Alexei A. Efros Google Scholar: h-index, Total Citations, and Citation Map
Alexei A. Efros's h-index is 96 (183 i10-index, 196,957+ total citations across 273+ publications) according to Google Scholar as of October 2026. Alexei A. Efros is affiliated with Dept. of Electrical Engineering and Computer Sciences, UC Berkeley.
Alexei A. Efros is a researcher affiliated with Dept. of Electrical Engineering and Computer Sciences, UC Berkeley, specializing in AI & Machine Learning. Their work has been cited 196,957 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Alexei A. Efros's Citation Metrics
Bibliometric impact based on 273 indexed publications.
- H-Index
- 96
- i10-Index
- 183
- Total Citations
- 196,957
- Citing Countries
- 89
As of October 2026.
Alexei A. Efros has an h-index of 96 and 196,957 total citations across 273 publications, with research cited by institutions in 89 countries.
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Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
201732,042
Top Citing Countries
Top Citing Institutions
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Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Alexei A. Efros's research
Alexei A. Efros is a researcher in AI & Machine Learning at Dept. of Electrical Engineering and Computer Sciences, UC Berkeley. Their work has been cited 196,957 times across 273 publications (h-index 96), according to Google Scholar.
Their most-cited work, “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks” (2017), has accumulated 32,042 citations. Other influential works include “The Unreasonable Effectiveness of Deep Features as a Perceptual Metric” (2018) with 11,717 citations and “Colorful Image Colorization” (2016) with 3,312 citations.
Citations of Alexei A. Efros'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.
