Brian R Hunt: h-index, Total Citations, and Citation Map
Brian R Hunt's h-index is 60 (118 i10-index, 19,636+ total citations across 235+ publications) according to Google Scholar as of May 2026. Brian R Hunt is affiliated with University of Maryland.
Brian R Hunt is a researcher affiliated with University of Maryland, specializing in various fields. Their work has been cited 19,636 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Brian R Hunt's Citation Metrics
Bibliometric impact based on 235 indexed publications. Of these, 14 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 60
- i10-Index
- 118
- Total Citations
- 19,636
- Citing Countries
- 23
As of May 2026.
Brian R Hunt has an h-index of 60 and 19,636 total citations across 235 publications, with research cited by institutions in 23 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Brian R Hunt's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
We've mapped 5,000 of 19,636 citations for Brian R Hunt
We've shown the most-cited 5,000. Unlock the full crawl (19,294 more citations) to see every institution citing this scholar.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Top Cited Works
Tip: clickto hide a row from the map
Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter
20072,161
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 the Local Ensemble Transform Kalman Filter, a seminal method for efficient data assimilation in spatiotemporal chaotic systems, establishing a foundational approach widely adopted across scientific disciplines.
The researcher established a translation-invariant notion of 'almost every' for infinite-dimensional spaces, providing a foundational framework for prevalence in mathematical analysis.
The researcher developed a Local Ensemble Kalman Filter for atmospheric data assimilation, establishing a foundational method for handling high-dimensional systems in meteorology.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
