Bum Chul Kwon
Impact in
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- Data Visualization and Analytics
- Video Analysis and Summarization
- Health Informatics top 2%
Papers in
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- Data Visualization and Analytics 30
- Video Analysis and Summarization 7
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- Explainable Artificial Intelligence (XAI) 6
- Machine Learning in Healthcare 6
- Data Analysis with R 4
- Co-authors
- Daniel A. Keim (9 shared papers)Sung-Hee Kim (6 shared papers)Dominik Sacha (4 shared papers)Geoffrey Ellis (2 shared papers)Sukwon Lee (6 shared papers)Ji Soo Yi (15 shared papers)Andreas Stoffel (4 shared papers)Jaegul Choo (6 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (18 papers)International Journal of Human-Computer Interaction (2 papers)Scientific Reports (1 paper)JMIR mhealth and uhealth (1 paper)Diabetes (1 paper)
- Partner nations
- United StatesGermanySouth Korea
In The Last Decade
Bum Chul Kwon
59 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 146
- Computer Vision and Pattern Recognition 937
- Health Informatics 54
- Human-Computer Interaction 118
- Artificial Intelligence 633
- Health Information Management 71
Countries citing papers authored by Bum Chul Kwon
This map shows the geographic impact of Bum Chul Kwon'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 Bum Chul Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bum Chul Kwon more than expected).
Fields of papers citing papers by Bum Chul Kwon
This network shows the impact of papers produced by Bum Chul Kwon. 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 Bum Chul Kwon. The network helps show where Bum Chul Kwon may publish in the future.
Co-authors
The 25 scholars most cited alongside Bum Chul Kwon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 246 | |
| 2 | 2018 | 196 | |
| 3 | 2015 | 191 | |
| 4 | 2016 | 168 | |
| 5 | 2017 | 91 | |
| 6 | 2016 | 68 | |
| 7 | 2013 | 52 | |
| 8 | 2016 | 46 | |
| 9 | 2015 | 43 | |
| 10 | 2020 | 42 | |
| 11 | 2016 | 41 | |
| 12 | 2020 | 40 | |
| 13 | 2014 | 38 | |
| 14 | 2021 | 36 | |
| 15 | 2015 | 33 | |
| 16 | 2011 | 30 | |
| 17 | 2022 | 27 | |
| 18 | 2019 | 27 | |
| 19 | 2015 | 26 | |
| 20 | 2022 | 23 |
About Bum Chul Kwon
Bum Chul Kwon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems and Management, Sociology and Political Science and Human-Computer Interaction, having authored 61 papers that have together received 1.7k indexed citations. Recurring topics across this work include Data Visualization and Analytics (30 papers), Video Analysis and Summarization (7 papers), Explainable Artificial Intelligence (XAI) (6 papers), Machine Learning in Healthcare (6 papers), Cell Image Analysis Techniques (5 papers), Tactile and Sensory Interactions (5 papers), Mobile Health and mHealth Applications (4 papers) and Data Analysis with R (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (937 citations), Health Informatics (54 citations), Human-Computer Interaction (118 citations), Artificial Intelligence (633 citations) and Health Information Management (71 citations). Bum Chul Kwon has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include Daniel A. Keim, Sung-Hee Kim, Dominik Sacha, Geoffrey Ellis, Sukwon Lee, Ji Soo Yi, Andreas Stoffel, Jaegul Choo, Florian Stoffel and Hansi Senaratne. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, International Journal of Human-Computer Interaction, Scientific Reports, JMIR mhealth and uhealth and Diabetes.
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.