Stephen M. Smith: h-index, Total Citations, and Citation Map
Stephen M. Smith's h-index is 170 (445 i10-index, 271,294+ total citations across 3+ publications) according to Google Scholar as of May 2026. Stephen M. Smith is affiliated with WIN (FMRIB), Oxford University.
Stephen M. Smith is a researcher affiliated with WIN (FMRIB), Oxford University, specializing in Brain imaging, MRI, Computational Neuroscience. Their work has been cited 271,294 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Stephen M. Smith's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 170
- i10-Index
- 445
- Total Citations
- 271,294
- Citing Countries
- 10
As of May 2026.
Stephen M. Smith has an h-index of 170 and 271,294 total citations across 3 publications, with research cited by institutions in 10 countries.
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We've mapped 5,000 of 271,294 citations for Stephen M. Smith
We've shown the most-cited 5,000. Unlock the full crawl (271,279 more citations) to see every institution citing this scholar.
Global Impact Map
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Top Cited Works
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Advances in functional and structural MR image analysis and implementation as FSL
200416,621
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.
7 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed FSL, a widely adopted software suite for functional and structural MR image analysis, establishing a foundational tool for neuroimaging research.
The researcher developed improved optimization methods for robust, accurate linear registration and motion correction of brain images, establishing a foundational standard in neuroimaging analysis.
The researcher published a seminal 2012 paper that has garnered over 13,000 citations, establishing a foundational contribution widely adopted by independent scholars across the field.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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