Kristen Grauman Google Scholar: h-index, Total Citations, and Citation Map
Kristen Grauman's h-index is 109 (257 i10-index, 59,073+ total citations across 457+ publications) according to Google Scholar as of October 2026. Kristen Grauman is affiliated with University of Texas at Austin.
Kristen Grauman is a researcher affiliated with University of Texas at Austin, specializing in various fields. Their work has been cited 59,073 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Kristen Grauman's Citation Metrics
Bibliometric impact based on 457 indexed publications.
- H-Index
- 109
- i10-Index
- 257
- Total Citations
- 59,073
- Citing Countries
- 65
As of October 2026.
Kristen Grauman has an h-index of 109 and 59,073 total citations across 457 publications, with research cited by institutions in 65 countries.
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Global Impact Map
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Advances in neural information processing systems 22
20099,941
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.
11 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered methods for identifying salient entities in egocentric video, establishing a foundational framework that enabled the creation of large-scale datasets for first-person vision research.
The researcher pioneered key-segment-based video object segmentation, establishing a foundational framework later expanded to fuse motion and appearance cues for fully automatic generic object segmentation.
The researcher pioneered fine-grained visual comparison methods and extended this framework to natural language-based image retrieval, establishing a foundational approach for detailed visual understanding.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Kristen Grauman's research
Kristen Grauman is a researcher at University of Texas at Austin. Their work has been cited 59,073 times across 457 publications (h-index 109), according to Google Scholar.
Their most-cited work, “Advances in neural information processing systems 22” (2009), has accumulated 9,941 citations. Other influential works include “Geodesic flow kernel for unsupervised domain adaptation” (2012) with 3,181 citations and “The pyramid match kernel: Discriminative classification with sets of image features” (2005) with 2,190 citations.
Citations of Kristen Grauman'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.
