Stefano Ermon Google Scholar: h-index, Total Citations, and Citation Map
Stefano Ermon's h-index is 123 (345 i10-index, 154,322+ total citations across 529+ publications) according to Google Scholar as of November 2026. Stefano Ermon is affiliated with Stanford University.
Stefano Ermon is a researcher affiliated with Stanford University, specializing in AI & Machine Learning. Their work has been cited 154,322 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Stefano Ermon's Citation Metrics
Bibliometric impact based on 529 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 123
- i10-Index
- 345
- Total Citations
- 154,322
- Citing Countries
- 98
As of November 2026.
Stefano Ermon has an h-index of 123 and 154,322 total citations across 529 publications, with research cited by institutions in 98 countries.
Global Impact Map
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Denoising diffusion implicit models
202014,014
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.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Stefano Ermon's research
Stefano Ermon is a researcher in AI & Machine Learning at Stanford University. Their work has been cited 154,322 times across 529 publications (h-index 123), according to Google Scholar.
Their most-cited work, “Denoising diffusion implicit models” (2020), has accumulated 14,014 citations. Other influential works include “On the Opportunities and Risks of Foundation Models” (2021) with 2,137 citations and “Csdi: Conditional score-based diffusion models for probabilistic time series imputation” (2021) with 1,602 citations.
Citations of Stefano Ermon's research come primarily from United States, China 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.
