Ming-Wei Chang: h-index, Total Citations, and Citation Map
Ming-Wei Chang's h-index is 1 (1 i10-index, 211,525+ total citations across 1+ publications) according to Google Scholar as of June 2026. Ming-Wei Chang is affiliated with Google Deepmind.
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 United States.
Ming-Wei Chang's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 211,525
- Citing Countries
- 3
As of June 2026.
Ming-Wei Chang has an h-index of 1 and 211,525 total citations across 1 publication, with research cited by institutions in 3 countries.
Global Impact Map
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
2018172,220
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.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Ming-Wei Chang's research
Ming-Wei Chang is a researcher in AI & Machine Learning at Google Deepmind. Their work has been cited 211,525 times across 1 publications, according to Google Scholar.
Their most-cited work, “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding” (2018), has accumulated 172,220 citations.
Citations of Ming-Wei Chang's research come primarily from United States, China and Taiwan, reflecting international research impact. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
