vapnik: h-index, Total Citations, and Citation Map
vapnik's h-index is 107 (302 i10-index, 351,665+ total citations across 3+ publications) according to Google Scholar as of May 2026. vapnik is affiliated with Professor of Columbia, Fellow of NEC Labs America,.
vapnik is a researcher affiliated with Professor of Columbia, Fellow of NEC Labs America,, specializing in machine learning, statistics, computer science. Their work has been cited 351,665 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
vapnik's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 107
- i10-Index
- 302
- Total Citations
- 351,665
- Citing Countries
- 11
As of May 2026.
vapnik has an h-index of 107 and 351,665 total citations across 3 publications, with research cited by institutions in 11 countries.
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Global Impact Map
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Top Cited Works
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The Nature of Statistical Learning Theory
1995113,525
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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 pioneered the application of backpropagation to handwritten zip code recognition, establishing a foundational benchmark for neural network performance in practical pattern recognition tasks.
The researcher established the foundational theoretical framework for statistical learning theory, providing rigorous bounds on generalization error that underpin modern machine learning.
The researcher introduced support-vector networks, a foundational machine learning framework that has achieved widespread independent adoption, evidenced by over 82,000 citations.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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