Hangjun Che

1.9k total citations · 2 hit papers
73 papers, 1.3k citations indexed

About

Hangjun Che is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Hangjun Che has authored 73 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Computer Vision and Pattern Recognition, 32 papers in Artificial Intelligence and 14 papers in Computational Mechanics. Recurrent topics in Hangjun Che's work include Face and Expression Recognition (28 papers), Neural Networks and Applications (14 papers) and Sparse and Compressive Sensing Techniques (13 papers). Hangjun Che is often cited by papers focused on Face and Expression Recognition (28 papers), Neural Networks and Applications (14 papers) and Sparse and Compressive Sensing Techniques (13 papers). Hangjun Che collaborates with scholars based in China, United Kingdom and Hong Kong. Hangjun Che's co-authors include Jun Wang, Man-Fai Leung, Cheng Liu, Chuandong Li, Xing He, Tingwen Huang, Shiping Wen, Chenglu Li, Yan Zheng and Zheng Yan and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and IEEE Transactions on Industrial Informatics.

In The Last Decade

Hangjun Che

62 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Robust multi-view non-negative matrix factorization with adaptive graph and diversity constraints

2023 82 citations Chenglu Li, Hangjun Che et al. profile →
Projected cross-view learning for unbalanced incomplete multi-view clustering

2024 53 citations Hangjun Che, Man-Fai Leung et al. Information Fusion profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Hangjun Che China	23	585	509	177	137	126	73	1.3k
Ye Yuan China	16	429 0.7×	290 0.6×	95 0.5×	94 0.7×	106 0.8×	52	1.0k
Aijia Ouyang China	19	424 0.7×	250 0.5×	57 0.3×	242 1.8×	157 1.2×	62	1.1k
Yiguang Liu China	23	398 0.7×	634 1.2×	109 0.6×	239 1.7×	134 1.1×	106	1.5k
Jie Zhou China	23	510 0.9×	466 0.9×	83 0.5×	52 0.4×	99 0.8×	111	1.4k
Bin Gu China	8	414 0.7×	330 0.6×	56 0.3×	117 0.9×	115 0.9×	10	1000
Pengcheng Wei China	18	298 0.5×	585 1.1×	52 0.3×	296 2.2×	52 0.4×	72	1.3k
Christian Schulz Germany	20	160 0.3×	372 0.7×	322 1.8×	193 1.4×	321 2.5×	62	1.3k
Alina Beygelzimer United States	14	841 1.4×	342 0.7×	49 0.3×	289 2.1×	59 0.5×	36	1.4k
Yang He China	14	864 1.5×	959 1.9×	58 0.3×	107 0.8×	67 0.5×	46	1.5k
Yuanxiang Li China	18	507 0.9×	175 0.3×	67 0.4×	76 0.6×	119 0.9×	103	964

Countries citing papers authored by Hangjun Che

Since Specialization

Citations

This map shows the geographic impact of Hangjun Che's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hangjun Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hangjun Che more than expected).

Fields of papers citing papers by Hangjun Che

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hangjun Che. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hangjun Che. The network helps show where Hangjun Che may publish in the future.

Co-authorship network of co-authors of Hangjun Che

This figure shows the co-authorship network connecting the top 25 collaborators of Hangjun Che. A scholar is included among the top collaborators of Hangjun Che based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hangjun Che. Hangjun Che is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Che, Hangjun, et al.. (2025). Robust Diverse Multi-View Learning for Cancer Subtyping. 22(6). 2685–2696.

Che, Hangjun, et al.. (2025). Robust Deep Matrix Factorization With Low-Rank and Hypergraph Learning for Multi-View Data Processing. IEEE Transactions on Consumer Electronics. 71(2). 4807–4818.

Che, Hangjun, et al.. (2025). Matrix Factorization for Multimedia Clustering.

