Education

2007.09 – 2013.01: Beihang University, Fundamental Mathematics, Ph.D.

2003.09 – 2007.07: Beihang University, Mathematics and Applied Mathematics, B.S.

Work Experience

2022.08 – Present: Professor, School of Statistics, Renmin University of China

2017.08 – 2022.08: Associate Professor, School of Statistics, Renmin University of China

2013.01 – 2017.08: Lecturer, School of Statistics, Renmin University of China

Research Interests

Multi-source Heterogeneous Data Analysis, Federated Learning, Distributed Optimization, Privacy in Large Models

Honors and Awards

1. Teaching Pacemaker, Renmin University of China, 2023

2. Excellent Undergraduate Thesis Supervisor, Beijing Higher Education Institutions, 2023

3. First Prize, Beijing Higher Education Teaching Achievement Award, 9th Contributor, 2022

4. Special Prize, Renmin University of China Teaching Achievement Award, 9th Contributor, 2021

5. Outstanding Party Affairs Worker (Party Branch Secretary), Renmin University of China, 2021

6. Excellent Undergraduate Thesis Supervisor, Beijing Higher Education Institutions, 2021

7. Excellent Undergraduate Thesis Supervisor, Beijing Higher Education Institutions, 2020

8. Outstanding Scientific Research Achievement Award, Renmin University of China, 2019

9. Third Prize, Youth Excellent Paper Award, Beijing Society of Biostatistics and Data Management, 2018

10. First Prize, Renmin University of China Teaching Achievement Award, 2017

11. Third Prize, 9th Young Teachers' Basic Teaching Skills Competition, Renmin University of China, 2017

Funding

1. Mathematical Theory and Methods for Heterogeneous Federated Learning (No. 2024K20075), Future Blockchain and Privacy Computing Beijing Advanced Innovation Center Project, 2024.5-2025.5, PI, Ongoing.

2. Methods, Theory, and Applications of High-Dimensional Data Effect Heterogeneity Mining (No. 23XNL014), Renmin University of China Major Scientific Research Fund Project, 2023.1-2025.12, PI, Ongoing.

3. Supervised Clustering for High-Dimensional Data: Optimal Error, Learning Algorithms, and Phase Transition Characteristics (No. 12171479), National Natural Science Foundation General Program, 2022.1-2025.12, PI, Ongoing.

4. UNIDO Environmental and Social Governance (ESG) Dongying Pilot Project and Its Theoretical Research (No. 2022K20095), Institutional Project, 2022.4-2023.3, PI, Ongoing.

5. Research on Analysis and Identification Methods for Subsample Heterogeneity and Homogeneity in the Context of Big Data (No. 2019LZ11), National Statistical Science Research Key Project, 2019.10-2021.10, PI, Completed.

6. Research on Dynamic Reconstruction Methods for Complex Coupled Systems (No. 18XNB004), Renmin University of China Scientific Research Fund, 2018.1-2020.12, PI, Completed.

7. Research on Computing Pure Strategy Nash Equilibria in Network Games and Realization Paths of Socially Efficient States Based on Spin Glass Theory (No. 11605288), National Natural Science Foundation Youth Program, 2017.1-2019.12, PI, Completed.

8. Research on Employment Migration Patterns and Influencing Factors of Chinese University Graduates (No. 16YJCZH088), 2016.9-2019.9, PI, Completed.

9. Research on Comprehensive Evaluation Methods for Basic Public Service Performance (No. 12XNQ080), Renmin University of China Scientific Research Fund, 2013.1-2014.1, PI, Completed.

10. Research on the Evaluation of Beijing's Basic Education Public Service Level (No. 2014010241), Beijing Education Science Planning Key Project, 2014.8-2017, Participant, Completed.

Educational Reform Projects

1. Optimization Methods in Data Science — Textbook Compilation, Renmin University of China Undergraduate Education and Teaching Reform Project, 2021-2023, PI, Completed.

2. Probability Foundation for Data Science — Textbook Compilation, Renmin University of China Undergraduate Education and Teaching Reform Project, 2021-2023, Participant, Completed.

Selected Publications

41. Feng Wang, Tianxiang Chen, Shuyue Wei, Qian Chu, Yi Zhang*, Yifan Sun*, Zhiming Zheng. Unlocking Dynamic Inter-Client Spatial Dependencies: A Federated Spatio-Temporal Graph Learning Method for Traffic Flow Forecasting. AAAI, 2026. To appear.

