Education

2004.09-2009.07，Ph.D. , majored in Probability and Mathematical Statistics, Peking University. 

1999.09-2003.07，B.Sci., majored in Theoretical and Applied Statistics, Peking University.

 

Work Experience

2025.09- Present，Professor, School of Statistic, Renmin University of China 

2012.08-2025.08，Associate Professor, School of Statistics, Renmin University of China 

2011.09-2012.08，Assistant Professor, School of Statistics, Renmin University of China 

2009.08-2011.08，Postdoctoral Researcher, University of Pennsylvania, U.S.A. 

 

Research Interests

Graphical Model，High Dimensional Statistical Inference、Machine Learning、Statistical Modeling in Unstructured Data

 

Honors and Awards (in Chinese)

1. 第七届高等公司科学研究（人文社会科学）优秀成果奖，论文奖三等奖，第1获奖人，教育部，2015

2. 新工科研究与实践优秀成果奖二等奖，独立获奖人，伟德国际唯一官网，2020

3. 北京市高等公司产品成果奖一等奖，第3获奖人，北京市教委，2022

 

Funding (in Chinese)

1. 基于多模态信息、具有临床可解释性的膝关节运动损伤个性化诊断与治疗模型，北京市自然科学基金-海淀原始创新联合基金，主持，2024.10-2027.09。

2. 骨关节炎早期诊断、风险因素筛查、预警模型建立及阶梯精准治疗（课题），国家重点研发计划“主动健康与老龄化科技应对”专项之“老年骨骼系统退行性病变的防控技术研究”项目，科技部，主持，2020.07-2023.06。

3. 疾病模型和健康效应参数评估模型构建，国家食品安全风险评估中心项目，主持，2021-2022。

 

Teaching Reform Projects (in Chinese)

1. 面向数据科学的统计学科知识体系图谱建设，伟德国际唯一官网教学改革重点项目，项目主持人，2018-2020。

 

Publications (in English and Chinese)

1. Shixiang Liu，Zhifan Li$，Yanhang Zhang and Jianxin Yin*.(2026) Exact recovery in the double sparse model: Sufficient and necessary signal conditions, Electron. J. Statist. 20(1) 83 - 137, 2026. https://doi.org/10.1214/26-EJS2486.

2. Y. Zhang, S. Liu, Z. Li, X. Wang and J. Yin (2025), "Rethinking Hard Thresholding Pursuit: Full Adaptation and Sharp Estimation," in IEEE Transactions on Information Theory, doi: 10.1109/TIT.2025.3603987.

3. Zhang, Y., Li, Z., Liu, S. and Yin, J.* (2024) A minimax optimal approach to high-dimensional double sparse linear regression, Journal of Machine Learning Research，25（2024）1-66.

4. Zhifan Li, Yanhang Zhang and Jianxin Yin*(2024) Estimating Double Sparse Structures over l_u(l_q)-Balls: Minimax Rates and Phase Transition， IEEE Transactions on Information Theory, Vol.70, No.10, 7066-7088.

5. Lai, J. and Yin, J.* (2024) Learning conditional dependence graph for concepts via matrix normal graphical model, Statistics and Its Interface，2024, Vol. 17, No.2, pp. 187-198.

6. Zhang, H., Hu, F. and Yin, J.*(2022) Covariate-adaptive randomization with variable selection in clinical trials, STAT, 2022;11:e461.

7. Yang Y., Wang, W., Lou, Y., Yin, J. and Gong, X.*(2018). Geometric and amino acid type determinants for protein-protein interaction interfaces, Quantitative Biology, https://doi.org/10.1007/s40484-018-0138-5.

8. Wang W., Yang Y., Yin J. * and Gong X. * (2017). Different protein-protein interface patterns predicted by different machine learning methods. Scientific Reports, 7:16023, DOI:10.1038/s41598-017-16397-z.

9. Li，X. and Yin, J. (2016). Sparse sufficient dimension reduction for Markov blanket discovery, Communications in Statistics--Simulation and Computation, 45: 1355-1364.

10. Liu Z Q, Yin J X and Hu F F. (2015). Covariate-adaptive designs with missing covariates in clinical trials, Science China Mathematics, Vol.58, Issue 6, 1191-1202. 

11. S. He, J. Yin*, H. Li and X. Wang (2014). Graphical Model Selection and Estimation for High Dimensional Tensor Data，Journal of Multivariate Analysis, 128,165-185.

12. J. Yin and H. Li* (2013). Adjusting for High-dimensional Covariates in Sparse Precision Matrix Estimation by L1-Penalization, Journal of Multivariate Analysis, 116, 365-381.

13. J. Yin and H. Li* (2012). Model selection and estimation in the matrix normal graphical model, Journal of Multivariate Analysis, 107, 119-140. 

14. J. Yin and H. Li (2011). A Sparse Conditional Gaussian Graphical Model for Analysis of Genetical Genomics Data, The Annals of Applied Statistics, Vol. 5, No. 4, 2630-2650.

15. J. Yin, Z. Geng, R. Li and H. Wang (2010). Nonparametric Covariance Model, Statistica Sinica, 20, 469-479.

16. Y. Zhou, C. Wang, J. Yin and Z. Geng (2008). Discover Local Causal Network around a Target to a Given Depth, Journal of Machine Learning Research: Workshop and Conference Proceedings 6: 191-202.

17. J.Yin, Y. Zhou, C. Wang,P. He, C. Zheng and Z. Geng(2008). Partial orientation and local structural learning of causal networks for prediction, Journal of Machine Learning Research: Workshop and Conference Proceedings 3: 93-105.

18. 桂鹏，娄立威，尹建鑫*(2025), 大量文本中特定主题含量的测度研究，《数理统计与管理》, https://link.cnki.net/urlid/11.2242.o1.20250508.1043.002.

19. 褚挺进，华雨臻，丁一鸣，尹建鑫* (2024)，高维地理空间回归模型的惩罚似然估计与模型选择, 《数理统计与管理》, Vol. 43, No.3, 407-422。

20. 李智凡，尹建鑫*(2023)， 类别不平衡高维数据的最优逻辑斯蒂回归，《系统科学与数学》，43（9），2341-2363。

21. 尹建鑫，王晓军(2023) 统计与数据科学知识图谱构建与创新人才培养，《伟德国际唯一官网教育学刊》，2023 (02): 69-79。

22. 廖军，文丽，尹建鑫(2021). 高阶空间自回归模型的选择与平均估计，《系统科学与数学》，2021，41(5)：1400-1417。

23. 尹建鑫，王天颖，王伟（2017）.稀疏稳健条件图模型的结构学习和参数估计，《中国科技论文》，第12卷，第17期，pp1921-1929。

24. 杜子芳，林一楠，尹建鑫*，郑冰（2017）.基于随机加权的空间聚集性检验及其在基础教育团队均衡性评价中的应用，《数学的实践与认识》，第47卷，第11期, pp50-65。

25. 佘振苏，杨铸，欧阳正清，朱怀球，王超，尹建鑫 (2003). SARS冠状病毒的起源和进化初探, 《北京大学学报（自然科学版）》, Vol. 39, No. 6: 809-814。

 

Books & Textbooks

1. Edited by Jianxin Yin，《Probability Foundation for Data Science》，China Renmin University Press，June, 2023.

 

Teaching

1. Undergraduate：Probability, Freshman Seminar.

2. Graduate：Advanced Mathematical Statistics, Selected Topics in Machine Learning, Mining in Big Data and Machine Learning.