Zhang, Wei, et al.. (2025). Bipartite Synchronization of Fractional-Order Multi-Layer Signed Network With a Non-Autonomous Leader. IEEE Transactions on Circuits and Systems I Regular Papers. 72(12). 8396–8407.

Che, Hangjun, et al.. (2025). High-order consensus graph learning for incomplete multi-view clustering. Applied Intelligence. 55(7). 4 indexed citations

Li, Guoxing, Yan Gan, Wei Zhang, & Hangjun Che. (2025). GS-YOLO: A lightweight and high-performance method for PCB surface defect detection. Expert Systems with Applications. 303. 130583–130583. 1 indexed citations

Che, Hangjun, et al.. (2024). Tensor-based unsupervised feature selection for error-robust handling of unbalanced incomplete multi-view data. Information Fusion. 114. 102693–102693. 23 indexed citations

Liu, Cheng, Rui Li, Hangjun Che, et al.. (2024). Latent Structure-Aware View Recovery for Incomplete Multi-View Clustering. IEEE Transactions on Knowledge and Data Engineering. 36(12). 8655–8669. 7 indexed citations

Che, Hangjun, et al.. (2024). Enhanced Tensorial Self-representation Subspace Learning for Incomplete Multi-view Clustering. 719–728. 1 indexed citations

10.

Che, Hangjun, et al.. (2024). Robust Hypergraph Regularized Deep Non-Negative Matrix Factorization for Multi-View Clustering. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(2). 1817–1829. 7 indexed citations

11.

Li, Chuandong, et al.. (2024). Error-robust multi-view subspace clustering with nonconvex low-rank tensor approximation and hyper-Laplacian graph embedding. Engineering Applications of Artificial Intelligence. 133. 108274–108274. 14 indexed citations

12.

Che, Hangjun, et al.. (2024). A Multi-Kernel-Based Multi-View Deep Non-Negative Matrix Factorization for Enhanced Healthcare Data Clustering. IEEE Transactions on Consumer Electronics. 71(1). 1442–1452. 3 indexed citations

13.

Liu, Cheng, Rui Li, Hangjun Che, et al.. (2024). Beyond Euclidean Structures: Collaborative Topological Graph Learning for Multiview Clustering. IEEE Transactions on Neural Networks and Learning Systems. 36(6). 10606–10618. 2 indexed citations

14.

Che, Hangjun, et al.. (2023). Centric graph regularized log-norm sparse non-negative matrix factorization for multi-view clustering. Signal Processing. 217. 109341–109341. 28 indexed citations

15.

Han, Xin, et al.. (2023). Distributed Neurodynamic Models for Solving a Class of System of Nonlinear Equations. IEEE Transactions on Neural Networks and Learning Systems. 36(1). 486–497. 2 indexed citations

16.

Che, Hangjun, et al.. (2023). Nonconvex low-rank tensor approximation with graph and consistent regularizations for multi-view subspace learning. Neural Networks. 161. 638–658. 41 indexed citations

17.

Huang, Zhiyong, Hangjun Che, Fang Xie, et al.. (2023). Segmentation of Brain Tissues from MRI Images Using Multitask Fuzzy Clustering Algorithm. Journal of Healthcare Engineering. 2023(1). 4387134–4387134. 7 indexed citations

18.

Wang, Zhenkun, Man-Fai Leung, Hangjun Che, & Carlos A. Coello Coello. (2023). Thematic issue on advances in analysis and application of multi-objective memetic optimization algorithms. Memetic Computing. 15(1). 1–2. 2 indexed citations

19.

Che, Hangjun, et al.. (2023). Low-Rank Tensor Regularized Graph Fuzzy Learning for Multi-View Data Processing. IEEE Transactions on Consumer Electronics. 70(1). 2925–2938. 46 indexed citations

20.

Yang, Xinsong, et al.. (2023). Neurodynamic optimization approaches with finite/fixed-time convergence for absolute value equations. Neural Networks. 165. 971–981. 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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