Leonidas Guibas: h-index, Total Citations, and Citation Map
Leonidas Guibas's h-index is 164 (628 i10-index, 184,638+ total citations across 1,000+ publications) according to Google Scholar as of September 2026. Leonidas Guibas is affiliated with Professor of Computer Science, Stanford University.
Leonidas Guibas is a researcher affiliated with Professor of Computer Science, Stanford University, specializing in geometric computing, computer vision, computer graphics. Their work has been cited 184,638 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Leonidas Guibas's Citation Metrics
Bibliometric impact based on 1,000 indexed publications.
- H-Index
- 164
- i10-Index
- 628
- Total Citations
- 184,638
- Citing Countries
- 80
As of September 2026.
Leonidas Guibas has an h-index of 164 and 184,638 total citations across 1000 publications, with research cited by institutions in 80 countries.
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Global Impact Map
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Pointnet: Deep learning on point sets for 3d classification and segmentation
201725,385
Top Citing Countries
Top Citing Institutions
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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.
339 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered deep hierarchical feature learning for point sets, establishing a foundational framework for 3D deep learning that enabled subsequent advances in flexible convolution and object detection.
The researcher pioneered the application of Earth Mover's Distance for image retrieval and advanced 3D point cloud representation learning, establishing foundational metrics and generative models widely adopted by the independent research community.
The researcher pioneered direct deep learning on raw point sets for 3D classification and segmentation, establishing a foundational framework that enabled subsequent advances in object detection and hierarchical part-level understanding.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Leonidas Guibas's research
Leonidas Guibas is a researcher in geometric computing, computer vision and computer graphics at Professor of Computer Science, Stanford University. Their work has been cited 184,638 times across 1,000 publications (h-index 164), according to Google Scholar.
Their most-cited work, “Pointnet: Deep learning on point sets for 3d classification and segmentation” (2017), has accumulated 25,385 citations. Other influential works include “Pointnet++: Deep hierarchical feature learning on point sets in a metric space” (2017) with 19,408 citations and “Shapenet: An information-rich 3d model repository” (2015) with 8,194 citations.
Citations of Leonidas Guibas's research come primarily from China, United States 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.