40. Ting Wei, Biao Mei, Junliang Lyu, Renquan Zhang, Feng Zhou*, Yifan Sun*. Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation. NIPS, 2025. To appear.

39. Yuzhao Zhang, Yifan Sun, Xin He, Jingnan Zhang*, Junhui Wang. On optimal tracking of structural changes in Time-Varying Networks.Journal of Computational and Graphical Statistics, 1-20, 2025.

38. Biao Mei, Yu Jiang, Yifan Sun*. Unveiling commonalites and differences in genetic regulations via two-way fusion. Journal of Computational Biology, 31(9), 2024.

37. Sun Yifan, Yao Yizhi, Yu Xue*. Effect Heterogeneity Analysis of Multiple High-Dimensional Datasets Based on Mixed Pairwise Penalty. Statistical Research, 2024. (In Chinese)

36. Xue Yu, Ziyi Liu, Wu Wang*, Yifan Sun*. Clustered federated learning based on nonconvex pairwise fusion. Information Science, 678: 120956, 2024.

35. Renquan Zhang, Ting Wei, Yifan Sun, Sen Pei*. Influence maximization based on simplicial contagion models. Physica A-Statistical mechanics and its applications, 2024, online.

34. Yifan Sun, Ziyi Liu, Wu Wang*. Subgroup analysis for the functional linear model. Journal of Statistical Planning and Inference, 231: 106120, 2024.

33. Xindi Wang, Yu Jiang, Yifan Sun*. Revealing genomic heterogeneity and commonality: A penalized integrative analysis approach accounting for the adjacency structure of measurements. Genetic Epidemiology, 48: 114-140, 2024.

32. Yuzhao Zhang, Jingnan Zhang*, Yifan Sun, Junhui Wang. Change point detection in dynamic network via regularized tensor decomposition. Journal of Computational and Graphical Statistics, 33(2)：515-524, 2024.

31. Xue Yu, Ziyi Liu, Yifan Sun*, Wu Wang*. Clustered federated learning for heterogeneous data. AAAI, 2023.

30. Yifan Sun, Ziye Luo, Xinyan Fan*. Robust structured heterogeneity analysis approach for high-dimensional data. Statistics in Medicine, 41(17)：3229-3259, 2022.

29. Ziye Luo, Xinyue Yao, Yifan Sun*, Xinyan Fan*. Regression-based heterogeneity analysis to identify overlapping subgroup structure in high-dimensional data. Biometrial Journal, 64(6): 1109-1141, 2022.

28. Ziye Luo, Yuzhao Zhang, Yifan Sun*. Estimating heterogeneous covariate effects with penalization. Genes, 13(4)：702，2022.

27. Zihan Li, Ziye Luo, Yifan Sun*. Robust nonparametric integrative analysis to decipher heterogeneity and commonality across subgroups using sparse boosting. Statistics in Medicine, 41(9)：1658-1687，2022.

26. Xue Yu, Yifan Sun*, Haijun Zhou*. An adaptive shortest-solution guided decimation approach to sparse high-dimensional linear regression. Scientific Reports, 11：24034，2021.

25. Ziqiao Yin, Binghui Guo*, Shuangge Ma*, Yifan Sun, Zhilong Mi, Zhiming Zheng. DReSS: a method to quantitatively describe the influence of structural perturbations on state spaces of genetic regulatory networks. Briefings in Bioinformatics, 22(4)：bbaa315，2021.

24. Sanguo Zhang, Xiaonan Hu, Ziye Luo, Yu Jiang, Yifan Sun*, Shuangge Ma*. Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion. Statistics in Medicine, 40(17)：3915-3936，2021.

23. Sun Yifan, Wang Caijing, Luo Ziye*. Research on High-Dimensional Data Similarity and Difference Identification Method Based on Varying-Coefficient Model. Statistical Research, 38(5): 136-146, 2021. ( (In Chinese)

22. Huangdi Yi, Qingzhao Zhang, Yifan Sun*, Shuangge Ma*. Assisted estimation of gene expression graphical models. Genetic Epidemiology, 45(4): 372-385, 2021.

21. Yang Li, Fan Wang, Rong Li, Yifan Sun*. Semiparametric integrative interaction analysis for non-small-cell lung cancer. Statistical Methods in Medical Research, 29: 2865-2880, 2020.

20. Yifan Sun, Zhengyang Sun, Yu Jiang,Yang Li, Shuangge Ma*. An integrative sparse boosting analysis of cancer genomic commonality and difference. Statistical Methods in Medical Research, 29: 1325-1337, 2020.

