Mingxing Tan is a researcher affiliated with Waymo Research, Google Brain, specializing in AI & Machine Learning. Their work has been cited 89,204 times. This profile visualizes their global influence, spanning a global audience.
Unlock Full Map — Pro tier (10K–100K citations)
One-time payment. Full data, CSV export, and embed code.
Viewing Limited Data
Showing up to 10 papers and top 10 citing sources. Upgrade to see all 1 paper and complete citation data.
Bibliometric impact based on 1 indexed publication.
As of April 2026.
Mingxing Tan has an h-index of 1 and 89,204 total citations across 1 publication, with research cited by institutions in 0 countries.
Visualizing the geographic distribution of institutions that have cited your work.
No institution data available.
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.
Citations flagged as non-independent share the scholar's home institution (Google Research). EB-1A & O-1A petitions typically quote the independent-citation count as the stronger evidence of outside recognition.
· cites “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”
· cites “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”
Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu + 5 more
Advances in Neural Information Processing Systems 37 (NeurIPS 2024)· cites “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”
· cites “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”
· cites “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”
Learn how to use citation maps for your research and visa applications.
