Yuke Zhu Google Scholar: h-index, Total Citations, and Citation Map
Yuke Zhu's h-index is 79 (178 i10-index, 45,735+ total citations across 301+ publications) according to Google Scholar as of October 2026. Yuke Zhu is affiliated with The University of Texas at Austin, NVIDIA Research.
Yuke Zhu is a researcher affiliated with The University of Texas at Austin, NVIDIA Research, specializing in Robot Learning, Computer Vision, Machine Learning. Their work has been cited 45,735 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Yuke Zhu's Citation Metrics
Bibliometric impact based on 301 indexed publications.
- H-Index
- 79
- i10-Index
- 178
- Total Citations
- 45,735
- Citing Countries
- 69
As of October 2026.
Yuke Zhu has an h-index of 79 and 45,735 total citations across 301 publications, with research cited by institutions in 69 countries.
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Global Impact Map
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
20167,873
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.
11 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established foundational principles for offline robot learning from human demonstrations, subsequently scaling this approach through large-scale, open-source datasets and models that have become central to the field.
The researcher advanced object affordance reasoning and grounded visual question answering, establishing a foundational framework for task-oriented manipulation and semantic understanding in robotics and computer vision.
The researcher developed foundational interactive 3D simulation environments for visual AI and robot learning, establishing widely adopted benchmarks that advanced autonomous agent training.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Yuke Zhu's research
Yuke Zhu is a researcher in Robot Learning, Computer Vision and Machine Learning at The University of Texas at Austin, NVIDIA Research. Their work has been cited 45,735 times across 301 publications (h-index 79), according to Google Scholar.
Their most-cited work, “Visual genome: Connecting language and vision using crowdsourced dense image annotations” (2016), has accumulated 7,873 citations. Other influential work includes “Voyager: An open-ended embodied agent with large language models” (2023) with 3,095 citations.
Citations of Yuke Zhu'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.
