Juntang Zhuang Google Scholar: h-index, Total Citations, and Citation Map
Juntang Zhuang's h-index is 16 (20 i10-index, 42,574+ total citations across 20+ publications) according to Google Scholar as of October 2026. Juntang Zhuang is affiliated with Yale University.
Juntang Zhuang is a researcher affiliated with Yale University, specializing in various fields. Their work has been cited 42,574 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Juntang Zhuang's Citation Metrics
Bibliometric impact based on 20 indexed publications.
- H-Index
- 16
- i10-Index
- 20
- Total Citations
- 42,574
- Citing Countries
- 56
As of October 2026.
Juntang Zhuang has an h-index of 16 and 42,574 total citations across 20 publications, with research cited by institutions in 56 countries.
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BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis
2020653
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.
1 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed interpretable deep learning frameworks for fMRI analysis, establishing a methodological lineage from initial biomarker interpretation in ASD to scalable graph neural networks.
The researcher developed machine learning frameworks for ASD biomarker selection and treatment outcome prediction, establishing a methodological lineage from random forest models to invertible networks.
The researcher developed LadderNet, a multi-path U-Net architecture for medical image segmentation, establishing a widely adopted framework for hierarchical feature integration in biomedical imaging.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Juntang Zhuang's research
Juntang Zhuang is a researcher at Yale University. Their work has been cited 42,574 times across 20 publications (h-index 16), according to Google Scholar.
Their most-cited work, “BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis” (2020), has accumulated 653 citations. Other influential works include “LadderNet: Multi-path networks based on U-Net for medical image segmentation” (2018) with 222 citations and “AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed\n Gradients” (2020) with 219 citations.
Citations of Juntang Zhuang'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.
