David Cox
- Cognitive Neuroscience top 0.5%
- Neural dynamics and brain function 20
- Visual perception and processing mechanisms 14
- Face Recognition and Perception 11
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- Advanced Image and Video Retrieval Techniques 12
- Face and Expression Recognition 8
- Face recognition and analysis 6
- Geometry and Topology top 1%
- Computational Mathematics top 5%
- Sensory Systems top 1%
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- Cell Image Analysis Techniques 7
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- Neural Networks and Applications 6
David Cox
87 papers receiving 9.0k citations
Hit Papers
Peers
Comparison fields: 5 of 207
- Cognitive Neuroscience 2.6k
- Computer Vision and Pattern Recognition 2.6k
- Geometry and Topology 641
- Computational Mathematics 42
- Sensory Systems 281
Countries citing papers authored by David Cox
This map shows the geographic impact of David Cox'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 David Cox with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Cox more than expected).
Fields of papers citing papers by David Cox
This network shows the impact of papers produced by David Cox. 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 David Cox. The network helps show where David Cox may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Cox, 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 | 2025 | 0 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 9 | |
| 4 | 2020 | 36 | |
| 5 | 2019 | 23 | |
| 6 | 2018 | 5 | |
| 7 | 2014 | 35 | |
| 8 | RNA-guided editing of bacterial genomes using CRISPR-Cas systems | 2013 | 1 |
| 9 | Affordable Options for Ground-Based, Large-Aperture Optical Space Surveillance Systems | 2013 | 1 |
| 10 | Towards condition-invariant, top-down visual place recognition | 2013 | 5 |
| 11 | Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architecturesbreakdown → | 2013 | 935 |
| 12 | 2009 | 162 | |
| 13 | 2009 | 150 | |
| 14 | 2008 | 23 | |
| 15 | Untangling invariant object recognitionbreakdown → | 2007 | 572 |
| 16 | 2007 | 37 | |
| 17 | 2005 | 116 | |
| 18 | 2005 | 2 | |
| 19 | Functional magnetic resonance imaging (fMRI) “brain reading”: detecting and classifying distributed patterns of fMRI activity in human visual cortexbreakdown → | 2003 | 757 |
| 20 | Mirror Symmetry and Algebraic Geometrybreakdown → | 1999 | 394 |
About David Cox
David Cox is a scholar working on Computational Mathematics, Biophysics and Computer Vision and Pattern Recognition, having authored 91 papers that have together received 9.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (20 papers), Visual perception and processing mechanisms (14 papers), Advanced Image and Video Retrieval Techniques (12 papers), Face Recognition and Perception (11 papers), Face and Expression Recognition (8 papers), Cell Image Analysis Techniques (7 papers), Face recognition and analysis (6 papers) and Neural Networks and Applications (6 papers). The work is most often cited by research in Cognitive Neuroscience (2.6k citations), Computer Vision and Pattern Recognition (2.6k citations) and Geometry and Topology (641 citations). David Cox has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include James J. DiCarlo, James Bergstra, Robert L. Savoy, Nicolas Pinto, Donal O’Shea, John B. Little, Daniel Yamins, Dan Yamins, Sheldon Katz and Lawrence Que. Their work appears in journals such as Journal of Neuroscience, Scientific Reports, Journal of Visualized Experiments, Journal of Neurophysiology and Proceedings of the National Academy of Sciences.
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.