Yann LeCun Google Scholar: h-index, Total Citations, and Citation Map
Yann LeCun's h-index is 177 (510 i10-index, 503,901+ total citations across 806+ publications) according to Google Scholar as of October 2026. Yann LeCun is affiliated with Executive Chairman AMI Labs & Jacob T Schwarz Professor, Courant Institute, New York University.
Yann LeCun is a researcher affiliated with Executive Chairman AMI Labs & Jacob T Schwarz Professor, Courant Institute, New York University, specializing in AI, machine learning, computer vision. Their work has been cited 503,901 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Yann LeCun's Citation Metrics
Bibliometric impact based on 806 indexed publications.
- H-Index
- 177
- i10-Index
- 510
- Total Citations
- 503,901
- Citing Countries
- 112
As of October 2026.
Yann LeCun has an h-index of 177 and 503,901 total citations across 806 publications, with research cited by institutions in 112 countries.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
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Deep learning
2015124,576
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.
13113 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established a foundational framework for gradient-based learning in document recognition, which evolved into a seminal contribution to the field of deep learning.
The researcher established foundational convolutional network architectures for diverse data modalities, later extending this framework to catalyze next-generation neuro-inspired artificial intelligence.
The researcher established a foundational benchmark for handwritten digit recognition that catalyzed decades of subsequent research in visual representation learning.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Yann LeCun's research
Yann LeCun is a researcher in AI, machine learning and computer vision at Executive Chairman AMI Labs & Jacob T Schwarz Professor, Courant Institute, New York University. Their work has been cited 503,901 times across 806 publications (h-index 177), according to Google Scholar.
Their most-cited work, “Deep learning” (2015), has accumulated 124,576 citations. Other influential works include “Deep learning” (2015) with 123,087 citations and “Gradient-based learning applied to document recognition” (1998) with 90,794 citations.
Citations of Yann LeCun'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.
