杨玥含 副教授，硕士生导师，统计学学士、博士 Email: yyh@cufe.edu.cn

研究方向 高维统计，复杂数据分析，因果推断，资产配置

工作经历与教育背景

2014年7月至今 全球十大赌船网址(中国)有限公司

2009年9月-2014年7月 北京大学应用数学专业，获博士学位

2005年9月-2009年7月 重庆大学统计学专业，获学士学位

所授课程

统计软件(本科生)，统计学(本科生)，统计计算(研究生）

著作

《金融大数据统计方法与实证》，2016，科学出版社

《金融大数据统计方法与实证配套课件及R程序》，2018，科学出版社

《非负模型选择理论及应用》，2022，中央财经出版社

学术奖励

公司“鸿基世业”优秀学术论文奖

课题

《高维相关数据分层估计与迭代筛选方法研究及金融实证》，国家自然科学基金青年项目，课题负责人，2021.01-2023.12

《基于“以学为中心”理念的《现代统计软件》教学方法研究和实践》，公司教学方法研究项目，课题负责人，2022.06-2024.06

《复杂相关数据的筛选建模与金融实证分析》，公司“青年英才”培育支持计划，课题负责人，2021.06-2023.06

《基于模型选择的有约束统计推断理论及金融大数据分析》，国家自然科学基金面上项目，第一主研，已结项

《罚项约束的模型选择理论及相关问题研究》，公司青年教师发展基金，课题负责人，已结项

研究生（本科生）科研指导

1. 个人状态：对科研有兴趣，在已有的课程中学有余力，计划或确定在本校读研，在本科后半程或即将的研究生阶段开展学术研究。

2. 课程基础：熟悉统计学、熟练使用R or Python or Matlab。

   以上，欢迎找我唠嗑。学术是综合的领域，包含文献学习、思考推导、数值分析、英文写作等等，它们需要的不是天赋，而是投入。

科研代表作：Publications on the top journals(*corresponding author)

Hanzhong Liu, Jiyang Ren and Yuehan Yang*, Randomization-based joint central limit theorem and efficient covariate adjustment in stratified 2^K factorial experiments.Journal of the American Statistical Association, 2023, in press. (Top 4 ofStatistics)

Hanzhong Liu and Yuehan Yang*, Regression-adjusted average treatment effect estimates instratified randomized experiments, Biometrika, 2020,107(4):935-948. (Top 4 ofStatistics)

Yuehan Yang*,Dimension reduction of high-dimension categorical data with two or multiple responses regarding the interactions between responses.Expert Systems With Applications, 2023, in press. (Computer Science, Q1)

Yimiao Gao and Yuehan Yang*, Transfer learning on stratified data: joint estimation transferred from strata. Pattern Recognition, 2023, in press. (Computer Science, Q1)

Siwei Xia and Yuehan Yang*,An iterative model-free feature screening procedure: forward recursive selection by random forest, Knowledge-Based Systems, 2022, 246:108745. (Computer Science, Q1)

Xingyu Chen and Yuehan Yang*, Local linear approximation with Laplacian smoothing penalty and application in biology.Statistical Methods in Medical Research, 2023, in press. (Statistics, Q1)

Fan Yang, Zhanyang Li, Yushan Xue, and Yuehan Yang*, A penalized least product relative error loss function based on wavelet decomposition for nonparametric multiplicative additive models.Journal of Computational and Applied Mathematics,2023, in press. (Mathematics, Q1)

Siwei Xia,Yuehan Yang# and Hu Yang*, High-dimensional Sparse Portfolio Selection with Nonnegative Constraint.Applied Mathematics and Computation, 2023,443, 127766.(Mathematics, Q1)

Yuehan Yang and Hu Yang*,Adaptive and reversed penalty for analysis ofhigh-dimensional correlated data, Applied Mathematical Modelling, 2021, 92:63-77.(Mathematics, Q1)

Yuehan Yang*, Ji Zhu and E. George, MuSP: A Multi-step Screening Procedure for Sparse Recovery,Stat, 2021,10:1-19.(Statistics, Q1,This paper is listed on the Stat Sample Issue as representative of high-dimensional analysis.)

