个人信息
School of Mathematics and Statistics,NENU
Personal Particulars
个人简介 / Biography
李丹宁，博士，现任东北师范大学数学与统计学院副教授,硕导。主要从事高维统计学、大规模假设检验及前沿交叉数据分析的理论与方法研究。近年来的核心工作聚焦于：超高维协方差阵与均值向量的检验、微生物高维成分数据的稳健估计与检验、以及网络数据的统计推断。主持国家自然科学基金面上项目与青年项目。在统计学及计量经济学国际权威期刊 Journal of the American Statistical Association (JASA), Biometrics, Journal of Business & Economic Statistics (JBES), Test, Statistica Sinica 等发表多篇高水平学术论文。
Dr. Danning Li is an Associate Professor in the School of Mathematics and Statistics at Northeast Normal University. My research focuses on the theoretical development and methodological innovations in high-dimensional statistics and large-scale hypothesis testing. Specifically, my work investigates power-enhanced tests for high-dimensional mean vectors and covariance matrices, robust estimation for compositional data (with critical applications in microbial inter-taxa and econometric analysis), and network data analysis. My research has been funded by the National NaturalScience Foundation of China (NSFC), and work appears in leading statistical,econometric, and biometrical journals, including the Journal of the American Statistical Association(JASA), Biometrics, Journal of Business & Economic Statistics (JBES), Test, and Statistica Sinica.
学术论文 / Selected Publications
[1]Yuan, Q., Liu, B. ,Li, D., & Ma, Y. (2025). Community extraction of network data under stochastic block models. Statistica Sinica, 35, 1789-1809.
[2]Li, D., Xue, L.*, Yang, H., & Yu, X. (2025). Power-enhanced two-sample mean tests for high-dimensional microbiome compositional data. Biometrics, 81(2), ujaf034-1-12.
[3] Hu, K., Li, D.*, & Liu, B. (2025). Reproducible Learning of Gaussian Graphical Models via Graphical Lasso Multiple Data Splitting. Acta Mathematica Sinica, English Series, 41(2), 553–568.
[4] Liu, T., Li, D.*, Ren, F., Sun, J., & Yuan, X. A new sufficient dimension reduction method via rank divergence. Test, 33(3), 921–950.
[5]Yu, X., Li, D.*, & Xue, L.* (2024). Fisher‘s Combined Probability Test for High-Dimensional Covariance Matrices. Journal of the American Statistical Association (JASA), 119(545), 511–524.
[6] Yu, X., Li, D.*, Xue, L.*, & Li, R. (2023). Power-Enhanced Simultaneous Test of High-Dimensional Mean Vectors and Covariance Matrices with Application to Gene-Set Testing. Journal of the American Statistical Association (JASA), 118(544), 2548–2561.
[7] Li, D., Srinivasan, A., Xue, L.*, & Zhan, X. (2023). Robust Covariance Matrix Estimation for High-Dimensional Compositional Data with Application to Sales Data Analysis. Journal of Business&Economics Statistics, 41(4), 1090–1100.
[8] Li, D., Srinivasan, A., Xue, L.*, & Zhan, X. (2023). Robust Shape Matrix Estimation for High-Dimensional Compositional Data with Application to Microbial Inter-Taxa Analysis. Statistica Sinica, 33, 1577–1602.
[9] Wang, P., Li, D.*, & Sun, J. (2021). A pairwise pseudo-likelihood approach for left-truncated and
interval-censored data under the Cox model. Biometrics, 77(4), 1303–1314.
教学与招生 / Teaching & Prospective Students
教学工作：长期承担数学与统计学院本科及研究生核心课程教学任务，教学态度严谨。
招生期待：本课题组招收硕士研究生（学术型硕士及应用统计专业硕士），欢迎具有扎实数学推导功底、良好编程实现能力并对高维统计推断、网络数据分析、生物信息/大健康交叉学科感兴趣的同学联系。
2020.12--今，东北师范大学，副教授。
2018.09--2020.09，美国宾夕法尼亚州立大学（Pennsylvania State University），冠名助理教授（Named Assistant Professor）。
2015.08--2018.08，吉林大学，讲师。
2013.07--2015.07，英国剑桥大学（University of Cambridge），博士后。
学习经历：
2008.08--2013.06，美国明尼苏达大学（University of Minnesota），统计学专业，博士。
1. 获国家天元数学东北中心优秀青年学者奖励计划资助 （2022年）
2. 国家级一流本科课程线下一流课程 概率论基础 参与人（2025年）