, Renmin University of China

Work Experience

2021.08 - Present, Associate Professor, School of Statistics, Renmin University of China

2019.08-2021.08, Assistant Professor, School of Statistics, Renmin University of China

2017.07-2019.08, Postdoctoral Research Fellow, School of Statistics, Renmin University of China

Visiting Experience

2015.08-2016.08, Visiting Scholar, Department of Statistics, Duke University, USA

Research Interests

Federated Learning and Privacy Preservation Text Analysis and Large Language Models Robotic Intelligence and Optimization Design

Honors and Awards

1.Second Prize, Best Student Paper Award, IEEE International Conference on Data Science in Cyberspace, 2016

2.Outstanding Research Achievement Award, Renmin University of China, 2022, 2023

3.Award for Undergraduate Extracurricular Teaching, Renmin University of China, 2021

4.Outstanding Thesis Supervisor for Undergraduate Students, Renmin University of China, 2021, 2022, 2023

5.Second Prize, Young Faculty Teaching Skills Competition, Renmin University of China, 2021

6.First Prize & Outstanding Teaching Design Award, National Case Teaching Competition in Data Science and Business Analytics for Young Faculty, China Association of Business Statistics, 2023

7.Outstanding Individual in Graduate Teaching Case Development, Renmin University of China, 2024

Funding

1.China Postdoctoral Science Foundation (General Program, 62nd Batch), 2017–2019, PI, Completed

2.National Natural Science Foundation of China (Young Scientists Fund), 2021–2024, PI, Completed

3.Major Project of National Statistical Science Research, 2022–2024, PI, Completed

4.Beijing Social Science Fund (General Program), 2024–2026, PI, Ongoing

5.National Natural Science Foundation of China (General Program), 2024–2027, PI, Ongoing

Publications

1.Wang, F., Zhao, Z., Ye, R., Gu, X., and Lu, X. (2025). Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process. Journal of Machine Learning Research. 26: 1-53.

2.Yan, H., Wang, F.*, He, C., and Wang, H. (2025). Auxiliary Learning and its Statistical Understanding. Statistical Sinica. To appear.

3.Lin, Z., Gao, Y, Wang, F.* and Wang, H. (2025). Testing Sufficiency for Transfer Learning. Computational Statistics & Data Analysis. 203: 108075.

4.Wang, F., Zhang, Z., Song, J., Yang, Y., and Lu, X. (2025). Unraveling the Anchoring Effect of Seller’s Show on Buyer’s Show to Enhance Review Helpfulness Prediction: A Multi-Granularity Attention Network Model With Multimodal Information. Electronic Commerce Research and Applications. 70: 101484.

5.Song, J., Hong, J.,Lu, X. and Wang, F.* (2025). External Information Enhancing Topic Model Based on Graph Neural Network. Expert Systems with Applications. 263: 125709.

6.Song, J., Chen, T. and Wang, F.* (2025). HeteroHTC: Enhancing Hierarchical Text Classification via Heterogeneity Encoding of Label Hierarchy. Expert Systems with Applications. 271: 126558.

7.Song, J., Yang, Y., Xiao, H., Peng, W., Yao, W., and Wang, F.* (2025). LASeR: Towards Diversified and Generalizable Robot Design with Large Language Models. Accepted by The Thirteenth International Conference on Learning Representations (ICLR 25').

8.Wang, F., Xu, S., Qin, Y., Shen, Y., & Li, Y.* (2024). Sparse Clustering for Customer Segmentation with High-Dimensional Mixed-Type Data. Annals of Applied Statistics. 18(3):2382-2402.

9.Wang, F., Jia, K., and Li, Y. (2024). Integrative Deep Learning with Prior Assisted Feature Selection. Statistics in Medicine. 43(20):3792-3814.

10.Yang, Y., Wang, F.*, Zhu, E., Jiang, F., Yao, W. (2024). Social Behavior Analysis in Exclusive Enterprise Social Networks by FastHAND. ACM Transactions on Knowledge Discovery from Data. 18(6): 1-32.

