About
Jianming Liang is a full professor at Arizona State University's College of Health Solutions, specializing in biomedical informatics, data science, and computer vision. His research focuses on self-supervised learning, foundation models, and improving transfer learning techniques for medical imaging applications.
- National Academy of Inventors Fellow (2021)
- ASU Faculty Innovation Award (2019)
- ASU Distinguished Faculty Award (2023)
- NIH R01 grant recipient
- Led lab producing FDA-approved medical imaging products
His lab has developed multiple open-source frameworks like Ark, Foundation_X, and ModelsGenesis for medical image analysis. Team has received over 70 student research awards including NCWIT Collegiate and AMIA Ph.D. Dissertation honors.
Key research contributions include:
- Anatomically consistent foundation models
- Domain-adaptive pretraining strategies
- Annotation-efficient deep learning
- Integrated classification/localization/segmentation frameworks
- 40+ US patents (50+ pending)
Major publications demonstrate leadership in self-supervised learning for chest radiography, pulmonary embolism detection, and medical AI explainability.
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