冯龙

2005年9月---2009年6月  南开大学      数学试点班

2009年9月---2014年6月  南开大学      硕博连读  （导师：王兆军教授） 

2015年1月---2016年1月  佛罗里达大学     博士后   （导师：邱培华教授）

2014年7月--2019年6月 东北师范大学 讲师

2019年7月--2021年7月 东北师范大学 副教授

2021年12月--至今    南开大学    副教授、特聘研究员

冯龙现任南开大学统计与数据科学学院副教授、特聘研究员、博士生导师。2022年入选教育部青年人才计划、南开大学百名青年学科带头人。本科毕业于南开大学数学科学学院陈省身数学试点班，博士毕业于南开大学数学科学学院概率论与数理统计专业，获得南开大学优秀博士论文奖。主要从事质量控制、非参数模型、高维数据分析、高频数据分析方面的研究。曾获得2012年教育部学术新人奖，2022年天津市数学与统计联合会议青年学者奖，于2012-2014年分别访问香港浸会大学、新加坡国立大学和香港大学，2015年于美国佛罗里达大学做博士后研究。在统计学国际顶尖杂志Journal of the Royal Statistical Society: Series B、Journal of American Statistical Association、Biometrika、Annals of Statistics、Journal of Econometrics、Journal of Business and Economic Statistics、Technometrics等发表SCI论文40余篇。曾主持一项国家自然科学基金青年项目，正主持一项国家自然科学基金面上项目，天津市杰出青年基金项目，南开大学百青项目一项。

高维数据分析、计量经济学、高频数据分析、变点检测等

2022年春季学期   极限理论（概率论II）  本科生课程

2022年秋季学期   数理统计         本科生课程

2023年春季学期   极限理论         本科生课程

2023年秋季学期    数理统计           本科生课程

2023年秋季学期    高维数据统计推断         研究生课程

2016年1月--2018年12月  国家自然科学基金青年项目 超高维数据中若干检验问题的研究

2015年1月--2016年12月   东北师范大学校内青年基金  高维数据中若干检验问题的研究

2022年1月--2025年12月   南开大学校级人才科研经费  高维数据检验中的若干问题研究

2023年1月--2026年12月  国家自然科学基金面上项目  基于求和与极值渐进独立性的若干高维数据检验问题的研究

2023年10月--2027年9月  天津市杰出青年科学基金   高维复杂数据分析

代表作

1. Feng Long, Zou Changliang and Wang Zhaojun. (2016). Multivariate-sign-based high-dimensional tests for the two-sample location problem, Journal of American Statistical Association. 111, 721-735.

2. Feng Long, Jiang tiefeng, Liu Binghui and Xiong wei. (2022) Max-sum tests for cross-sectional independence of high-dimensional panel data. Annals of Statistics. 50(2), 1124-1143.

3. Wang guanghui and Feng Long*. (2023) Computationally efficient and data-adaptive change point inference in high dimensions. Journal of the Royal Statistical Society: Series B 85(3), 936-958.

4. Zou Changliang, Peng Liuhua, Feng Long andWang Zhaojun (2014). Multivariate-signs based high-dimensional tests for sphericity. Biometrika. 101(1), 229-236.

5. Zou Changliang, Yin Guosheng, Feng Long and Wang Zhaojun(2014).Nonparametric maximum likelihood approach to multiple change-point problems. Annals of Statistics.42 (3), 970-1002.

6. Feng Long, Lan Wei, Liu binghui and Ma yanyuan. (2022) High-dimensionaltest for alpha in  linear factorpricing models with sparse alternatives. Journal of Econometrics.229(1), 152-175.

7. Wang hongfei, Liu Binghui,Feng Long*and Ma yanyuan. (2023). Rank-based max-sum tests for mutual independence of high-dimensional random vectors. Journal of Econometrics Accepted.

8. Feng Long and Qiu Peihua (2018) Difference detection between two images for image monitoring.Technometrics, 60, 345-359.

9. Feng Long, Liu binghui and Ma yanyuan. (2021) An Inverse Norm Sign Test of Location Parameter for High-Dimensional Data.Journal of Business and Economic Statistics.39 (3), 807-815.

10. Feng Long, Liu binghui and Ma yanyuan. (2023)A one-sided refined symmetrized data aggregation approach to robust mutual fund selection.Journal of Business and Economic Statistics.Accepted

11. Ma Huifang, Feng Long*, Wang Zhaojun and Bao Jigang (2024) Adaptive Testing for Alphas in Conditional Factor Models with High Dimensional Assets. Journal of Business and Economic StatisticsAccepted.

12. Lan Wei,Lei Bo,Feng Long*and Tsai Chih-Ling. (2024). Tests of Equal Predictive Ability Based on Subsampling-Maximum Type Statistic. Journal of Business and Economic Statistics.Accepted.

13. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing. (2015) Two Sample Behrens-Fisher problem for high-dimensional data. Statistica Sinica. 25, 1297-1312.

14. Feng Long, Wang Zhaojun, Zhang Chunming and Zou Changliang. (2016) Nonparametric testing in regression models with Wilcoxon-type generalized likelihood ratio. Statistica Sinica. 26, 137-155.

15. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing (2017) Composite T-2 test for high dimensional data. Statistica Sinica, 27, 1419-1436.

