Se Jin Song: h-index, Total Citations, and Citation Map
Se Jin Song's h-index is 49 (70 i10-index, 47,895+ total citations across 3+ publications) according to Google Scholar as of May 2026. Se Jin Song is affiliated with University of California San Diego.
Se Jin Song is a researcher affiliated with University of California San Diego, specializing in microbial ecology, symbiosis, evolution. Their work has been cited 47,895 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Se Jin Song's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 49
- i10-Index
- 70
- Total Citations
- 47,895
- Citing Countries
- 23
As of May 2026.
Se Jin Song has an h-index of 49 and 47,895 total citations across 3 publications, with research cited by institutions in 23 countries.
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We've mapped 5,000 of 47,895 citations for Se Jin Song
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Global Impact Map
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Top Cited Works
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Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
201925,419
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.
The researcher developed QIIME 2, a highly cited, reproducible, and scalable framework for interactive microbiome data science that has become a standard tool in the field.
The researcher established a foundational characterization of the treatment-naive microbiome in new-onset Crohn’s disease, providing a critical baseline for understanding disease-associated microbial shifts.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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