Tsinghua University
Chinese University of Hong Kong
Ming-Hsuan YangResearch Scientist · Google DeepMindResearcher↗
Researcher · Academic
Kaiming He
MITAssociate Professor
Google DeepMindDistinguished Scientist
He led ResNet, which lets information take shortcuts through a neural network and made far deeper models practical. He also helped create systems that locate and outline objects in images, and methods that teach visual AI by asking it to reconstruct missing parts of a picture.
Career & education
Current rolesMITFeb 2024-presentAssociate Professor
MITFeb 2024-presentDistinguished Scientist
Previously
Meta2016-2024Research Scientist, FAIR
Meta2016-2024Microsoft Research Asia2011-2016
ResearcherWork 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.
citations879,889As of Oct 1, '26
citations+11,209Since last snapshot, Sep 1, '26
Selected contributions
Deep Residual Learning for Image Recognition
Introduced ResNet, using shortcut connections between layers to make much deeper neural networks easier to train, improving their ability to recognize objects in images accurately.
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Made object detection faster by teaching a neural network where to look, sharing image processing between finding likely objects and identifying what those objects are.
Mask R-CNN
Extended object detection to trace the outline of each individual object, allowing computers to identify what appears in an image and precisely where it is.
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Reviewed August 7, 2026 · Checked for accuracy and new information.
