Keyan Ding

1.5k total citations · 1 hit paper
23 papers, 906 citations indexed

About

Keyan Ding is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Keyan Ding has authored 23 papers receiving a total of 906 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 4 papers in Molecular Biology. Recurrent topics in Keyan Ding's work include Medical Image Segmentation Techniques (6 papers), Image and Object Detection Techniques (5 papers) and Image and Video Quality Assessment (5 papers). Keyan Ding is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Image and Object Detection Techniques (5 papers) and Image and Video Quality Assessment (5 papers). Keyan Ding collaborates with scholars based in China, Hong Kong and United States. Keyan Ding's co-authors include Shiqi Wang, Eero P. Simoncelli, Kede Ma, Linfang Xiao, Guirong Weng, Ronggang Wang, Xiuqin Rao, Huajun Chen, Qiang Zhang and Qiang Zhang and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Vision.

In The Last Decade

Keyan Ding

19 papers receiving 874 citations

Hit Papers

Image Quality Assessment: Unifying Structure and Texture ... 2020 2026 2022 2024 2020 100 200 300 400 500
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. Image Quality Assessment: Unifying Structure and Texture Similarity
    2020 523 citations Keyan Ding, Kede Ma et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Keyan Ding China 7 655 261 78 45 43 23 906
Xiangyu Chen China 14 930 1.4× 448 1.7× 132 1.7× 63 1.4× 34 0.8× 53 1.2k
Chandan Singh India 23 1.3k 2.0× 435 1.7× 155 2.0× 40 0.9× 44 1.0× 87 1.5k
Dongbo Min South Korea 23 1.5k 2.2× 534 2.0× 128 1.6× 47 1.0× 21 0.5× 67 1.7k
Saeid Belkasim United States 14 671 1.0× 113 0.4× 120 1.5× 24 0.5× 31 0.7× 62 876
Xiaogang Xu China 13 606 0.9× 163 0.6× 80 1.0× 35 0.8× 10 0.2× 32 768
Zhenhong Jia China 18 549 0.8× 576 2.2× 67 0.9× 170 3.8× 22 0.5× 128 1.0k
Liangyu Chen China 12 522 0.8× 209 0.8× 192 2.5× 30 0.7× 24 0.6× 61 818
Bai Xue China 12 344 0.5× 302 1.2× 89 1.1× 73 1.6× 14 0.3× 42 679

Countries citing papers authored by Keyan Ding

Since Specialization
Citations

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

Fields of papers citing papers by Keyan Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keyan Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Keyan Ding. A scholar is included among the top collaborators of Keyan 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 Keyan Ding. Keyan 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.
Zhang, Yuhang, Peilin Chen, Keyan Ding, et al.. (2025). MPSol: A Multimodal Prompt Learning Framework for Protein Solubility Prediction. IEEE Journal of Biomedical and Health Informatics. 29(12). 8807–8814.
2.
Ding, Keyan, et al.. (2025). SciToolAgent: a knowledge-graph-driven scientific agent for multitool integration. Nature Computational Science. 5(10). 962–972. 4 indexed citations
3.
Zhang, Qiang, Yuhao Wang, Zhongji Pu, et al.. (2025). Integrating protein language models and automatic biofoundry for enhanced protein evolution. Nature Communications. 16(1). 1553–1553. 15 indexed citations
4.
Ding, Keyan, Kede Ma, Zhihua Wang, et al.. (2025). Sample-Efficient Human Evaluation of Large Language Models via Maximum Discrepancy Competition. CityU Scholars. 10913–10947.
5.
Ding, Keyan, et al.. (2024). CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement. International Journal of Computer Vision. 132(12). 5983–6003. 6 indexed citations
6.
Zhu, Hanwei, et al.. (2024). Deep Shape-Texture Statistics for Completely Blind Image Quality Evaluation. ACM Transactions on Multimedia Computing Communications and Applications. 20(12). 1–21. 1 indexed citations
7.
Ni, Zhangkai, et al.. (2024). Opinion-Unaware Blind Image Quality Assessment Using Multi-Scale Deep Feature Statistics. IEEE Transactions on Multimedia. 26. 10211–10224. 3 indexed citations
8.
9.
Han, Yuqiang, Chang‐Yu Hsieh, Keyan Ding, et al.. (2024). Retrosynthesis prediction with an iterative string editing model. Nature Communications. 15(1). 6404–6404. 17 indexed citations
10.
Wang, Zeyuan, Qiang Zhang, Keyan Ding, et al.. (2024). InstructProtein: Aligning Human and Protein Language via Knowledge Instruction. 1114–1136. 6 indexed citations
11.
Ding, Keyan, et al.. (2023). Adaptive Structure and Texture Similarity Metric for Image Quality Assessment and Optimization. IEEE Transactions on Multimedia. 26. 5398–5409. 3 indexed citations
12.
Zhuang, Xiang, et al.. (2023). Graph Sampling-based Meta-Learning for Molecular Property Prediction. 4729–4737. 5 indexed citations
13.
Ding, Keyan, Kede Ma, Shiqi Wang, & Eero P. Simoncelli. (2020). Image Quality Assessment: Unifying Structure and Texture Similarity. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(5). 1–1. 523 indexed citations breakdown →
14.
Ding, Keyan, Ronggang Wang, & Shiqi Wang. (2019). Social Media Popularity Prediction. 2682–2686. 37 indexed citations
15.
Xiao, Linfang, et al.. (2018). Active contours driven by grayscale morphology fitting energy for fast image segmentation. Journal of Electronic Imaging. 27(6). 1–1. 1 indexed citations
16.
Xiao, Linfang, et al.. (2018). Behavior-induced health condition monitoring of caged chickens using binocular vision. Computers and Electronics in Agriculture. 156. 254–262. 37 indexed citations
17.
Ding, Keyan, Linfang Xiao, & Guirong Weng. (2018). Active contours driven by local pre-fitting energy for fast image segmentation. Pattern Recognition Letters. 104. 29–36. 100 indexed citations
18.
19.
Ding, Keyan, Linfang Xiao, & Guirong Weng. (2016). Active contours driven by region-scalable fitting and optimized Laplacian of Gaussian energy for image segmentation. Signal Processing. 134. 224–233. 138 indexed citations
20.
Ding, Keyan, et al.. (1990). Corn quality evaluation with computer vision.. Paper - American Society of Agricultural Engineers. 4 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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