16. Liu binghui,Feng Long*and Ma yanyuan. (2022) High-dimensional alpha test of linearfactor pricing models with heavy-tailed distributions. Statistica Sinica. Online published

17. Feng Long, Jiang Tiefeng,Li Xiaoyun and Liu Binghui. (2023) Asymptotic Independence of the Sum and Maximum of Dependent Random Variables with Applications to High-Dimensional Tests.  Statistica Sinica.Accepted

18. Chen dachuan, Song Fengyi and Feng Long*(2023) Rank-based tests for high dimensional white noise. Statistica Sinica.Accepted

其他已发表论文

1. Feng Long, Zou Changliang, and Wang Zhaojun (2012).local walsh average regression. Journal of Multivariate Analysis. 106(1), 36-48.

2. Feng Long, Zou Changliang, and Wang Zhaojun (2012).Rank-based inference for single-index model Statistics and Probability Letters. 82(3), 535-541.

3. Feng Long, Zou Changliang, Wang Zhaojun and Chen bin (2013). Rank-based score tests for high-dimensional regression coefficients. Electronic Journal of Statistics. 7, 2131-2149.

4. Feng Long, Zou Changliang, Wang Zhaojun, Wei Xianwu and Chen bin. (2015). Robust Spline-Based Variable Selection in Varying Coefficient Model.  Metrika. 78 (1), 85-118.

5. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing. (2015) Robust comparison of regression curves. Test. 24 (1), 185-204.

6. Feng Longand Sun Fasheng. (2015). A note on the high dimensional two sample test.Statistics and Probability Letters.105, 29-36.

7. Feng Long and Sun Fasheng. (2016). Spatial sign based high dimensional location test. Electronic Journal of Statistics.10, 2420-2434.

8. Feng Long and Liu binhui (2017). High dimensional rank tests for sphericity. Journal of Multivariate Analysis 155, 217-233.

9. Lan wei, Feng Long and Luo ronghua (2018). Testing high dimensional linear asset pricing model. Journal of Financial Econometrics 16 (2), 191-210.

10. Feng Long, Ren haojieand Zou Changliang (2020). A setwise EWMA scheme for monitoring high-dimensional datastreams.Random Matrices: Theory and Applications. 9, 2050004.

11. Feng Long, Zhang xiaoxu and Liu binghui. (2020) A high-dimensional spatial rank test for two-sample location problems. Computational Statistics and Data Analysis. 144,106889.

12. Feng Long, Zhang xiaoxu and Liu binghui. (2020) Multivariate tests of independence and their application in correlation analysis between financial markets. Journal of Multivariate Analysis.179, 104652.

13. Feng Long, Ding Yanling and Liu Binghui. (2020) Rank-based tests for cross-sectional dependence in large (N,T) fixed effects panel data models. Oxford Bulletin of Economics and Statistics. 82, 1198-1216.

14. Feng Long, Zhao Ping, Ding Yanling, Liu Binghui (2021) Rank-based tests of cross-sectional dependence in panel data models. Computational Statistics and Data Analysis. 153, 107070.

15. Wang hongfei, Feng Long* and Liu Binghui, Zhou Qin.(2021) An inverse norm weight spatial sign test for high-dimensional directional data. Electronic Journal of Statistics,15(1),3249-3286.

16. Ding Yanling, Liu Binghui, Zhao Ping  and Feng Long* (2022) Rank-based test for slope homogeneity in highdimensional panel data models. Metrika. 85(5), 605-626.

17. Feng Long, Zhang xiaoxu and Liu binghui (2022) High-dimensional proportionality test of two covariance matrices and its application to gene expression data.Statistical Theory and Related Fields. 6 (2), 161-174.

18. Zhang Xiaoxu, Zhao Ping and Feng Long*. (2022) Robust sphericity test in the panel data model. Statistics and Probability Letters.182, 109304.

19. Huang Xifen, Liu Binghui, and Zhou Qinand Feng Long*. (2022) High-dimensional inverse norm sign test fortwo-sample location problems. Canadian Journal of Statistics.Online published.

20. Meng Jing, Feng Long,Zou Changliang,Wang Zhaojun. (2022) Covariate-Assisted Matrix Completion with Multiple Structural Breaks. Journal of Systems Science & Complexity,Accepted.

21. Wang Guanghui, Feng Longand Zhao Ping.(2023) Tests for slope homogeneity in large panel data model. Communications in Mathematics and Statistics.Accepted.

22. Chen dachuan, Feng Long and Liang Decai. (2023). Asymptotic Independence of the Quadratic form and Maximum of Independent Random Variables with Applications to High-Dimensional Tests. Acta Mathematica, English Series,Accepted.

23. Zhang yuhao, Liu yanhong, Feng Long*and Wang Zhaojun. (2023). Testing The Differential Network Between Two Gaussian Graphical Models With False Discovery Rate Control. Journal Of Statistical Computation And SimulationAccepted.

学术访问经历

2012.3-2012.6        香港浸会大学         朱力行教授

2013.8-2013.9        新加坡国立大学        夏应存教授

2014.2-2014.3        香港大学               尹国圣教授

2021.8-2021.11       南方科技大学         陈欣 副教授

2022年 教育部青年人才计划

2022年 天津市数学与统计联合学术年会“青年学者奖”

2022年 南开大学百名青年学科带头人

2015年 南开大学优秀博士论文

2012年 教育部学术新人奖