Long Sha
Impact in
- Cognitive Neuroscience top 10%
- Face Recognition and Perception
- Visual perception and processing mechanisms
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Functional Brain Connectivity Studies
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- Multisensory perception and integration
Papers in
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- Face Recognition and Perception 3
- Visual perception and processing mechanisms 3
- Neural and Behavioral Psychology Studies 2
- Memory and Neural Mechanisms 1
- Neural dynamics and brain function 1
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- Face and Expression Recognition 1
- Co-authors
- Hervé Abdi (2 shared papers)Nikolaas N. Oosterhof (2 shared papers)Roozbeh Kiani (3 shared papers)Andrew C. Connolly (2 shared papers)James V. Haxby (2 shared papers)Yaroslav O. Halchenko (2 shared papers)J. Swaroop Guntupalli (2 shared papers)Gouki Okazawa (2 shared papers)
- Journals
- Journal of Neuroscience (2 papers)Journal of Cognitive Neuroscience (1 paper)Nature Communications (1 paper)Journal of Vision (1 paper)PubMed (1 paper)
- Partner nations
- United StatesItalyCanada
In The Last Decade
Long Sha
6 papers receiving 218 citations
Peers
Comparison fields: 5 of 36
- Cognitive Neuroscience 199
- Experimental and Cognitive Psychology 44
- General Decision Sciences 6
- Sensory Systems 14
- Social Psychology 39
Countries citing papers authored by Long Sha
This map shows the geographic impact of Long Sha'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 Long Sha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Sha more than expected).
Fields of papers citing papers by Long Sha
This network shows the impact of papers produced by Long Sha. 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 Long Sha. The network helps show where Long Sha may publish in the future.
Co-authors
The 19 scholars most cited alongside Long Sha, 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 | 2014 | 111 | |
| 2 | 2018 | 49 | |
| 3 | 2016 | 36 | |
| 4 | 2018 | 12 | |
| 5 | 2021 | 11 | |
| 6 | 2017 | 2 |
About Long Sha
Long Sha is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Computational Mathematics, Radiology, Nuclear Medicine and Imaging and Developmental and Educational Psychology, having authored 6 papers that have together received 221 indexed citations. Recurring topics across this work include Face Recognition and Perception (3 papers), Visual perception and processing mechanisms (3 papers), Neural and Behavioral Psychology Studies (2 papers), Face and Expression Recognition (1 paper), Tensor decomposition and applications (1 paper), Memory and Neural Mechanisms (1 paper), Advanced Neuroimaging Techniques and Applications (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Cognitive Neuroscience (199 citations), Experimental and Cognitive Psychology (44 citations), General Decision Sciences (6 citations), Sensory Systems (14 citations) and Social Psychology (39 citations). Long Sha has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include Hervé Abdi, Nikolaas N. Oosterhof, Roozbeh Kiani, Andrew C. Connolly, James V. Haxby, Yaroslav O. Halchenko, J. Swaroop Guntupalli, Gouki Okazawa, Braden A. Purcell and Samuel A. Nastase. Their work appears in journals such as Journal of Neuroscience, Journal of Cognitive Neuroscience, Nature Communications, Journal of Vision and PubMed.
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.