19. Yifan Sun, Jiang Yu, Yang Li, Shuangge Ma*. Identification of cancer omics commonality and difference via community fusion. Statistics in Medicine, 38: 1200-1212, 2019

18. Yifan Sun, Kunfeng Pan*, Zhangli He, Intercity migration behavior of Chinese graduates: from home region to work. The Annals of Regional Science, 64: 111-132, 2019.

17. Sun Yifan, Wu Mengyun, Shi Xingjie. Community Detection in High-Dimensional Big Data Gene Networks: Taking the NC Method as an Example. Statistical Research, 36(3): 124-128, 2019. (In Chinese)

16. Yi-Fan Sun*, Zheng-Yang Sun, Target observation of complex networks, Physica A-Statistical mechanics and its applications, 517: 233-245, 2019

15. Sun Yifan, Pan Kunfeng, Sun Zhengyang, He Zhangli. Ideas and Methods for Predicting the Post-Graduation Destinations of College Students: An Attempt Based on Machine Learning Algorithms. Education Research Monthly, 1, 2019. (In Chinese)

14. Yi-Fan Sun, Hai-Jun Zhou*, Serving by local consensus in the public service location game, Scientific Reports 6: 32502, 2016

13. Yifan Sun, Optimal selection of nodes to propagate influence on networks, Eurs. Phys. J.B, 89:253-262, 2016

12. Pan Kunfeng, He Zhangli, Sun Yifan*. The Paper Preference Patterns and Journal Influence of Top Chinese Education Journals. China Higher Education Research, 4, 2016 (In Chinese)

13. Sun Yifan, Xing Jingli, Du Zifang. Construction of a Performance Evaluation Indicator System for Basic Public Services. Statistics & Decision, 3, 2016 (In Chinese)

14. Du Zifang, Lei Xiaoqiao, Sun Yifan*. Measurement of Beijing's Basic Education Public Service Level. The World of Survey and Research, 1, 2016 (In Chinese)

9. YiFan Sun, Statistical mechanics of the fashion game on networks, Journal of Statistical Mechanics: Theory and Experiment, P023203, 2016

8. Sun Yifan, Li Sai. A Similarity-Based Community Detection Method for Weibo Social Networks. Computer Engineering and Applications, 12, 2014 (In Chinese)

7. Yifan Sun, Kunfeng Pan*, Prediction of intercity migration of Chinese graduates, Journal of Statistical Mechanics: Theory and Experiment, P12022, 2014

6. Florent Krzakala*, Marc Mézard, François Sausset, Yifan Sun and Lenka Zdeborová, Statistical-physics-based reconstruction in compressed sensing, Physical Review X, 2:021005, 2012

5. Florent Krzakala*, Marc Mezard, Francois Sausset,, Yifan Sun and Lenka Zdeborova, Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices, Journal of Statistical Mechanics: Theory and Experiment, P08009, 2012

4. Yifan Sun, Andrea Crisanti, Florent Krzakala*, Luca Leuzzi and Lenka Zdeborova, Following states in temperature in the spherical s+p-spin model, Journal of Statistical Mechanics: Theory and Experiment, P07002, 2012

3. SUN Yi-Fan, Phase transitions in q-states signal reconstruction, Commun. Theor. Phys, 57: 1095-1100, 2012

2. Binghui Guo, Wei Wei*, Yifan Sun, Zhiming Zheng, Algebraic characteristics and satisfiability threshold of random Boolean equations, Physical Review E, 81L 030122, 2010

1. Y.F. Sun*, B.H. Guo, W. Wei and Z.M. Zheng, On the thresholds in linear and nonlinear Boolean equations, Eurs. Phys. J.B, 76:123-146, 2010

Books and Textbooks

1. Sun Yifan (Author), Optimization Methods for Data Science, Renmin University of China Press, 2023.

2. Sun Yifan (Contributor), Analysis of Unstructured Big Data, Renmin University of China Press, 2018.

3. Sun Yifan et al. (Translator), Statistics and Its Applications, China Machine Press, 2016.

Teaching Courses

1. Undergraduate Courses: Probability Theory, Optimization Methods, Statistics

2. Graduate Course: Analysis of Unstructured Big Data

Professional Service

1. 2022 – Present: Standing Council Member, National Industrial Statistics Teaching Research Society

2. 2022 – Present: Council Member, China Statistical Education Association