Chris Ding

1.3k citations
14 papers · 750 · h-index 9

Impact in

Papers in

Chris Ding

13 papers receiving 711 citations

Peers

Chris Ding
Comparison fields: 5 of 99
  • Computational Mathematics 37
  • Computer Vision and Pattern Recognition 327
  • Artificial Intelligence 392
  • Signal Processing 111
  • Statistical and Nonlinear Physics 118
Replace Hong Peng with:
Hong Peng China
Yasuhiro Fujiwara Japan
Hongchang Gao United States
Feng Tian China
Dongxia Chang China
Yogish Sabharwal India
Bilian Chen China
Tarek Abudawood United States
Wangdong Yang China
Choon Hui Teo United States
Chris Ding relative to Hong Peng China Hong Peng's profile →
Citations per field
00.5×1.5×2.5×
Hong Peng · 1×
Citations per year

Countries citing papers authored by Chris Ding

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Chris Ding Line = papers co-authored together Chris Ding links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2010195
2 2007170
3 2008114
4 2007103
5 200155
6 201446
7 201227
8 201711
9 20049
10 20247
11 20157
12 20074
13 20162
14
Spectral Clustering, Ordering and Ranking: Statistical Learning with Matrix Factorizations
20140

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 14 papers that have together received 750 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (4 papers), Face and Expression Recognition (4 papers), Advanced Clustering Algorithms Research (3 papers), Graph Theory and Algorithms (2 papers), Data Management and Algorithms (2 papers), Advanced Graph Neural Networks (2 papers), VLSI and FPGA Design Techniques (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Computational Mathematics (37 citations), Computer Vision and Pattern Recognition (327 citations), Artificial Intelligence (392 citations), Signal Processing (111 citations) and Statistical and Nonlinear Physics (118 citations). Chris Ding has collaborated with scholars based in United States and China. Frequent co-authors include Michael I. Jordan, Quanquan Gu, Jie Zhou, Tao Li, Tao Li, Zhongyuan Zhang, Xiang‐Sun Zhang, Tao Li, Xiaofeng He and Bin Luo. Their work appears in journals such as Language Speech and Hearing Services in Schools, Pattern Recognition Letters, Scientific Reports, Journal of Computational Biology and Knowledge and Information Systems.

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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