Ling Ding

699 total citations · 1 hit paper
43 papers, 371 citations indexed

About

Ling Ding is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Ling Ding has authored 43 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 10 papers in Statistical and Nonlinear Physics. Recurrent topics in Ling Ding's work include Advanced Clustering Algorithms Research (11 papers), Complex Network Analysis Techniques (10 papers) and Face and Expression Recognition (6 papers). Ling Ding is often cited by papers focused on Advanced Clustering Algorithms Research (11 papers), Complex Network Analysis Techniques (10 papers) and Face and Expression Recognition (6 papers). Ling Ding collaborates with scholars based in China, Singapore and Taiwan. Ling Ding's co-authors include Shifei Ding, Di Jin, Xiao Xu, Lili Guo, Jian Zhang, Yanru Wang, Lijuan Wang, Lili Guo, Laura Astolfi and A. Basilisco and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and Pattern Recognition.

In The Last Decade

Ling Ding

39 papers receiving 367 citations

Hit Papers

Survey of spectral clustering based on graph theory 2024 2026 2025 2024 10 20 30 40
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. Survey of spectral clustering based on graph theory
    2024 49 citations Ling Ding, Di Jin et al. Pattern Recognition profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ling Ding China 10 177 94 54 53 30 43 371
Juan Yang China 12 215 1.2× 190 2.0× 12 0.2× 26 0.5× 20 0.7× 40 445
Ce Guo United Kingdom 11 130 0.7× 90 1.0× 18 0.3× 14 0.3× 21 0.7× 53 332
Mohammed Nasser Al-Andoli Malaysia 12 122 0.7× 33 0.4× 14 0.3× 63 1.2× 43 1.4× 32 325
Fardad Farokhi Iran 11 122 0.7× 60 0.6× 29 0.5× 5 0.1× 62 2.1× 50 317
Shalini Stalin India 9 88 0.5× 112 1.2× 26 0.5× 16 0.3× 28 0.9× 16 340
Min Dong China 9 87 0.5× 132 1.4× 8 0.1× 16 0.3× 14 0.5× 40 305
Hongrong Cheng China 8 137 0.8× 104 1.1× 12 0.2× 9 0.2× 25 0.8× 22 318
Doudou Lin China 5 192 1.1× 88 0.9× 7 0.1× 40 0.8× 9 0.3× 7 295
José Ricardo Cárdenas-Valdez Mexico 9 81 0.5× 292 3.1× 11 0.2× 149 2.8× 11 0.4× 28 499

Countries citing papers authored by Ling Ding

Since Specialization
Citations

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

Fields of papers citing papers by Ling Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling Ding. 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 Ling Ding. The network helps show where Ling Ding may publish in the future.

Co-authorship network of co-authors of Ling Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Ding. A scholar is included among the top collaborators of Ling Ding 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 Ling Ding. Ling Ding 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.
Ding, Shifei, et al.. (2025). Fast Density Peaks Clustering Algorithm Based on Approximate k-Nearest Neighbors. IEEE Transactions on Knowledge and Data Engineering. 37(10). 5878–5889. 1 indexed citations
2.
Ding, Ling, et al.. (2024). Survey of spectral clustering based on graph theory. Pattern Recognition. 151. 110366–110366. 49 indexed citations breakdown →
3.
Ding, Shifei, et al.. (2024). Towards Faster Deep Graph Clustering via Efficient Graph Auto-Encoder. ACM Transactions on Knowledge Discovery from Data. 18(8). 1–23.
4.
Du, Wei, et al.. (2024). Expressive Multi-Agent Communication via Identity-Aware Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(16). 17354–17361. 1 indexed citations
5.
Ding, Shifei, et al.. (2024). Graph-Based Semi-Supervised Deep Image Clustering With Adaptive Adjacency Matrix. IEEE Transactions on Neural Networks and Learning Systems. 35(12). 18828–18837. 4 indexed citations
6.
Ding, Shifei, Wei Du, Ling Ding, Lili Guo, & Jian Zhang. (2024). Learning Efficient and Robust Multi-Agent Communication via Graph Information Bottleneck. Proceedings of the AAAI Conference on Artificial Intelligence. 38(16). 17346–17353. 4 indexed citations
7.
Ding, Shifei, et al.. (2024). Vertical Federated Density Peaks Clustering Under Nonlinear Mapping. IEEE Transactions on Knowledge and Data Engineering. 37(2). 1004–1017. 3 indexed citations
8.
Ding, Ling, Qiong Wang, Yin Poo, & Xinggan Zhang. (2024). Nonlocal Gaussian scale mixture modeling for hyperspectral image denoising. Computer Vision and Image Understanding. 251. 104270–104270.
9.
Ding, Shifei, et al.. (2023). A novel image denoising algorithm combining attention mechanism and residual UNet network. Knowledge and Information Systems. 66(1). 581–611. 5 indexed citations
10.
Ding, Ling, Wei Du, Jian Zhang, et al.. (2023). Better value estimation in Q-learning-based multi-agent reinforcement learning. Soft Computing. 28(6). 5625–5638. 3 indexed citations
11.
Chen, Xi, Ling Ding, Xiong Xiong, et al.. (2023). The MKK3–MPK7 cascade phosphorylates ERF4 and promotes its rapid degradation to release seed dormancy in Arabidopsis. Molecular Plant. 16(11). 1743–1758. 13 indexed citations
12.
Ding, Ling, et al.. (2023). Botnet DGA Domain Name Classification Using Transformer Network with Hybrid Embedding. Big Data Research. 33. 100395–100395. 7 indexed citations
13.
Ding, Shifei, et al.. (2023). Graph clustering network with structure embedding enhanced. Pattern Recognition. 144. 109833–109833. 22 indexed citations
14.
Ding, Shifei, et al.. (2023). Fast density peaks clustering algorithm based on improved mutual K-nearest-neighbor and sub-cluster merging. Information Sciences. 647. 119470–119470. 26 indexed citations
15.
Ding, Ling, et al.. (2023). Identifying Counterexamples Without Variability in Software Product Line Model Checking. Computers, materials & continua/Computers, materials & continua (Print). 75(2). 2655–2670. 1 indexed citations
16.
Ding, Shifei, et al.. (2023). A novel clustering algorithm based on multi-layer features and graph attention networks. Soft Computing. 27(9). 5553–5566. 3 indexed citations
17.
Zhang, Jian, Qinghai Xu, Lili Guo, Ling Ding, & Shifei Ding. (2023). A novel capsule network based on deep routing and residual learning. Soft Computing. 27(12). 7895–7906. 3 indexed citations
18.
Yang, Fan, Ling Ding, Dan Zhao, et al.. (2022). Identification and Functional Analysis of Tomato MicroRNAs in the Biocontrol Bacterium Pseudomonas putida Induced Plant Resistance to Meloidogyne incognita. Phytopathology. 112(11). 2372–2382. 12 indexed citations
19.
Ding, Ling. (2011). Review of Energy Storage System in Electric Power System. 6 indexed citations
20.
Song, Wei, et al.. (2005). A New Method for Representation of the Cardinal Direction Relations Using Rectangle Algebra. Computer Engineering and Applications Journal. 41(31). 79–81. 3 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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