Yunjun Nam
Impact in
- Human-Computer Interaction top 2%
- Gaze Tracking and Assistive Technology
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
Papers in
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- EEG and Brain-Computer Interfaces 12
- Neural dynamics and brain function 5
- Face Recognition and Perception 2
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- Neuroscience and Neural Engineering 7
- Co-authors
- Hyohyeong Kang (2 shared papers)Seungjin Choi (5 shared papers)Bonkon Koo (7 shared papers)Seungjin Choi (6 shared papers)Andrzej Cichocki (5 shared papers)Chin Su Koh (2 shared papers)Hyung‐Cheul Shin (1 shared paper)Qibin Zhao (1 shared paper)
- Journals
- IEEE Transactions on Biomedical Engineering (2 papers)Scientific Reports (1 paper)Experimental Neurobiology (1 paper)PLoS ONE (1 paper)IEEE Signal Processing Letters (1 paper)
- Partner nations
- South KoreaJapanIsrael
In The Last Decade
Yunjun Nam
14 papers receiving 521 citations
Peers
Comparison fields: 5 of 48
- Human-Computer Interaction 183
- Cognitive Neuroscience 469
- Signal Processing 104
- Cellular and Molecular Neuroscience 163
- Biomedical Engineering 125
Countries citing papers authored by Yunjun Nam
This map shows the geographic impact of Yunjun Nam'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 Yunjun Nam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yunjun Nam more than expected).
Fields of papers citing papers by Yunjun Nam
This network shows the impact of papers produced by Yunjun Nam. 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 Yunjun Nam. The network helps show where Yunjun Nam may publish in the future.
Co-authors
The 18 scholars most cited alongside Yunjun Nam, 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 | 2009 | 205 | |
| 2 | 2014 | 100 | |
| 3 | 2013 | 86 | |
| 4 | 2015 | 45 | |
| 5 | 2011 | 31 | |
| 6 | 2014 | 17 | |
| 7 | 2013 | 13 | |
| 8 | 2016 | 12 | |
| 9 | 2013 | 8 | |
| 10 | 2014 | 6 | |
| 11 | 2021 | 4 | |
| 12 | 2018 | 4 | |
| 13 | 2014 | 2 | |
| 14 | 2011 | 1 | |
| 15 | 2012 | 0 |
About Yunjun Nam
Yunjun Nam is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Human-Computer Interaction, Signal Processing and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 534 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (12 papers), Neuroscience and Neural Engineering (7 papers), Gaze Tracking and Assistive Technology (6 papers), Neural dynamics and brain function (5 papers), Blind Source Separation Techniques (3 papers), Face Recognition and Perception (2 papers), Visual Attention and Saliency Detection (2 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Human-Computer Interaction (183 citations), Cognitive Neuroscience (469 citations), Signal Processing (104 citations), Cellular and Molecular Neuroscience (163 citations) and Biomedical Engineering (125 citations). Yunjun Nam has collaborated with scholars based in South Korea, Japan and Israel. Frequent co-authors include Hyohyeong Kang, Seungjin Choi, Bonkon Koo, Seungjin Choi, Andrzej Cichocki, Chin Su Koh, Hyung‐Cheul Shin, Qibin Zhao, Seungjin Choi and Fumitoshi Matsuno. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Scientific Reports, Experimental Neurobiology, PLoS ONE and IEEE Signal Processing Letters.
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.