Trevor Hastie Google Scholar: h-index, Total Citations, and Citation Map
Trevor Hastie's h-index is 166 (457 i10-index, 472,731+ total citations across 99+ publications) according to Google Scholar as of November 2026. Trevor Hastie is affiliated with Stanford University.
Trevor Hastie is a researcher affiliated with Stanford University, specializing in Statistical learning and modeling, data mining, machine learning. Their work has been cited 472,731 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Trevor Hastie's Citation Metrics
Bibliometric impact based on 99 indexed publications.
- H-Index
- 166
- i10-Index
- 457
- Total Citations
- 472,731
- Citing Countries
- 98
As of November 2026.
Trevor Hastie has an h-index of 166 and 472,731 total citations across 99 publications, with research cited by institutions in 98 countries.
Global Impact Map
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Elements of Statistical Learning
2009116,357
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 established a foundational framework for statistical learning, data mining, and prediction through a seminal textbook that has become a standard reference in the field.
The researcher authored a seminal textbook on statistical learning that has become a foundational reference for data mining, inference, and prediction, accumulating over 100,000 citations.
The researcher developed the elastic net, a regularization method combining L1 and L2 penalties to address variable selection challenges in high-dimensional statistical modeling.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Trevor Hastie's research
Trevor Hastie is a researcher in Statistical learning and modeling, data mining and machine learning at Stanford University. Their work has been cited 472,731 times across 99 publications (h-index 166), according to Google Scholar.
Their most-cited work, “Elements of Statistical Learning” (2009), has accumulated 116,357 citations. Other influential work includes “The Elements of Statistical Learning: Data Mining, Inference, and Prediction” (2009) with 109,013 citations.
Citations of Trevor Hastie'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.
