David Silver: h-index, Total Citations, and Citation Map
David Silver's h-index is 104 (180 i10-index, 317,131+ total citations across 227+ publications) according to Google Scholar as of September 2026. David Silver is affiliated with DeepMind, UCL.
David Silver is a researcher affiliated with DeepMind, UCL, specializing in Artificial Intelligence, Machine Learning, Reinforcement Learning. Their work has been cited 317,131 times. This profile visualizes their global influence, highlighting strong citation networks in China.
David Silver's Citation Metrics
Bibliometric impact based on 227 indexed publications.
- H-Index
- 104
- i10-Index
- 180
- Total Citations
- 317,131
- Citing Countries
- 74
As of September 2026.
David Silver has an h-index of 104 and 317,131 total citations across 227 publications, with research cited by institutions in 74 countries.
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Global Impact Map
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Highly accurate protein structure prediction with AlphaFold
202152,227
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.
11 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced Monte-Carlo planning by integrating online and offline knowledge in UCT, a framework subsequently extended to large POMDPs, establishing a foundational approach for decision-making under uncertainty.
The researcher pioneered massively parallel and asynchronous methods for deep reinforcement learning, establishing a foundational framework that significantly advanced the scalability and efficiency of training deep neural agents.
The researcher developed AlphaFold, a system for highly accurate protein structure prediction, establishing a foundational benchmark in computational biology.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About David Silver's research
David Silver is a researcher in Artificial Intelligence, Machine Learning and Reinforcement Learning at DeepMind, UCL. Their work has been cited 317,131 times across 227 publications (h-index 104), according to Google Scholar.
Their most-cited work, “Highly accurate protein structure prediction with AlphaFold” (2021), has accumulated 52,227 citations. Other influential works include “Human-level control through deep reinforcement learning” (2015) with 43,418 citations and “Mastering the game of Go with deep neural networks and tree search” (2016) with 25,529 citations.
Citations of David Silver's research come primarily from China, United States 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.
