Suh-Yeon Dong
- Experimental and Cognitive Psychology top 5%
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 10%
- Cardiology and Cardiovascular Medicine
- Biomedical Engineering
- Co-authors
- Bo-Kyeong KimSoo-Young LeeJihyeon RohInchan YounDa-Mi JeongByung‐Gyu KimHee Su ParkMiran Lee
- Topics
- EEG and Brain-Computer Interfaces (10 papers)Non-Invasive Vital Sign Monitoring (6 papers)Heart Rate Variability and Autonomic Control (6 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- South KoreaUnited StatesSingapore
In The Last Decade
Suh-Yeon Dong
28 papers receiving 628 citations
Peers
Comparison fields: 5 of 93
- Experimental and Cognitive Psychology 279
- Computer Vision and Pattern Recognition 276
- Cognitive Neuroscience 167
- Cardiology and Cardiovascular Medicine 124
- Biomedical Engineering 109
Countries citing papers authored by Suh-Yeon Dong
This map shows the geographic impact of Suh-Yeon Dong'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 Suh-Yeon Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suh-Yeon Dong more than expected).
Fields of papers citing papers by Suh-Yeon Dong
This network shows the impact of papers produced by Suh-Yeon Dong. 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 Suh-Yeon Dong. The network helps show where Suh-Yeon Dong may publish in the future.
Co-authorship network of co-authors of Suh-Yeon Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Suh-Yeon Dong. A scholar is included among the top collaborators of Suh-Yeon Dong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Suh-Yeon Dong. Suh-Yeon Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 31 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 9 | |
| 10 | 0 | |
| 11 | 23 | |
| 12 | 80 | |
| 13 | 40 | |
| 14 | 16 | |
| 15 | 27 | |
| 16 | 25 | |
| 17 | 33 | |
| 18 | 73 | |
| 19 | 4 | |
| 20 | Understanding Human Implicit Intention While Reading Self-relevant Sentences: An fMRI Study | 2 |
About Suh-Yeon Dong
Suh-Yeon Dong is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Behavioral Neuroscience, having authored 34 papers that have together received 663 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (10 papers), Non-Invasive Vital Sign Monitoring (6 papers) and Heart Rate Variability and Autonomic Control (6 papers). The work is most often cited by research in Experimental and Cognitive Psychology (279 citations), Computer Vision and Pattern Recognition (276 citations) and Human-Computer Interaction (54 citations). Suh-Yeon Dong has collaborated with scholars based in South Korea, United States and Singapore. Frequent co-authors include Bo-Kyeong Kim, Soo-Young Lee, Jihyeon Roh, Inchan Youn, Da-Mi Jeong, Byung‐Gyu Kim, Hee Su Park, Miran Lee, Soyeon Park and Soo Young Lee. Their work appears in journals such as Scientific Reports, IEEE Access and Sensors.
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.