Chang‐Dong Wang

7.9k total citations · 2 hit papers
232 papers, 5.2k citations indexed

About

Chang‐Dong Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Chang‐Dong Wang has authored 232 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 145 papers in Artificial Intelligence, 95 papers in Computer Vision and Pattern Recognition and 59 papers in Information Systems. Recurrent topics in Chang‐Dong Wang's work include Face and Expression Recognition (61 papers), Advanced Graph Neural Networks (56 papers) and Advanced Clustering Algorithms Research (53 papers). Chang‐Dong Wang is often cited by papers focused on Face and Expression Recognition (61 papers), Advanced Graph Neural Networks (56 papers) and Advanced Clustering Algorithms Research (53 papers). Chang‐Dong Wang collaborates with scholars based in China, United States and United Arab Emirates. Chang‐Dong Wang's co-authors include Jianhuang Lai, Dong Huang, Ling Huang, Philip S. Yu, Man-Sheng Chen, Hongyang Chao, Guangyu Zhang, Yumeng Xu, Yuren Zhou and Zhi‐Hong Deng and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Expert Systems with Applications.

In The Last Decade

Chang‐Dong Wang

207 papers receiving 5.2k citations

Hit Papers

Fast Multi-View Clustering Via Ensembles: Towards Scalabi... 2023 2026 2024 2025 2023 2023 50 100 150
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.

  1. Fast Multi-View Clustering Via Ensembles: Towards Scalability, Superiority, and Simplicity
    2023 155 citations Dong Huang, Chang‐Dong Wang et al. IEEE Transactions on Knowledge and Data Engineering profile →
  2. Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning
    2023 112 citations Dong Huang, Chang‐Dong Wang et al. IEEE Transactions on Neural Networks and Learning Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chang‐Dong Wang China 41 3.1k 2.8k 843 628 518 232 5.2k
En Zhu China 43 3.8k 1.2× 4.0k 1.4× 429 0.5× 565 0.9× 787 1.5× 233 6.2k
Zenglin Xu China 42 3.8k 1.2× 3.6k 1.3× 428 0.5× 400 0.6× 736 1.4× 212 6.4k
Shitong Wang China 44 3.9k 1.2× 2.4k 0.9× 310 0.4× 215 0.3× 526 1.0× 406 6.9k
Vikas Sindhwani United States 28 3.7k 1.2× 2.8k 1.0× 628 0.7× 324 0.5× 456 0.9× 71 6.0k
Deng Cai China 27 2.1k 0.7× 3.5k 1.2× 344 0.4× 302 0.5× 953 1.8× 67 5.5k
Wenzhong Guo China 39 1.9k 0.6× 1.4k 0.5× 872 1.0× 309 0.5× 359 0.7× 271 5.3k
Yiu‐ming Cheung Hong Kong 43 2.7k 0.9× 3.5k 1.3× 361 0.4× 197 0.3× 704 1.4× 362 6.8k
Benyu Zhang China 18 1.6k 0.5× 2.4k 0.8× 528 0.6× 199 0.3× 635 1.2× 36 3.8k
Huaxiang Zhang China 40 2.1k 0.7× 2.5k 0.9× 462 0.5× 209 0.3× 270 0.5× 233 5.4k
Lifang He China 33 2.2k 0.7× 1.0k 0.4× 431 0.5× 563 0.9× 117 0.2× 175 4.2k

Countries citing papers authored by Chang‐Dong Wang

Since Specialization
Citations

This map shows the geographic impact of Chang‐Dong Wang'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 Chang‐Dong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang‐Dong Wang more than expected).

Fields of papers citing papers by Chang‐Dong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang‐Dong Wang. 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 Chang‐Dong Wang. The network helps show where Chang‐Dong Wang may publish in the future.

