虞龙

发布者：严继臧发布时间：2022-09-30浏览次数：10361

姓　　名：虞龙

职　　称：副教授
研究方向：因子模型，高维数据分析，随机矩阵理论
教授课程：《统计学》本科课程、《统计学习》硕博课程、专硕课程

E - mail：yulong@mail.shufe.edu.cn 电话：021-65901469

研究项目

序号	项目名称	项目编号	项目来源	起止时间	项目经费
1	若干非线性高维矩阵值因子模型的研究	12301350	国家自科青年基金项目	2024-2026	30万元
2	高维张量数据的因子建模方法及其在金融经济等领域的应用	23PJ1402700	上海市浦江人才计划A类	2023-2025	30万元

教育经历

2015.9-2020.6 复旦大学管理学院统计学系博士

2018.9-2019.8 美国密歇根大学安娜堡分校统计系联合培养

2011.9-2015.6 复旦大学管理学院统计学系学士

工作经历

2024.7-至今上海财经大学统计与管理学院副教授

2022.9-2024.6 上海财经大学统计与管理学院助理教授

2020.9-2022.9 新加坡国立大学数据科学与统计系博士后研究员

学术兼职

任Journal of Multivariate Analysis 编委(Early Career Advisory Board)成员

https://www.sciencedirect.com/journal/journal-of-multivariate-analysis/about/editorial-board

中国现场统计研究会多元分析应用专业委员会理事

中国现场统计研究会随机矩阵理论与应用分会理事

研究成果

[1].Yu, L., Zhao, P., & Zhou, W. (2025). Testing the number of common factors by bootstrapped sample covariance matrix in high-dimensional factor models. Journal of the American Statistical Association, 120(549), 448-459.https://doi.org/10.1080/01621459.2024.2346364

[2].Wang, Y., & Yu, L. (2025). Robust factorization for high-dimensional matrix-variate observations. Journal of Multivariate Analysis, 105467.https://doi.org/10.1016/j.jmva.2025.105467

[3].He, Y., Wang, Y., Yu, L., Zhou, W., & Zhou, W. X. (2025). A new non-parametric Kendall’s tau for matrix-valued elliptical observations. Bernoulli, 31(4), 3331-3355.DOI: 10.3150/24-BEJ1849

[4].He, Y., Kong, X., Trapani, L., & Yu, L. (2024). Online change-point detection for matrix-valued time series with latent two-way factor structure. The Annals of Statistics, 52(4), 1646-1670.DOI: 10.1214/24-AOS2410

[5].He, Y., Kong, X., Yu, L., Zhang, X., & Zhao, C. (2024). Matrix factor analysis: From least squares to iterative projection. Journal of Business & Economic Statistics, 42(1), 322-334.https://doi.org/10.1080/07350015.2023.2191676

[6].Yu L., Xie J., Zhou W. (2023). Testing Kronecker Product Covariance Matrices for High-Dimensional Matrix-Variate Data. Biometrika, 110(3), 799-814.doi: 10.1093/biomet/asac063.

[7].He Y., Kong X., Trapani L., & Yu L. (2023). One-way or Two-way Factor Model for Matrix Sequences? Journal of Econometrics, 235(2), 1981-2004.https://doi.org/10.1016/j.jeconom.2023.02.008

[8].Yu, L., He, Y., Kong, X., & Zhang, X. (2022). Projected estimation for large-dimensional matrix factor models. Journal of Econometrics, 229(1), 201-217.https://doi.org/10.1016/j.jeconom.2021.04.001

[9].He, Y., Kong, X., Yu, L, & Zhang, X. (2022). Large-dimensional factor analysis without moment constraints. Journal of Business & Economic Statistics, 40(1), 302-312.https://doi.org/10.1080/07350015.2020.1811101

[10].Wen, J., Xie J., Yu L, & Zhou, W. (2022). Tracy-Widom limit for the largest eigenvalue of high-dimensional covariance matrices in elliptical distributions. Bernoulli, 28(4), 2941-2967.DOI: 10.3150/21-BEJ1443

[11].Chen H., Guo Y., He Y., Ji J., Liu L., Shi Y., Wang Y., Yu L, Zhang X. (2022). Simultaneous Differential Network Analysis and Classification for Matrix-variate Data with Application to Brain Connectivity. Biostatistics, 23(3), 967–989.https://doi.org/10.1093/biostatistics/kxab007

[12].Zhao, B., Yu, L., Wang, C., Shuai, C., Zhu, J., Qu, S., Taiebat M, & Xu, M. (2021). Urban Air Pollution Mapping Using Fleet Vehicles as Mobile Monitors and Machin Learning. Environmental Science & Technology, 2021 55(8), 5579-5588.https://doi.org/10.1021/acs.est.0c08034

[13].Yu, L., He, Y., & Zhang, X. (2019). Robust factor number specification for large-dimensional elliptical factor model. Journal of Multivariate analysis, 174, 104543.https://doi.org/10.1016/j.jmva.2019.104543

Preprint:

[1].Ding X., Xie J., Yu L., Zhou W. (2025+). Multiplier bootstrap meets high-dimensional PCA: the good, the bad and the modification. https://xcding1212.github.io/m1.pdf

[2].Kong, X., Liu, Y., Yu, L., & Zhao, P. (2025+). Matrix Quantile Factor Model. arXiv:2208.08693