教育背景

2012.09-2017.07，北京大学统计学专业，统计学博士学位

2008.09-2012.06，太阳成集团122cc官网入口统计学专业，经济学学士学位

 

工作经历

2021.08至今，太阳成集团tyc122cc，副教授

2019.08-2021.08，太阳成集团tyc122cc，讲师

2017.07-2019.08，太阳成集团tyc122cc，团队博士后

 

访学经历

2015.08-2016.08，美国杜克大学统计系，访问学者

 

研究方向

联邦学习与隐私保护、文本分析与大模型、机器人智能优化设计等。

 

荣誉奖励

1. IEEE International Conference on Data Science in Cyberspace, Best Student Paper Award, the second recipient, 2016

2. 太阳成集团122cc官网入口优秀科研成果奖（2022、2023）

3. 太阳成集团122cc官网入口本科课外教学优秀奖，2021年

4. 太阳成集团122cc官网入口本科优秀论文指导教师，2021年、2022年、2023年

5. 太阳成集团122cc官网入口青年教师基本功大赛二等奖，2021年

6. 首届全国高校青年教师数据科学与商业分析案例教学竞赛一等奖、优秀教学设计奖，中国商业统计学会，2023年

7. 太阳成集团122cc官网入口专业学位研究生教学案例优秀个人，2024年

 

科研项目

1. 第62批中国博士后科学基金面上项目，2017~2019，主持，结项

2. 国家自然科学基金青年基金，2021~2024，主持，结项

3. 全国统计科学研究重大项目，2022-2024，主持，结项

4. 北京市社会科学基金规划项目，2024-2026，主持，在研

5. 国家自然科学基金面上基金，2024~2027，主持，在研

 

科研发表

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. 

30. 何辰轩，王菲菲*，朱利平，袁卫. (2025). 中国统计学者在国际统计学领域的学术发表情况分析. 统计研究，网络首发.

31. 王菲菲，贾珂，张开宇，李扬*. (2024). 融合先验信息的整合财务预警模型研究. 统计研究. 41(392): 137-149.

32. 王菲菲，刘雯珺，朱立奥，吕晓玲*. (2024).基于客户-客服沟通文本信息的客户流失研究. 管理学报，21(8): 1199-1207.

33. 王菲菲，林中潭，吴昆，韩树庭，孙立博，吕晓玲*. (2024). 多阶元路径引导的异质图神经网络新闻推荐模型. 系统工程理论与实践. 44(5): 1562-1576.

34. 王菲菲，朱雪宁*，潘蕊，高天辰. 广义网络向量自回归；中国科学（数学）. 2021, 51（8）: 1253-1266. 

35. 王雅琼，徐敏亚，王菲菲*. (2021). 隐含动态地理统计校准模型—以PM2.5污染分析为例；数理统计与管理. 40(2): 191-204.

 

 

著作教材

1. 王汉生、王菲菲著，《商务统计学基础：从不确定性到人工智能》，北京大学出版社，2023.02

 

 

教学课程

1. 本科课程：数据科学概论、数据科学：从问题到结论、回归分析、时间序列分析、营销调研与数据分析

2. 研究生课程：非结构化数据分析、时间序列分析选讲

 

社会兼职

1. 2025.06-2027.06，中国商业统计学会人工智能分会，副会长

2. 2025.06-2028.04，全国工业统计学教学研究会青年统计学家协会，常务理事、副秘书长