Anqi Zhu: h-index, Total Citations, and Citation Map
Anqi Zhu's h-index is 7 (6 i10-index, 2,454+ total citations across 5+ publications) according to Google Scholar as of May 2026. Anqi Zhu is affiliated with Genentech.
Anqi Zhu is a researcher affiliated with Genentech, specializing in Statistics, Bioinformatics, Causal Inference. Their work has been cited 2,454 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Anqi Zhu's Citation Metrics
Bibliometric impact based on 5 indexed publications. Of these, 4 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 7
- i10-Index
- 6
- Total Citations
- 2,454
- Citing Countries
- 10
As of May 2026.
Anqi Zhu has an h-index of 7 and 2,454 total citations across 5 publications, with research cited by institutions in 10 countries.
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Global Impact Map
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Top Cited Works
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Heavy-tailed prior distributions for sequence count data: removing the noise and preserving large differences
20192,183
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 statistical framework using heavy-tailed priors to denoise sequence count data while preserving large biological differences, as evidenced by their highly cited 2019 Bioinformatics paper.
The researcher developed a nonparametric framework for expression analysis using inferential replicate counts, establishing a robust statistical method for genomic data interpretation.
The researcher characterized the mutational profile and monocytic differentiation features of acute myeloid leukemia with co-mutated ASXL1 and SRSF2.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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