Yuehan Yang* and Ji Zhu, A two-step method for estimating high-dimensional Gaussian graphical models. Science China Mathematics, 2020, 63(6):1203-1218.(Mathematics, Top journal)

Lan Wu and Yuehan Yang*, Nonnegative Elastic Net and application in index tracking. Applied Mathematics and Computation, 2014,227:541-552.(Mathematics, Q1)

Published or Accepted (*corresponding author)

1. Yuehan Yang*,Dimension reduction of high-dimension categorical data with two or multiple responses regarding the interactions between responses.Expert Systems With Applications, 2023, in press.

2. Yimiao Gao and Yuehan Yang*, Transfer learning on stratified data: joint estimation transferred from strata. Pattern Recognition, 2023, in press.

3. Xingyu Chen and Yuehan Yang*, Local linear approximation with Laplacian smoothing penalty and application in biology.Statistical Methods in Medical Research, 2023, in press.

4. Fan Yang, Zhanyang Li, Yushan Xue and Yuehan Yang*, A penalized least product relative error loss function based on wavelet decomposition for nonparametric multiplicative additive models.Journal of Computational and Applied Mathematics,2023, in press.

5. Hanzhong Liu, Jiyang Ren and Yuehan Yang*, Randomization-based joint central limit theorem and efficient covariate adjustment in stratified 2^K factorial experiments.Journal of the American Statistical Association, 2023, in press.

6. Yuanyuan Cao, Hongying Li and Yuehan Yang*, Combining random forest and multicollinearity modeling for index tracking. Communications in Statistics - Simulation and Computation, 2022, in press.

7. ZhaoyangLi and Yuehan Yang*,Directed association network analysis on the Standard & Poor's 500 Index.Computational Economics, 2023, in press.

8. Yanan Yan and Yuehan Yang*, Community detection for New York stock market by SCORE-CCD. Computational Statistics, 2023, in press.

9. Xingyu Chen and Yuehan Yang*, An iterative algorithm with adaptive weights and sparse Laplacian shrinkage for regression problems. Statistics and Its Interface, 2023, in press.

10. Yimiao Gao and Yuehan Yang*, A joint estimation for the high-dimensional regression modeling on stratified data. Communications in Statistics - Simulation and Computation, 2023, in press.

11. Siwei Xia,Yuehan Yang# and Hu Yang*, High-dimensional Sparse Portfolio Selection with Nonnegative Constraint.Applied Mathematics and Computation, 2023,443, 127766.

12. Yuehan Yang, Siwei Xia and Hu Yang*, Multivariate sparse laplacian shrinkage for joint estimation of two graphical network structures, Computational Statistics & Data Analysis, 2023, 178,107620.

13. Yuehan Yang and Siwei Xia*, An integrated precision matrix estimation for multivariate regression problems. Journal of Statistical Planning and Inference, 2023, 222, 261-272.

14. Binghui Li and Yuehan Yang*, Undirected and directed network analysis of the Chinese stock market.Computational Economics, 2022, 60, 1155-1173.

15. Siwei Xia and Yuehan Yang*,An iterative model-free feature screening procedure: forward recursive selection by random forest, Knowledge-Based Systems, 2022, 246:108745.

16. Siwei Xia,Yuehan Yang and Hu Yang*, Sparse Laplacian shrinkage with the graphical lasso estimator for regression problems, TEST, 2022, 31:255-277.

17. Wenjun Cao, Lisu Wang and Yuehan Yang*, Multiple penalized regularization for clusters with varying correlation levels. Statistics and Its Interface, 2022, 15, 373-382.

18. Yuehan Yang*, Ji Zhu and E. George, MuSP: A Multi-step Screening Procedure for Sparse Recovery,Stat, 2021,10(1):1-19.

