Ziad Obermeyer: h-index, Total Citations, and Citation Map
Ziad Obermeyer's h-index is 48 (69 i10-index, 25,249+ total citations across 108+ publications) according to Google Scholar as of June 2026. Ziad Obermeyer is affiliated with UC Berkeley.
Ziad Obermeyer is a researcher affiliated with UC Berkeley, specializing in Machine learning, medicine, public policy. Their work has been cited 25,249 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Ziad Obermeyer's Citation Metrics
Bibliometric impact based on 108 indexed publications. Of these, 4 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 48
- i10-Index
- 69
- Total Citations
- 25,249
- Citing Countries
- 9
As of June 2026.
Ziad Obermeyer has an h-index of 48 and 25,249 total citations across 108 publications, with research cited by institutions in 9 countries.
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We've mapped 5,000 of 25,249 citations for Ziad Obermeyer
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Dissecting racial bias in an algorithm used to manage the health of populations
20199,498
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Visa Evidence Package
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Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Ziad Obermeyer's research
Ziad Obermeyer is a researcher in Machine learning, medicine and public policy at UC Berkeley. Their work has been cited 25,249 times across 108 publications (h-index 48), according to Google Scholar.
Their most-cited work, “Dissecting racial bias in an algorithm used to manage the health of populations” (2019), has accumulated 9,498 citations. Other influential works include “Predicting the future—big data, machine learning, and clinical medicine” (2016) with 5,112 citations and “Prediction policy problems” (2015) with 970 citations.
Citations of Ziad Obermeyer's research come primarily from United States, China and Australia, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
