Mehdi Mirza
Mehdi Mirza is a researcher affiliated with DeepMind, specializing in AI & Machine Learning. Their work has been cited 248,882 times. This profile visualizes their global influence, highlighting strong citation networks in US.
Mehdi Mirza is a researcher affiliated with DeepMind, specializing in AI & Machine Learning. Their work has been cited 248,882 times. This profile visualizes their global influence, highlighting strong citation networks in US.
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Bibliometric impact based on 1 indexed publication.
As of April 2026.
Mehdi Mirza has an h-index of 1 and 248,882 total citations across 1 publication, with research cited by institutions in 3 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 3 of 3 countries (5 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.
Tianhong Li
7.0Massachusetts Institute of Technology
United States· Cited your work 1 time
Mingyang Deng
7.0Massachusetts Institute of Technology
United States· Cited your work 1 time
Yonglong Tian
8.5Google DeepMind
United Kingdom· Cited your work 1 time
He Li
8.5Tsinghua University
China· Cited your work 1 time
Kaiming He
7.0Massachusetts Institute of Technology
United States· 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 (Université de Montréal). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
· cites “Generative Adversarial Nets”
· cites “Generative Adversarial Nets”
· cites “Generative Adversarial Nets”
· cites “Generative Adversarial Nets”
Tianhong Li, Mingyang Deng, Kaiming He, Yonglong Tian + 1 more
38th Conference on Neural Information Processing Systems (NeurIPS 2024)· cites “Generative Adversarial Nets”
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