19. Yuehan Yang* and Hu Yang,Rates of Convergence of the Adaptive Elastic Net and the Post-selection Procedure in Ultra-high Dimensional Sparse Models. Communications in Statistics Theory and Methods, 2021,50(1):73-94.

20. Tianchen Gao, Yan Zhang, Siyu Wang,Yuehan Yang and Rui Pan*,Community detection for statistical citation network by D-SCORE, Statistics and Its Interface, 2021,14:279-294.

21. Yuehan Yang and Hu Yang*,Adaptive and reversed penalty for analysis ofhigh-dimensional correlated data, Applied Mathematical Modelling, 2021, 92:63-77.

22. Hanzhong Liu and Yuehan Yang*, Regression-adjusted average treatment effect estimates instratified randomized experiments, Biometrika, 2020,107(4):935-948.

23. Yuehan Yang* and Ji Zhu, A two-step method for estimating high-dimensional Gaussian graphical models. Science China Mathematics, 2020, 63(6):1203-1218.

24. Yuehan Yang* and Lan Wu, A significance test for the elastic net and its asymptotic distribution with general predictors (in Chinese). Science China Mathematics, 2019,49:1119-1138.

25. Yuehan Yang* and Hu Yang, Model selection consistency of lasso for empirical data. Chinese Annals of Mathematics Series B, 2018, 39(4):607-620.

26. Yuehan Yang* and Lan Wu, Nonnegative adaptive lasso for ultra-high dimensional regression models and a two-stage method applied in financial modeling. Journal of Statistical Planning and Inference, 2016, 174:52-67.

27. Lan Wu,Yuehan Yang* and Hanzhong Liu, Nonnegative-lasso and application in index tracking. Computational Statistics and Data Analysis, 2014, 70:116-126.

28. Lan Wu and Yuehan Yang*, Nonnegative Elastic Net and application in index tracking. Applied Mathematics and Computation, 2014,227:541-552.

Under Review

1. Zhaoyang Li and Yuehan Yang*, Structurally incoherent adaptive weighted low-rank matrix decomposition for image classification. Under Review.

2. Siwei Xia and Yuehan Yang*, A model-free feature selection technique of feature screening and random forest based recursive feature elimination. Under Review.

3. Weixiong, Liang and Yuehan Yang*,Iterative sequential screening strategies for sparse recovery with computational advantages. Under Review.

4. Lisu Wang, Yufan Zhou and Yuehan Yang*, Cluster Gelnet for estimating Gaussian graphical model with multiple conditional correlation levels and block-diagonal structures. Under Review.

5. Zhaoyang Li and Yuehan Yang*, A semi-orthogonal nonnegative matrix tri-factorization algorithm for overlapping community detection. Under Review.

6. Weixiong Liang and Yuehan Yang*, A sequential stepwise screening procedure for sparse recovery in high-dimensional multiresponse models with complex group structures. Under Review.

7. Ke Zhu, Hanzhong Liu,Yuehan Yang*, Blocking, rerandomization, and regression adjustment in randomized experiments with high-dimensional covariates. Under Review.

8. Rui Chen, Erbo Li, Yushan Xue, and Yuehan Yang*, Spectral feature selection with the Graphical Lasso estimator for ultra-high dimensional Gaussian graphical models. Under Review.

9. Xingyu Dong, Ziyi Lin, Ziyi Cai, and Yuehan Yang*, Adaptive analysis of the heteroscedastic multivariate regression modeling. Under Review.

部分会议邀请报告：

2022年，海淀医院，邀请报告

2021年，重庆大学，邀请报告

2020年，人民大学，邀请报告

2019年，泛华统计协会国际会议，邀请报告

2019年，南开大学青年统计论坛，邀请报告

2018年，第八届IMS-China概率统计大会，作为分会主席并作报告

2017年，2018泛华统计协会中国会议，邀请报告。

2017年，第六届IMS-China概率统计大会，邀请报告。

2016年，北大金融数学系20周年系庆系列讲座，北京大学，邀请报告。

2016年，青年统计学者论坛，清华大学，邀请报告。

2015年，国际数理统计协会年会，邀请报告。