Chris Ding
Impact in
- Computational Mathematics top 5%
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- Face and Expression Recognition
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
Papers in
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- Advanced Clustering Algorithms Research 3
- Advanced Graph Neural Networks 2
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- Face and Expression Recognition 3
- Graph Theory and Algorithms 2
- Co-authors
- Michael I. Jordan (2 shared papers)Jie Zhou (1 shared paper)Quanquan Gu (1 shared paper)Tao Li (1 shared paper)Tao Li (2 shared papers)Zhongyuan Zhang (2 shared papers)Xiang‐Sun Zhang (1 shared paper)Bin Luo (2 shared papers)
- Journals
- Language Speech and Hearing Services in Schools (1 paper)Scientific Reports (1 paper)Journal of Computational Biology (1 paper)Knowledge and Information Systems (1 paper)Pattern Recognition Letters (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Chris Ding
12 papers receiving 634 citations
Peers
Comparison fields: 5 of 99
- Computational Mathematics 31
- Computer Vision and Pattern Recognition 283
- Artificial Intelligence 353
- Signal Processing 100
- Statistical and Nonlinear Physics 113
Countries citing papers authored by Chris Ding
This map shows the geographic impact of Chris 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 Chris Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Ding more than expected).
Fields of papers citing papers by Chris Ding
This network shows the impact of papers produced by Chris 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 Chris Ding. The network helps show where Chris Ding may publish in the future.
Co-authors
The 23 scholars most cited alongside Chris Ding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 178 | |
| 2 | 2007 | 155 | |
| 3 | 2008 | 102 | |
| 4 | 2007 | 89 | |
| 5 | 2001 | 48 | |
| 6 | 2014 | 43 | |
| 7 | 2012 | 23 | |
| 8 | 2017 | 11 | |
| 9 | 2004 | 8 | |
| 10 | 2024 | 6 | |
| 11 | 2015 | 6 | |
| 12 | 2007 | 2 | |
| 13 | Spectral Clustering, Ordering and Ranking: Statistical Learning with Matrix Factorizations | 2014 | 0 |
About Chris Ding
Chris Ding is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Molecular Biology and Information Systems, having authored 13 papers that have together received 671 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (4 papers), Face and Expression Recognition (3 papers), Advanced Clustering Algorithms Research (3 papers), Data Management and Algorithms (2 papers), Graph Theory and Algorithms (2 papers), Advanced Graph Neural Networks (2 papers), Machine Learning in Bioinformatics (1 paper) and AI and HR Technologies (1 paper). The work is most often cited by research in Computational Mathematics (31 citations), Computer Vision and Pattern Recognition (283 citations), Artificial Intelligence (353 citations), Signal Processing (100 citations) and Statistical and Nonlinear Physics (113 citations). Chris Ding has collaborated with scholars based in United States and China. Frequent co-authors include Michael I. Jordan, Jie Zhou, Quanquan Gu, Tao Li, Tao Li, Zhongyuan Zhang, Xiang‐Sun Zhang, Tao Li, Bin Luo and Xiaofeng He. Their work appears in journals such as Language Speech and Hearing Services in Schools, Scientific Reports, Journal of Computational Biology, Knowledge and Information Systems and Pattern Recognition Letters.
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.