Robert Tibshirani: h-index, Total Citations, and Citation Map
Robert Tibshirani's h-index is 199 (594 i10-index, 612,866+ total citations across 3+ publications) according to Google Scholar as of June 2026. Robert Tibshirani is affiliated with Professor of Biomedical Data Sciences, and of Statistics, Stanford University.
Robert Tibshirani is a researcher affiliated with Professor of Biomedical Data Sciences, and of Statistics, Stanford University, specializing in Statistics, data science, Machine Learning. Their work has been cited 612,866 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Robert Tibshirani's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 199
- i10-Index
- 594
- Total Citations
- 612,866
- Citing Countries
- 27
As of June 2026.
Robert Tibshirani has an h-index of 199 and 612,866 total citations across 3 publications, with research cited by institutions in 27 countries.
Global Impact Map
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
200195,865
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, highly cited monograph that synthesized key methodologies for the field.
The researcher established a foundational framework for bootstrap methodology, as evidenced by the seminal 1994 paper that has garnered over 58,000 citations.
The researcher developed efficient coordinate descent algorithms for computing regularization paths in generalized linear models, establishing a foundational computational framework widely adopted in statistical software.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Robert Tibshirani's research
Robert Tibshirani is a researcher in Statistics, data science and Machine Learning at Professor of Biomedical Data Sciences, and of Statistics, Stanford University. Their work has been cited 612,866 times across 3 publications (h-index 199), according to Google Scholar.
Their most-cited work, “The Elements of Statistical Learning: Data Mining, Inference, and Prediction” (2001), has accumulated 95,865 citations. Other influential works include “An introduction to the bootstrap” (1994) with 58,862 citations and “Regularization Paths for Generalized Linear Models via Coordinate Descent” (2010) with 22,753 citations.
Citations of Robert Tibshirani's research come primarily from United States, United Kingdom and China, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
