Jay Hegdé
- Cognitive Neuroscience top 2%
- Visual perception and processing mechanisms 23
- Neural dynamics and brain function 14
- Face Recognition and Perception 8
- Neural and Behavioral Psychology Studies 6
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- Neurobiology and Insect Physiology Research 8
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- Visual Attention and Saliency Detection 5
- Sensory Systems top 10%
- Biophysics top 10%
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- AI in cancer detection 5
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- Color Science and Applications 3
- Co-authors
- David C. Van EssenDaniel J. FellemanDaniel KerstenEvgeniy BartGeoffrey M. BoyntonEdwin C. StephensonXin ChenScott O. Murray
- Cited by
- Cognitive NeuroscienceCellular and Molecular NeuroscienceComputer Vision and Pattern Recognition
- Journals
- Journal of Neurophysiology (4 papers)Journal of Vision (4 papers)Journal of Neuroscience (3 papers)
- Partner nations
- United StatesBulgariaSouth Korea
In The Last Decade
Jay Hegdé
37 papers receiving 901 citations
Peers
Comparison fields: 5 of 76
- Cognitive Neuroscience 790
- Cellular and Molecular Neuroscience 160
- Computer Vision and Pattern Recognition 174
- Sensory Systems 33
- Biophysics 33
Countries citing papers authored by Jay Hegdé
This map shows the geographic impact of Jay Hegdé'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 Jay Hegdé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Hegdé more than expected).
Fields of papers citing papers by Jay Hegdé
This network shows the impact of papers produced by Jay Hegdé. 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 Jay Hegdé. The network helps show where Jay Hegdé may publish in the future.
Co-authorship network
The 14 scholars most cited alongside Jay Hegdé, 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 | 2022 | 1 | |
| 2 | 2022 | 1 | |
| 3 | 2022 | 0 | |
| 4 | 2021 | 3 | |
| 5 | 2018 | 4 | |
| 6 | 2018 | 2 | |
| 7 | 2012 | 8 | |
| 8 | 2012 | 6 | |
| 9 | 2012 | 2 | |
| 10 | 2012 | 2 | |
| 11 | 2009 | 9 | |
| 12 | 2008 | 34 | |
| 13 | 2006 | 129 | |
| 14 | 2006 | 19 | |
| 15 | 2005 | 36 | |
| 16 | 2004 | 21 | |
| 17 | 2004 | 12 | |
| 18 | 2004 | 35 | |
| 19 | 2003 | 64 | |
| 20 | 1999 | 7 |
About Jay Hegdé
Jay Hegdé is a scholar working on Cognitive Neuroscience, General Decision Sciences and Health Informatics, having authored 41 papers that have together received 931 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (23 papers), Neural dynamics and brain function (14 papers), Face Recognition and Perception (8 papers), Neurobiology and Insect Physiology Research (8 papers), Neural and Behavioral Psychology Studies (6 papers), Visual Attention and Saliency Detection (5 papers), AI in cancer detection (5 papers) and Color Science and Applications (3 papers). The work is most often cited by research in Cognitive Neuroscience (790 citations), Cellular and Molecular Neuroscience (160 citations) and Computer Vision and Pattern Recognition (174 citations). Jay Hegdé has collaborated with scholars based in United States, Bulgaria and South Korea. Frequent co-authors include David C. Van Essen, Daniel J. Felleman, Daniel Kersten, Evgeniy Bart, Geoffrey M. Boynton, Edwin C. Stephenson, Xin Chen, Scott O. Murray, Fang Fang and Thomas D. Albright. Their work appears in journals such as Journal of Neurophysiology, Journal of Vision, Journal of Neuroscience, Current Biology and Frontiers in Neuroscience.
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.