Search
Chinese
Home
Personal Profile
Feiping Nie, Professor, PhD Tutor
Title: Leading talents of the ministry of science and technology
Scholar Homepages: [Google Scholar] | [DBLP] | [NWPU]
Research Direction：Data analysis, Machine learning.
Contact Address: P.O. Box 64, 127 West Youyi Road, Beilin District, Xi'an 710000, Shaanxi, P.R. China
Zip Code: 710072
E-mail: feipingnie@gmail.com
Education Background
He received the Ph.D. degree in computer science from Tsinghua University, Beijing, China, in 2009.
Work Experience
From December 2010 to August 2015, he worked at the University of Texas at Arlington. From September 2015 until now, he has been a professor at Northwestern Polytechnical University in China.
Honors
The first prize of CCF Science and Technology Award for Natural Science
The second prize of Wu Wenjun Artificial Intelligence Science and Technology Award
The second prize of the Science and Technology Award of the Chinese Society of Image and Graphics
Selected into the Clarivate Analytics "Global Highly Cited Scientists" list
Selected into the Elsevier's "Highly Cited Scholars in China" list
Selected into the Guide2Research "Top Computer Scientists in the World" list
Ranked 9th in the world's first Chinese AI academic influence TOP100 list released by Xinzhiyuan
Ranked 5th in the world in the classic AI subfield in the 2020 list of the most influential people in artificial intelligence released by Tsinghua University
Academic Service
Journal reviewer:T-PAMI, IJCV, JMLR
Editorial board member:T-NNLS, Information Fusion, Information Science, Pattern Recognition, Neural Processing Letters
Senior Program committee member：Association for the Advance of Artificial Intelligence(2017,2018)
Senior Program committee member：International Joint Conference on Artificial Intelligence(2018,2019)
Area Chair：Chinese Conference on Pattern Recognition(2016)
Area Chair：International Conference on Pattern Recognition(2016,2018)
Area Chair：International Conference on Data Mining(2018)
Special guest speaker:The seminar "Basic Theory and Application of Machine Learning" at Tsinghua University（2017）
Special guest speaker:The 9th "National Conference on Computer Mathematics"（2017）
Special guest speaker:The annual report meeting of the "Knowledge Intelligence Joint Research center"（2019）
Representative Papers
F. Nie*, J. Li, and X. Li, "Convex multiview semi-supervised classification", IEEE Transactions on Image Processing (IF: 6.79), vol. 26, no. 12, pp. 5718-5729, 2017. [PDF]
F. Nie*, G. Cai, J. Li, and X. Li, "Auto-weighted multi-view learning for image clustering and semi-supervised classification", IEEE Transactions on Image Processing (IF: 6.79), vol. 27, no. 3, pp. 1501-1511, 2018. [PDF]
Q. Wang, J. Wan, F. Nie*, B. Liu, C. Yan, and X. Li, "Hierarchical feature selection for random projection", IEEE Transactions on Neural Networks and Learning Systems (IF: 11.683), vol. 30, no. 5, pp. 1581-1586, 2018. [PDF]
F. Nie*, Z. Hu, and X. Li, "Matrix completion based on non-convex low-rank approximation", IEEE Transactions on Image Processing (IF: 6.79), vol. 28, no. 5, pp. 2378-2388, 2019. [PDF]
F. Nie*, H. Zhang, R. Zhang, and X. Li, "Robust multiple rank-k bilinear projections for unsupervised learning", IEEE Transactions on Image Processing (IF: 6.79), vol. 28, no. 5, pp. 2574-2582, 2019. [PDF]
Y. Yang, Z. Ma, F. Nie*, X. Chang, and Alexander G. Hauptmann, "Multi-class active learning by uncertainty sampling with diversity maximization", International Journal of Computer Vision, vol. 113, no. 2, pp. 113-127, 2015. [PDF]
Z. Li, F. Nie*, X. Chang, and Y. Yang, "Beyond trace ratio:weighted harmonic mean of trace ratios for multiclass discriminant analysis", IEEE Transactions on Knowledge and Data Engineering (IF: 3.857), vol. 29, no. 10, pp. 2100-2110, 2017. [PDF]
X. Chang, F. Nie*, S. Wang, Y. Yang, X. Zhou, and C. Zhang, "Compound rank-k projections for bilinear analysis", IEEE Transactions on Neural Networks and Learning Systems (IF: 11.683), vol. 27, no. 7, pp. 1502-1513, 2016. [PDF]
R. Zhang, F. Nie*, and X. Li, "Self-weighted supervised discriminative feature selection", IEEE Transactions on Neural Networks and Learning Systems (IF: 11.683), vol. 29, no. 8, pp. 3913-3918, 2018. [PDF]
Q. Wang, Z. Qin, F.Nie*, and X. Li, "Spectral embedded adaptive neighbors clustering", IEEE Transactions on Neural Networks and Learning Systems (IF: 11.683), vol. 30, no. 4, pp. 1265-1271, 2019. [PDF]