Jian Wu: h-index, Total Citations, and Citation Map
Jian Wu's h-index is 159 (1691 i10-index, 158,067+ total citations across 3+ publications) according to Google Scholar as of May 2026. Jian Wu is affiliated with Microsoft Corp.
Jian Wu is a researcher affiliated with Microsoft Corp, specializing in Speech recognition, natural language processing, machine learnin. Their work has been cited 158,067 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Jian Wu's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 159
- i10-Index
- 1691
- Total Citations
- 158,067
- Citing Countries
- 8
As of May 2026.
Jian Wu has an h-index of 159 and 158,067 total citations across 3 publications, with research cited by institutions in 8 countries.
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We've mapped 5,000 of 158,067 citations for Jian Wu
We've shown the most-cited 5,000. Unlock the full crawl (158,052 more citations) to see every institution citing this scholar.
Global Impact Map
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Top Cited Works
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Guidelines for the use and interpretation of assays for monitoring autophagy
202114,822
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.
2 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered methods for detecting circulating tumor DNA across early and late-stage human malignancies, establishing a foundational approach for non-invasive cancer monitoring.
The researcher established standardized guidelines for autophagy assay interpretation, creating a foundational reference that has been cited over 14,000 times by independent scientists.
The researcher developed Unet 3+, a full-scale connected architecture for medical image segmentation, establishing a highly cited foundation for advanced neural network design in biomedical imaging.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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