Kurt Keutzer: h-index, Total Citations, and Citation Map
Kurt Keutzer's h-index is 123 (376 i10-index, 78,236+ total citations across 661+ publications) according to Google Scholar as of June 2026. Kurt Keutzer is affiliated with Professor of the Graduate School, EECS, University of California, Berkeley.
Kurt Keutzer is a researcher affiliated with Professor of the Graduate School, EECS, University of California, Berkeley, specializing in artificial intelligence systems, deep learning, efficient computation. Their work has been cited 78,236 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Kurt Keutzer's Citation Metrics
Bibliometric impact based on 661 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 123
- i10-Index
- 376
- Total Citations
- 78,236
- Citing Countries
- 67
As of June 2026.
Kurt Keutzer has an h-index of 123 and 78,236 total citations across 661 publications, with research cited by institutions in 67 countries.
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We've mapped 5,000 of 78,236 citations for Kurt Keutzer
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Global Impact Map
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size
201612,675
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.
13 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered lightweight neural network architectures, notably SqueezeNet, and advanced hardware-aware design and quantization methods to enable efficient, low-power deep learning inference.
The researcher developed DAGON, a seminal 1987 framework for technology binding and local optimization via DAG matching, establishing a foundational approach in electronic design automation.
The researcher provided a seminal, highly cited synthesis of the parallel computing research landscape, establishing a foundational reference point for the field.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Kurt Keutzer's research
Kurt Keutzer is a researcher in artificial intelligence systems, deep learning and efficient computation at Professor of the Graduate School, EECS, University of California, Berkeley. Their work has been cited 78,236 times across 661 publications (h-index 123), according to Google Scholar.
Their most-cited work, “SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size” (2016), has accumulated 12,675 citations. Other influential works include “The landscape of parallel computing research: A view from berkeley” (2006) with 3,111 citations and “Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge” (2018) with 2,801 citations.
Citations of Kurt Keutzer'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.
