David Silver Google Scholar: h-index, Total Citations, and Citation Map
David Silver's h-index is 106 (185 i10-index, 317,131+ total citations across 101+ publications) according to Google Scholar as of October 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 United States.
David Silver's Citation Metrics
Bibliometric impact based on 101 indexed publications.
- H-Index
- 106
- i10-Index
- 185
- Total Citations
- 317,131
- Citing Countries
- 81
As of October 2026.
David Silver has an h-index of 106 and 317,131 total citations across 101 publications, with research cited by institutions in 81 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing David Silver's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Showing partial map from open academic databases
Upgrade ($39.98) for the complete Google Scholar crawl.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
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)
Related Guides
Learn how to use citation maps for your research and visa applications.
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 101 publications (h-index 106), 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 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.
