Ming-Wei Chang is a researcher affiliated with Google Deepmind, specializing in AI & Machine Learning. Their work has been cited 211,525 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.
Ming-Wei Chang has an h-index of 1 and 211,525 total citations across 1 publication, with research cited by institutions in 1 country.
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 1 of 1 countries (29 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.
Zhiheng Xi
7.0Fudan University
China· Cited your work 1 time
Wenxiang Chen
7.0Fudan University
China· Cited your work 1 time
Xin Guo
7.0Fudan University
China· Cited your work 1 time
Wei He
7.0Fudan University
China· Cited your work 1 time
Yiwen Ding
7.0Fudan University
China· Cited your work 1 time
Boyang Hong
7.0Fudan University
China· Cited your work 1 time
Ming Zhang
7.0Fudan University
China· Cited your work 1 time
Junzhe Wang
7.0Fudan University
China· Cited your work 1 time
Senjie Jin
7.0Fudan University
China· Cited your work 1 time
Enyu Zhou
7.0Fudan University
China· 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). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
· cites “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He + 25 more
Science China Information Sciences· cites “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
· cites “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
· cites “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
· cites “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding”
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