Trevor Darrell Google Scholar: h-index, Total Citations, and Citation Map
Trevor Darrell's h-index is 189 (587 i10-index, 341,003+ total citations across 912+ publications) according to Google Scholar as of October 2026. Trevor Darrell is affiliated with U.C. Berkeley.
Trevor Darrell is a researcher affiliated with U.C. Berkeley, specializing in Computer Vision, Artificial Intelligence, AI. Their work has been cited 341,003 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Trevor Darrell's Citation Metrics
Bibliometric impact based on 912 indexed publications.
- H-Index
- 189
- i10-Index
- 587
- Total Citations
- 341,003
- Citing Countries
- 90
As of October 2026.
Trevor Darrell has an h-index of 189 and 341,003 total citations across 912 publications, with research cited by institutions in 90 countries.
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Global Impact Map
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Fully convolutional networks for semantic segmentation
201563,767
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
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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.
19 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered methods for simultaneous deep transfer across domains and tasks, establishing a foundational framework for adversarial domain adaptation that has been widely adopted by the independent research community.
The researcher developed rich feature hierarchies that significantly advanced the accuracy of object detection and semantic segmentation in computer vision.
The researcher pioneered fully convolutional networks for semantic segmentation, establishing a foundational architecture that transformed pixel-wise prediction in computer vision.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Trevor Darrell's research
Trevor Darrell is a researcher in Computer Vision, Artificial Intelligence and AI at U.C. Berkeley. Their work has been cited 341,003 times across 912 publications (h-index 189), according to Google Scholar.
Their most-cited work, “Fully convolutional networks for semantic segmentation” (2015), has accumulated 63,767 citations. Other influential work includes “Rich feature hierarchies for accurate object detection and semantic segmentation” (2014) with 47,707 citations.
Citations of Trevor Darrell's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
