Leonidas Guibas Google Scholar: h-index, Total Citations, and Citation Map
Leonidas Guibas's h-index is 164 (635 i10-index, 190,598+ total citations across 1,000+ publications) according to Google Scholar as of October 2026. Leonidas Guibas is affiliated with Stanford University.
Leonidas Guibas is a researcher affiliated with Stanford University, specializing in geometric computing, computer vision, computer graphics. Their work has been cited 190,598 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
- 635
- Total Citations
- 190,598
- Citing Countries
- 88
As of October 2026.
Leonidas Guibas has an h-index of 164 and 190,598 total citations across 1000 publications, with research cited by institutions in 88 countries.
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Global Impact Map
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Pointnet: Deep learning on point sets for 3d classification and segmentation
201726,650
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
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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 Stanford University. Their work has been cited 190,598 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 26,650 citations. Other influential work includes “Pointnet++: Deep hierarchical feature learning on point sets in a metric space” (2017) with 20,505 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.
