Sung Won Han
Impact in
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- Advanced Statistical Process Monitoring
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- Pituitary Gland Disorders and Treatments
Papers in
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- Bioinformatics and Genomic Networks 9
- Gene expression and cancer classification 7
- Gene Regulatory Network Analysis 7
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- Speech Recognition and Synthesis 6
- Co-authors
- Geum Joon Cho (21 shared papers)Kwok‐Leung Tsui (5 shared papers)Judy Zhong (18 shared papers)Woo-Seok Shin (10 shared papers)Min‐Jeong Oh (15 shared papers)Iman Osman (9 shared papers)Min Seok Lee (2 shared papers)Manish K. Aghi (6 shared papers)
- Journals
- Scientific Reports (6 papers)IEEE Access (5 papers)Resources Conservation and Recycling (3 papers)Journal of Tribology (3 papers)BMC Pregnancy and Childbirth (3 papers)
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Sung Won Han
118 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 180
- Statistics, Probability and Uncertainty 125
- Endocrinology, Diabetes and Metabolism 176
- Statistics and Probability 76
- Obstetrics and Gynecology 62
- Signal Processing 94
Countries citing papers authored by Sung Won Han
This map shows the geographic impact of Sung Won Han'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 Sung Won Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sung Won Han more than expected).
Fields of papers citing papers by Sung Won Han
This network shows the impact of papers produced by Sung Won Han. 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 Sung Won Han. The network helps show where Sung Won Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Sung Won Han, 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 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 88 | |
| 2 | 2015 | 83 | |
| 3 | 2016 | 68 | |
| 4 | 2017 | 64 | |
| 5 | 2017 | 61 | |
| 6 | 2014 | 57 | |
| 7 | 2019 | 55 | |
| 8 | 2022 | 52 | |
| 9 | 2011 | 49 | |
| 10 | 2009 | 47 | |
| 11 | 2013 | 43 | |
| 12 | 2011 | 43 | |
| 13 | 2020 | 42 | |
| 14 | 2022 | 41 | |
| 15 | 2017 | 34 | |
| 16 | 2019 | 32 | |
| 17 | 2018 | 32 | |
| 18 | 2016 | 32 | |
| 19 | 2020 | 31 | |
| 20 | 2021 | 31 |
About Sung Won Han
Sung Won Han is a scholar working on Molecular Biology, Artificial Intelligence, Epidemiology, Signal Processing and Statistics, Probability and Uncertainty, having authored 127 papers that have together received 1.9k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (9 papers), Speech and Audio Processing (9 papers), Advanced Statistical Process Monitoring (8 papers), Data-Driven Disease Surveillance (8 papers), Music and Audio Processing (8 papers), Gene expression and cancer classification (7 papers), Gene Regulatory Network Analysis (7 papers) and Speech Recognition and Synthesis (6 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (125 citations), Endocrinology, Diabetes and Metabolism (176 citations), Statistics and Probability (76 citations), Obstetrics and Gynecology (62 citations) and Signal Processing (94 citations). Sung Won Han has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Geum Joon Cho, Kwok‐Leung Tsui, Judy Zhong, Woo-Seok Shin, Min‐Jeong Oh, Iman Osman, Min Seok Lee, Manish K. Aghi, Arman Jahangiri and Tak Kim. Their work appears in journals such as Scientific Reports, IEEE Access, Resources Conservation and Recycling, Journal of Tribology and BMC Pregnancy and Childbirth.
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.