Jerome Friedman: h-index, Total Citations, and Citation Map
Jerome Friedman's h-index is 108 (222 i10-index, 385,117+ total citations across 3+ publications) according to Google Scholar as of July 2026. Jerome Friedman is affiliated with Unknown affiliation.
Jerome Friedman is a researcher affiliated with Unknown affiliation, specializing in various fields. Their work has been cited 385,117 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Jerome Friedman's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 108
- i10-Index
- 222
- Total Citations
- 385,117
- Citing Countries
- 13
As of July 2026.
Jerome Friedman has an h-index of 108 and 385,117 total citations across 3 publications, with research cited by institutions in 13 countries.
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Global Impact Map
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The elements of statistical learning: data mining, inference, and prediction
2009103,768
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.
1 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established a foundational framework for statistical learning, data mining, and prediction through a seminal 2009 text that has garnered over 100,000 citations.
The researcher introduced gradient boosting machines via greedy function approximation, establishing a foundational framework for ensemble learning that has achieved widespread independent adoption.
The researcher established a foundational framework for classification and regression trees, a seminal contribution that has become a standard reference in statistical learning.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Jerome Friedman's research
Jerome Friedman is a researcher at Unknown affiliation. Their work has been cited 385,117 times across 3 publications (h-index 108), according to Google Scholar.
Their most-cited work, “The elements of statistical learning: data mining, inference, and prediction” (2009), has accumulated 103,768 citations. Other influential works include “Classification and regression trees” (2017) with 70,733 citations and “Greedy function approximation: a gradient boosting machine” (2001) with 41,609 citations.
Citations of Jerome Friedman'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.











