Shakir Mohamed is a researcher affiliated with Research Director, Google DeepMind, specializing in AI & Machine Learning. Their work has been cited 39,061 times. This profile visualizes their global influence, highlighting strong citation networks in CN.
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Bibliometric impact based on 1 indexed publication.
As of April 2026.
Shakir Mohamed has an h-index of 1 and 39,061 total citations across 1 publication, with research cited by institutions in 2 countries.
Visualizing the geographic distribution of institutions that have cited your work.
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.
Visa-ready visualisation: each outer ring node is a country citing this scholar. Node size & edge weight scale with citing-paper count. Showing top 2 of 2 countries (7 total citations).
Ranked by EB-1A / O-1A relevance: independence from your home institution, affiliation with a top-ranked institution, repeat citations of your work, and recency. Reach out to the highest-scoring candidates to request support letters.
Shenda Hong
7.0Peking University
China· Cited your work 1 time
Bin Cui
7.0Peking University
China· Cited your work 1 time
Yang Song
8.5OpenAI
USA· Cited your work 1 time
Runsheng Xu
8.5University of California, Los Angeles
USA· Cited your work 1 time
Zhilong Zhang
7.0Peking University
China· Cited your work 1 time
Wentao Zhang
7.0Peking University
China· Cited your work 1 time
Yue Zhao
8.5Carnegie Mellon University
USA· Cited your work 1 time
Scores combine 5 signals: independence (+3), prestige institution (+2), repeat citations (+2 per paper, cap 5), recent activity (+1), and geography diversity (+1.5). Identity matching uses name + institution; namesakes at the same org are merged.
Citations flagged as non-independent share the scholar's home institution (Google DeepMind). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
Wentao Zhang, Bin Cui, Ling Yang, Zhilong Zhang + 5 more
ACM Computing Surveys· cites “Stochastic Backpropagation and Approximate Inference in Deep Generative Models”
· cites “Stochastic Backpropagation and Approximate Inference in Deep Generative Models”
· cites “Stochastic Backpropagation and Approximate Inference in Deep Generative Models”
· cites “Stochastic Backpropagation and Approximate Inference in Deep Generative Models”
· cites “Stochastic Backpropagation and Approximate Inference in Deep Generative Models”
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