Yaojia Zhu: h-index, Total Citations, and Citation Map
Yaojia Zhu's h-index is 6 (6 i10-index, 357+ total citations across 5+ publications) according to Google Scholar as of May 2026. Yaojia Zhu is affiliated with Unknown affiliation.
Yaojia Zhu is a researcher affiliated with Unknown affiliation, specializing in various fields. Their work has been cited 357 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Yaojia Zhu's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 6
- i10-Index
- 6
- Total Citations
- 357
- Citing Countries
- 14
As of May 2026.
Yaojia Zhu has an h-index of 6 and 357 total citations across 5 publications, with research cited by institutions in 14 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Yaojia Zhu's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Top Cited Works
Tip: clickto hide a row from the map
Model Selection for Degree-corrected Block Models
2014149
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.
The researcher developed a model selection framework for degree-corrected block models, establishing a rigorous statistical foundation for community detection in heterogeneous networks.
The researcher advanced active learning for node classification by addressing the distinct challenges of assortative and disassortative network structures.
The researcher developed an improved extremal optimization algorithm for the asymmetric traveling salesman problem, advancing heuristic methods for complex combinatorial optimization challenges.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.











