Peking University
Cornell University
Dragomir AnguelovVice President, Head of AI Foundations Team · WaymoResearcher↗
Researcher · Engineer
Mingxing Tan
WaymoResearch Director
Tan co-created EfficientNet, which showed that carefully scaling a network's depth, width and image resolution together could deliver better accuracy with far less computation.[1] He extended the approach to efficient object detection and now develops perception and foundation models for autonomous driving at Waymo.
Career & education
Current roleWaymo2021-presentResearch Director
Waymo2021-presentPreviously
Google Brain2015-2021Researcher
Google Brain2015-2021Education
Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations102,762As of Nov 1, '26
References
- EfficientNet: Rethinking Model Scaling for Convolutional Neural Networksproceedings.mlr.press
Tan and Quoc Le show how scaling depth, width and input resolution together improves the efficiency of image recognition.
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Reviewed August 10, 2026 · Checked for accuracy and new information.