11.Song, J., Yang, Y., Peng, W., Zhou, W., Wang, F.*, Yao, W. (2024). MorphVAE: Advancing Morphological Design of Voxel-Based Soft Robots with Variational Autoencoders. Accepted by the 38th AAAI Conference on Artificial Intelligence (AAAI-24).

12.Qi, H., Wang, F.*, Wang, H. (2023). Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator. Journal of Computational and Graphical Statistics. 32(4): 1348-1360.

13.Li, X., Wang, F.*, Lan, W., Wang, H. (2023). Subnetwork Estimation for Spatial Autoregressive Models in Large-scale Networks. Electronic Journal of Statistics,17: 1768-1805.

14.Wang, F., Liang, D., Li, Y., Ma, S. (2023). Prior Information Assisted Integrative Analysis of Multiple Datasets. Bioinformatics, 39(8), btad452.

15.Wang, F., Duan, C., Li, Y., Huang, H., Shia, B.C. (2023). Spatiotemporal Varying Coefficient Model for Respiratory Disease Mapping in Taiwan. Biostatistics. 25(1):40-56.

16.Song, J., Wang, F.*, Yang, Y. (2023). Peer-Label Assisted Hierarchical Text Classification. Accepted by The 61st Annual Meeting of the Association for Computational Linguistics (ACL’23)

17.Wang, F., Huang, D., Gao, T., Wu, S., Wang, H. (2022). Sequential One-Step Estimator by Subsampling for Customer Churn Analysis with Massive Datasets. Journal of the Royal Statistical Society: Series C (Applied Statistics). 71(5): 1753-1786.

18.Wang, F., Zhou, R., Feng, Y., Lu, X. (2022). Bayesian Sparse Joint Dynamic Topic Model with Flexible Lead-Lag Order. Information Sciences. 616: 392-410.

19.Lu, X., Guo, Y., Chen, J., and Wang, F.* (2022). Topic Change Point Detection Using a Mixed Bayesian Model. Data Mining and Knowledge Discovery. 36(1): 146-173.

20.Zhu, Y., Lu, X., Hong, J., Wang, F.* (2022). Joint Dynamic Topic Model for Recognition of Lead-lag Relationship in Two Text Corpora. Data Mining and Knowledge Discovery. 36: 2272–2298.

21.Wang, F., Liu, J., and Wang, H. (2021). Sequential Text-Term Selection in Vector Space Models. Journal of Business and Economic Statistics. 39(1):82-97.

22.Wang, F., Zhu, Y., Huang, D., Qi, H. and Wang, H. (2021). Distributed One-Step Upgraded Estimation for Non-Uniformly and Non-Randomly Distributed Data. Computational Statistics & Data Analysis. 162(2021), 107265.

23.Wang, F., Zhang, L. J., Li, Y., Deng, K. and Liu, S. J. (2021). Bayesian Text Classification and Summarization via A Class-Specified Topic Model. Journal of Machine Learning Research. 22 (2021): 1-48

24.Yang, Y. and Wang F.* (2021).Author Topic Model for Co-occurring Normal Documents and Short Texts to Explore Individual User Preferences. Information Sciences. 570 (2021): 185-199.

25.Huang, D., Wang, F.*, Zhu, X., and Wang, H. (2020). Two-Mode Network Autoregressive Model for Large-Scale Networks. Journal of Econometrics. 216:203-219.

26.Yang, Y., Liu, Y., Lu, X., Xu, J., and Wang, F.* (2020). A named entity topic model for news popularity prediction. Knowledge-Based Systems. 208:106430.

27.Yang, Y., Wang, F.*, Zhang, J., Xu, J. and Yu, P. S. (2018). A Topic Model for Co-occurring Normal Documents and Short Texts. World Wide Web Journal. 21(2), 487-513.

28.Wang, F., Wang, J., Gelfand, A. E. and Li, F. (2017). Accommodating the Ecological Fallacy in Disease Mapping in the Absence of Individual Exposures. Statistics in Medicine. 36(30): 4930-4942.

29.Yang, Y., Wang, F.*, Jiang, F., Xu, J. and Yu, P. S., A Topic Model for Hierarchical Documents. International Conference on Data Science in Cyberspace, IEEE (2016), Changsha, China, 2016/6/13-2016/6/16. Best Student Paper Award.