Hinton Google Scholar: h-index, Total Citations, and Citation Map
Hinton's h-index is 195 (553 i10-index, 1,089,507+ total citations across 838+ publications) according to Google Scholar as of October 2026. Hinton is affiliated with Emeritus Prof. Computer Science, University of Toronto.
Hinton is a researcher affiliated with Emeritus Prof. Computer Science, University of Toronto, specializing in machine learning, psychology, artificial intelligence. Their work has been cited 1,089,507 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Hinton's Citation Metrics
Bibliometric impact based on 838 indexed publications.
- H-Index
- 195
- i10-Index
- 553
- Total Citations
- 1,089,507
- Citing Countries
- 115
As of October 2026.
Hinton has an h-index of 195 and 1,089,507 total citations across 838 publications, with research cited by institutions in 115 countries.
Global Impact Map
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ImageNet classification with deep convolutional neural networks
2012198,566
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.
12288 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established foundational techniques for regularizing and compressing deep neural networks, significantly advancing the practical deployment of deep learning models.
The researcher established foundational methodologies for deep visual learning, advancing from core image classification to robust representation learning and normalization techniques.
The researcher established foundational methods for reducing data dimensionality with neural networks, a line of work that subsequently enabled deep learning applications in speech recognition and computer vision.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Hinton's research
Hinton is a researcher in machine learning, psychology and artificial intelligence at Emeritus Prof. Computer Science, University of Toronto. Their work has been cited 1,089,507 times across 838 publications (h-index 195), according to Google Scholar.
Their most-cited work, “ImageNet classification with deep convolutional neural networks” (2012), has accumulated 198,566 citations. Other influential works include “Deep learning” (2015) with 117,439 citations and “Visualizing High-Dimensional Data Using t-SNE” (2008) with 70,348 citations.
Citations of Hinton'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.