Co-authorship network of co-authors of Chang‐Dong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Chang‐Dong Wang. A scholar is included among the top collaborators of Chang‐Dong Wang 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 Chang‐Dong Wang. Chang‐Dong Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yang, Chenmin, et al.. (2025). Towards multi-fusion graph neural network for single-cell RNA sequence clustering. Neurocomputing. 631. 129764–129764.
2.
Yu, Philip S., et al.. (2025). Online Learning for Noisy Labeled Streams. ACM Transactions on Knowledge Discovery from Data. 19(6). 1–29.
3.
Zhang, Guangyu, et al.. (2025). Scalable tri-factorization guided multi-view subspace clustering. Knowledge-Based Systems. 312. 113119–113119. 4 indexed citations
4.
5.
Huang, Dong, et al.. (2024). DeepCluE: Enhanced Deep Clustering via Multi-Layer Ensembles in Neural Networks. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(2). 1582–1594. 9 indexed citations
6.
Zhang, Guangyu, Dong Huang, & Chang‐Dong Wang. (2024). Tensorized Incomplete Multi-view Kernel Subspace Clustering. Neural Networks. 179. 106529–106529. 6 indexed citations
7.
Huang, Dong, et al.. (2024). GLAC-GCN: Global and Local Topology-Aware Contrastive Graph Clustering Network. IEEE Transactions on Artificial Intelligence. 6(6). 1448–1459. 7 indexed citations
8.
Wang, Chang‐Dong, et al.. (2024). Time-Aware Multibehavior Contrastive Learning for Social Recommendation. IEEE Transactions on Industrial Informatics. 20(4). 6424–6435. 5 indexed citations
9.
Dai, Qingyun, et al.. (2024). MuSAM: Mutual-Scenario-Aware Multimodal-Enhanced Representation Learning for Semantic Similarity. IEEE Transactions on Industrial Informatics. 20(9). 11161–11170.
10.
Dai, Qingyun, et al.. (2024). MIGP: Metapath Integrated Graph Prompt Neural Network. Neural Networks. 179. 106595–106595. 2 indexed citations
11.
Khan, Latif U., Mohsen Guizani, Chang‐Dong Wang, & Di Wu. (2024). Resource Optimized Network Virtualization Empowered Metaverse for Wireless Networks. 4251–4256. 1 indexed citations
12.
Lin, Jiaqi, et al.. (2024). Dual Information Enhanced Multiview Attributed Graph Clustering. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 6466–6477. 11 indexed citations
13.
Huang, Dong, et al.. (2023). Strongly augmented contrastive clustering. Pattern Recognition. 139. 109470–109470. 55 indexed citations
14.
Chen, Zihao, et al.. (2023). Post-Distillation via Neural Resuscitation. IEEE Transactions on Multimedia. 26. 3046–3060. 1 indexed citations
15.
Wang, Chang‐Dong, et al.. (2023). Consensus Seeking in Large-Scale Multiagent Systems With Hierarchical Switching-Backbone Topology. IEEE Transactions on Neural Networks and Learning Systems. 35(11). 15810–15824. 3 indexed citations
16.
Wang, Chang‐Dong, Man-Sheng Chen, Ling Huang, Jianhuang Lai, & Philip S. Yu. (2020). Smoothness Regularized Multiview Subspace Clustering With Kernel Learning. IEEE Transactions on Neural Networks and Learning Systems. 32(11). 5047–5060. 43 indexed citations
17.
Wang, Kai, et al.. (2019). Inter-Intra Information Preserving Attributed Network Embedding. IEEE Access. 7. 79463–79476. 4 indexed citations
18.
Huang, Ling, Chang‐Dong Wang, & Hongyang Chao. (2019). HM-Modularity: A Harmonic Motif Modularity Approach for Multi-Layer Network Community Detection. IEEE Transactions on Knowledge and Data Engineering. 33(6). 2520–2533. 31 indexed citations
19.
Huang, Ling, Chang‐Dong Wang, Hongyang Chao, & Philip S. Yu. (2019). MVStream: Multiview Data Stream Clustering. IEEE Transactions on Neural Networks and Learning Systems. 31(9). 3482–3496. 46 indexed citations
20.
Huang, Ling, Hongyang Chao, & Chang‐Dong Wang. (2018). Multi-view intact space clustering. Pattern Recognition. 86. 344–353. 92 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by En Zhu Breakdown of academic impact, for papers by Zenglin Xu Breakdown of academic impact, for papers by Shitong Wang Breakdown of academic impact, for papers by Vikas Sindhwani Breakdown of academic impact, for papers by Deng Cai Breakdown of academic impact, for papers by Wenzhong Guo Breakdown of academic impact, for papers by Yiu‐ming Cheung Breakdown of academic impact, for papers by Benyu Zhang Breakdown of academic impact, for papers by Huaxiang Zhang Breakdown of academic impact, for papers by Lifang He
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