Demis Hassabis: h-index, Total Citations, and Citation Map
Demis Hassabis's h-index is 92 (132 i10-index, 292,192+ total citations across 186+ publications) according to Google Scholar as of July 2026. Demis Hassabis is affiliated with DeepMind.
Demis Hassabis is a researcher affiliated with DeepMind, specializing in various fields. Their work has been cited 292,192 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Demis Hassabis's Citation Metrics
Bibliometric impact based on 186 indexed publications.
- H-Index
- 92
- i10-Index
- 132
- Total Citations
- 292,192
- Citing Countries
- 54
As of July 2026.
Demis Hassabis has an h-index of 92 and 292,192 total citations across 186 publications, with research cited by institutions in 54 countries.
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Global Impact Map
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Highly accurate protein structure prediction with AlphaFold
202142,952
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.
2368 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced complementary learning systems theory by addressing catastrophic forgetting and integrating fast and slow learning mechanisms in neural networks.
The researcher pioneered hybrid neural architectures with dynamic external memory, establishing a foundational framework subsequently applied to critical clinical prediction and complex reinforcement learning tasks.
The researcher advanced computational biology by developing AlphaFold for high-accuracy protein structure prediction and extending it to biomolecular interactions with AlphaFold 3.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Demis Hassabis's research
Demis Hassabis is a researcher at DeepMind. Their work has been cited 292,192 times across 186 publications (h-index 92), according to Google Scholar.
Their most-cited work, “Highly accurate protein structure prediction with AlphaFold” (2021), has accumulated 42,952 citations. Other influential works include “Highly accurate protein structure prediction with AlphaFold” (2021) with 42,952 citations and “Highly accurate protein structure prediction with AlphaFold” (2021) with 42,952 citations.
Citations of Demis Hassabis's research come primarily from United States, China 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.
