Eli Shechtman Google Scholar: h-index, Total Citations, and Citation Map
Eli Shechtman's h-index is 84 (167 i10-index, 71,958+ total citations across 242+ publications) according to Google Scholar as of October 2026. Eli Shechtman is affiliated with Adobe Research.
Eli Shechtman is a researcher affiliated with Adobe Research, specializing in Computer Vision, Computer Graphics, Machine Learning. Their work has been cited 71,958 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Eli Shechtman's Citation Metrics
Bibliometric impact based on 242 indexed publications.
- H-Index
- 84
- i10-Index
- 167
- Total Citations
- 71,958
- Citing Countries
- 44
As of October 2026.
Eli Shechtman has an h-index of 84 and 71,958 total citations across 242 publications, with research cited by institutions in 44 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Eli Shechtman's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
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.
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
201823,486
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 introduced a foundational framework for modeling human actions as space-time shapes, establishing a seminal approach in computer vision that has been widely adopted by the independent research community.
The researcher established deep neural network features as a robust perceptual metric for image quality, fundamentally shifting how visual similarity is quantified in computer vision.
The researcher advanced multimodal image-to-image translation, establishing a foundational framework that has been widely adopted by the independent research community.
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.
About Eli Shechtman's research
Eli Shechtman is a researcher in Computer Vision, Computer Graphics and Machine Learning at Adobe Research. Their work has been cited 71,958 times across 242 publications (h-index 84), according to Google Scholar.
Their most-cited work, “The Unreasonable Effectiveness of Deep Features as a Perceptual Metric” (2018), has accumulated 23,486 citations. Other influential works include “PatchMatch: A randomized correspondence algorithm for structural image editing” (2009) with 4,308 citations and “Actions as space-time shapes” (2005) with 2,277 citations.
Citations of Eli Shechtman's research come primarily from China, United States and Singapore, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
