Saining Xie: h-index, Total Citations, and Citation Map
Saining Xie's h-index is 54 (81 i10-index, 111,447+ total citations across 107+ publications) according to Google Scholar as of July 2026. Saining Xie is affiliated with AMI Labs; New York University.
Saining Xie is a researcher affiliated with AMI Labs; New York University, specializing in artificial intelligence, computer vision, machine learning. Their work has been cited 111,447 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Saining Xie's Citation Metrics
Bibliometric impact based on 107 indexed publications.
- H-Index
- 54
- i10-Index
- 81
- Total Citations
- 111,447
- Citing Countries
- 60
As of July 2026.
Saining Xie has an h-index of 54 and 111,447 total citations across 107 publications, with research cited by institutions in 60 countries.
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Global Impact Map
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Momentum Contrast for Unsupervised Visual Representation Learning
202020,891
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.
1071 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced 3D point cloud recognition by introducing attentional shape context methods and pioneering unsupervised contrastive pre-training frameworks for data-efficient scene understanding.
The researcher established a foundational framework for analyzing CLIP data, subsequently pioneering critical evaluations of visual capabilities and open-source architectures in multimodal large language models.
The researcher developed Momentum Contrast, a seminal framework for unsupervised visual representation learning that has achieved widespread independent adoption across the computer vision community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Saining Xie's research
Saining Xie is a researcher in artificial intelligence, computer vision and machine learning at AMI Labs; New York University. Their work has been cited 111,447 times across 107 publications (h-index 54), according to Google Scholar.
Their most-cited work, “Momentum Contrast for Unsupervised Visual Representation Learning” (2020), has accumulated 20,891 citations. Other influential works include “Aggregated Residual Transformations for Deep Neural Networks” (2017) with 17,044 citations and “Masked Autoencoders are Scalable Vision Learners” (2022) with 16,310 citations.
Citations of Saining Xie'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.
