Scholar
Long Feng
Google Scholar ID: ehSG_E8AAAAJ
Professor of Nankai University
Citations & Impact
Citations
662
H-index
14
i10-index
20
Publications
20
Co-authors
23
list available
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- - Projects:
- - January 2016-December 2018, Some studies on ultra high dimension data hypothesis testing problems, The National Natural Science Foundation Youth Project
- - January 2023-December 2026, Some studies on high dimensional hypothesis testing problems based on the asymptotic independence between sum and max of random vectors, The National Natural Science Foundation of China
- - October 2023-September 2027, High-dimensional complex data analysis, Tianjin Science Fund for Outstanding Young Scholar
- - Honors and Awards:
- - Young Changjiang Scholar of the Ministry of Education in 2023
- - The 'Young Scholar Award' of the 2022 Tianjin Mathematics and Statistics Joint Academic Annual Conference
- - 100 young academic leaders of Nankai University in 2022
- - Excellent Doctoral Dissertation of Nankai University in 2015
- - Publications:
- - 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.
- - 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.
- - 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.
- - Zou Changliang, Peng Liuhua, Feng Long and Wang Zhaojun (2014). Multivariate-signs based high-dimensional tests for sphericity. Biometrika. 101(1), 229-236.
- - 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.
- - Feng Long, Lan Wei, Liu binghui and Ma yanyuan. (2022) High-dimensional test for alpha in linear factor pricing models with sparse alternatives. Journal of Econometrics. 229(1), 152-175.
- - Wang hongfei, Liu Binghui, Feng Long* and Ma yanyuan*. (2024). Rank-based max-sum tests for mutual independence of high-dimensional random vectors. Journal of Econometrics 238,105578.
- - Feng Long and Qiu Peihua (2018) Difference detection between two images for image monitoring. Technometrics, 60, 345-359.
- - 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.
- - 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
- - 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 Statistics Accepted.
Research Experience
- - July 2014--June 2019, Northeast Normal University, Assistant Professor
- - July 2019--July 2021, Northeast Normal University, Associate Professor
- - December 2021-December 2023, Nankai University, Associate Professor
- - January 2024-now, Nankai University, Professor
- - Visiting Experience:
- - March. 2012-June. 2012, Hong Kong Baptist University, Hong Kong
- - August. 2013-September. 2013, National University of Singapore, Singapore
- - February. 2014-March. 2014, University of Hong Kong, Hong Kong
- - January. 2015-January. 2016, University of Florida, USA
- - August. 2021-November. 2021, Southern University of Science and Technology, China
Education
- - Ph.D., Statistics, Nankai University, 2014
- - B.S., Mathematics (Chern Class), Nankai University, 2009
Background
- - Research Interests: Non-parametric and semi-parametric regression, high-dimensional data, change point detection
- - Position: Professor
- - Affiliation: School of Statistics and Data Science, Nankai University
