Seonwoo Min: h-index, Total Citations, and Citation Map
Seonwoo Min's h-index is 22 (27 i10-index, 5,186+ total citations across 29+ publications) according to Google Scholar as of June 2026. Seonwoo Min is affiliated with Seoul National University.
Seonwoo Min is a researcher affiliated with Seoul National University, specializing in Machine Learning, NLP. Their work has been cited 5,186 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Seonwoo Min's Citation Metrics
Bibliometric impact based on 29 indexed publications.
- H-Index
- 22
- i10-Index
- 27
- Total Citations
- 5,186
- Citing Countries
- 74
As of June 2026.
Seonwoo Min has an h-index of 22 and 5,186 total citations across 29 publications, with research cited by institutions in 74 countries.
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Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
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Deep learning in bioinformatics
20172,267
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
22 citing papers could not be classified (no author data) — excluded from the percentages above.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Seonwoo Min's research
Seonwoo Min is a researcher in Machine Learning and NLP at Seoul National University. Their work has been cited 5,186 times across 29 publications (h-index 22), according to Google Scholar.
Their most-cited work, “Deep learning in bioinformatics” (2017), has accumulated 2,267 citations. Other influential works include “Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity” (2018) with 416 citations and “Pure transformers are powerful graph learners” (2022) with 353 citations.
Citations of Seonwoo Min's research come primarily from China, United States and South Korea, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
