World's Best Scientists 2026 revealed!
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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
109
Citations
45722
World Ranking
244
National Ranking
30

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2023 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in China Leader Award

Overview

Feiping Nie is affiliated with Northwestern Polytechnical University in China, contributing extensively to the field of computer science with a focus on areas such as computer vision and pattern recognition, artificial intelligence, and related subfields. Their research spans a range of topics including face and expression recognition, clustering algorithms, remote-sensing image classification, and machine learning techniques.

Their frequent publication venues demonstrate a concentration in high-impact journals and conferences, such as:

  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Knowledge and Data Engineering
  • Pattern Recognition
  • Information Sciences
  • Neurocomputing

Feiping Nie has contributed to several recent research papers, notable among them are:

  • "Multiview Clustering: A Scalable and Parameter-Free Bipartite Graph Fusion Method," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "An Effective and Efficient Algorithm for K-Means Clustering With New Formulation," 2022, IEEE Transactions on Knowledge and Data Engineering
  • "Fast Multi-View Clustering via Nonnegative and Orthogonal Factorization," 2020, IEEE Transactions on Image Processing
  • "Rethinking Maximum Mean Discrepancy for Visual Domain Adaptation," 2021, IEEE Transactions on Neural Networks and Learning Systems

The scientist collaborates frequently with a group of co-authors, including:

  • Xuelong Li
  • Rong Wang
  • Zheng Wang
  • Danyang Wu

The main fields of study and subfields covered by Feiping Nie's work include:

  • Computer Science
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Media Technology
  • Urban Studies
  • Computational Mechanics

Feiping Nie's research topics highlight their focus on algorithmic development and classification technologies, encompassing:

  • Face and Expression Recognition
  • Advanced Clustering Algorithms Research
  • Remote-Sensing Image Classification
  • Advanced Computing and Algorithms
  • Text and Document Classification Technologies
  • Sparse and Compressive Sensing Techniques
  • Machine Learning and Extreme Learning Machines (ELM)

Best Publications

  • Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization

    Feiping Nie;Heng Huang;Xiao Cai;Chris H. Ding

  • Clustering and projected clustering with adaptive neighbors

    Feiping Nie;Xiaoqian Wang;Heng Huang

  • The Constrained Laplacian Rank algorithm for graph-based clustering

    Feiping Nie;Xiaoqian Wang;Michael I. Jordan;Heng Huang

  • Learning a Mahalanobis distance metric for data clustering and classification

    Shiming Xiang;Feiping Nie;Changshui Zhang

  • Multi-view Subspace Clustering

    Hongchang Gao;Feiping Nie;Xuelong Li;Heng Huang

  • Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection

    Chenping Hou;Feiping Nie;Xuelong Li;Dongyun Yi

  • Large-scale multi-view spectral clustering via bipartite graph

    Yeqing Li;Feiping Nie;Heng Huang;Junzhou Huang

  • Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction

    Feiping Nie;Dong Xu;Ivor Wai-Hung Tsang;Changshui Zhang

  • Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours

    Feiping Nie;Guohao Cai;Xuelong Li

  • Multi-view K-means clustering on big data

    Xiao Cai;Feiping Nie;Heng Huang

  • Multi-Class Active Learning by Uncertainty Sampling with Diversity Maximization

    Yi Yang;Zhigang Ma;Feiping Nie;Xiaojun Chang

  • Discriminative Least Squares Regression for Multiclass Classification and Feature Selection

    Shiming Xiang;Feiping Nie;Gaofeng Meng;Chunhong Pan

  • Self-weighted Multiview Clustering with Multiple Graphs.

    Feiping Nie;Jing Li;Xuelong Li

  • Multiview Consensus Graph Clustering

    Kun Zhan;Feiping Nie;Jing Wang;Yi Yang

  • A Multimedia Retrieval Framework Based on Semi-Supervised Ranking and Relevance Feedback

    Yi Yang;Feiping Nie;Dong Xu;Jiebo Luo

  • Image Clustering Using Local Discriminant Models and Global Integration

    Yi Yang;Dong Xu;Feiping Nie;Shuicheng Yan

  • Parameter-free auto-weighted multiple graph learning: a framework for multiview clustering and semi-supervised classification

    Feiping Nie;Jing Li;Xuelong Li

  • Multi-view Clustering: A Scalable and Parameter-free Bipartite Graph Fusion Method.

    Xuelong Li;Han Zhang;Rong Wang;Feiping Nie

  • Trace ratio criterion for feature selection

    Feiping Nie;Shiming Xiang;Yangqing Jia;Changshui Zhang

  • Auto-Weighted Multi-View Learning for Image Clustering and Semi-Supervised Classification.

    Feiping Nie;Guohao Cai;Jing Li;Xuelong Li

  • Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering

    Feiping Nie;Zinan Zeng;I. W. Tsang;Dong Xu

  • Low-rank matrix recovery via efficient schatten p-norm minimization

    Feiping Nie;Heng Huang;Chris Ding

Frequent Co-Authors

Xuelong Li
Xuelong Li China Telecom (China)
Heng Huang
Heng Huang University of Pittsburgh
Changshui Zhang
Changshui Zhang Tsinghua University
Hua Wang
Hua Wang Victoria University
Chris Ding
Chris Ding Chinese University of Hong Kong, Shenzhen
Shiming Xiang
Shiming Xiang Chinese Academy of Sciences
Xiaojun Chang
Xiaojun Chang University of Technology Sydney
Junwei Han
Junwei Han Northwestern Polytechnical University
Quanxue Gao
Quanxue Gao Xidian University
Dong Xu
Dong Xu University of Hong Kong

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