Aja Huang Google Scholar: h-index, Total Citations, and Citation Map
Aja Huang's h-index is 16 (17 i10-index, 46,019+ total citations across 22+ publications) according to Google Scholar as of October 2026. Aja Huang is affiliated with DeepMind.
Aja Huang is a researcher affiliated with DeepMind, specializing in various fields. Their work has been cited 46,019 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Aja Huang's Citation Metrics
Bibliometric impact based on 22 indexed publications.
- H-Index
- 16
- i10-Index
- 17
- Total Citations
- 46,019
- Citing Countries
- 52
As of October 2026.
Aja Huang has an h-index of 16 and 46,019 total citations across 22 publications, with research cited by institutions in 52 countries.
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Global Impact Map
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Mastering the game of Go with deep neural networks and tree search
201635,824
Top Citing Countries
Top Citing Institutions
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Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Aja Huang's research
Aja Huang is a researcher at DeepMind. Their work has been cited 46,019 times across 22 publications (h-index 16), according to Google Scholar.
Their most-cited work, “Mastering the game of Go with deep neural networks and tree search” (2016), has accumulated 35,824 citations. Other influential works include “Grandmaster level in StarCraft II using multi-agent reinforcement learning” (2019) with 6,738 citations and “Discovering faster matrix multiplication algorithms with reinforcement learning” (2022) with 1,190 citations.
Citations of Aja Huang'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.
