Jun-Wen Tan
Impact in
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- Emotion and Mood Recognition
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
Papers in
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- Emotion and Mood Recognition 7
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- EEG and Brain-Computer Interfaces 3
- Face Recognition and Perception 3
- Neural and Behavioral Psychology Studies 2
- Co-authors
- Harald C. Traue (7 shared papers)Steffen Walter (2 shared papers)Sascha Gruss (3 shared papers)Stephen Crawcour (2 shared papers)Adriano de Oliveira Andrade (3 shared papers)Ayoub Al-Hamadi (1 shared paper)Philipp Werner (1 shared paper)Holger Hoffmann (3 shared papers)
In The Last Decade
Jun-Wen Tan
12 papers receiving 326 citations
Peers
Comparison fields: 5 of 72
- Experimental and Cognitive Psychology 161
- Cognitive Neuroscience 156
- Human-Computer Interaction 21
- Anesthesiology and Pain Medicine 17
- Cardiology and Cardiovascular Medicine 62
Countries citing papers authored by Jun-Wen Tan
This map shows the geographic impact of Jun-Wen Tan'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 Jun-Wen Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun-Wen Tan more than expected).
Fields of papers citing papers by Jun-Wen Tan
This network shows the impact of papers produced by Jun-Wen Tan. 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 Jun-Wen Tan. The network helps show where Jun-Wen Tan may publish in the future.
Co-authors
The 21 scholars most cited alongside Jun-Wen Tan, 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 | 2013 | 180 | |
| 2 | 2011 | 55 | |
| 3 | 2016 | 32 | |
| 4 | 2013 | 27 | |
| 5 | 2016 | 22 | |
| 6 | 2011 | 10 | |
| 7 | 2019 | 5 | |
| 8 | 2021 | 4 | |
| 9 | 2025 | 2 | |
| 10 | 2025 | 1 | |
| 11 | 2022 | 1 | |
| 12 | 2012 | 1 | |
| 13 | 2024 | 0 |
About Jun-Wen Tan
Jun-Wen Tan is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience, Social Psychology, Computer Vision and Pattern Recognition and Clinical Psychology, having authored 13 papers that have together received 340 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (7 papers), EEG and Brain-Computer Interfaces (3 papers), Face Recognition and Perception (3 papers), Advanced Measurement and Metrology Techniques (2 papers), Neural and Behavioral Psychology Studies (2 papers), Optical measurement and interference techniques (2 papers), Child and Adolescent Psychosocial and Emotional Development (2 papers) and Gaze Tracking and Assistive Technology (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (161 citations), Cognitive Neuroscience (156 citations), Human-Computer Interaction (21 citations), Anesthesiology and Pain Medicine (17 citations) and Cardiology and Cardiovascular Medicine (62 citations). Jun-Wen Tan has collaborated with scholars based in China, Germany and Brazil. Frequent co-authors include Harald C. Traue, Steffen Walter, Sascha Gruss, Stephen Crawcour, Adriano de Oliveira Andrade, Ayoub Al-Hamadi, Philipp Werner, Holger Hoffmann, Steffen Walter and Andreas Scheck. Their work appears in journals such as PLoS ONE, Journal of Ambient Intelligence and Humanized Computing, IEEE Transactions on Instrumentation and Measurement, Personality and Individual Differences and Multimedia Tools and Applications.
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.