David Ouyang

David Ouyang

Staff Physician and Assistant Professor
Smidt Heart Institute and Division of Artificial Intelligence in Medicine
Cedars-Sinai Medical Center
127 S San Vicente Blvd, Los Angeles, CA


I am a cardiologist and researcher in the Department of Cardiology and Division of Artificial Intelligence in Medicine at Cedars-Sinai Medical Center. Our group works on applications of deep learning, computer vision, and the statistical analysis of large datasets within cardiovascular medicine. As an echocardiographer, I apply deep learning for precision phenotyping in cardiac ultrasound and the deployment and clinicial trials of AI models. Our work has been published in Nature, Nature Medicine, JAMA Cardiology, Circulation, NEJM AI, and other scientific venues.

As a physician-scientist and statistician with focus on cardiology and imaging, I majored in statistics at Rice University, obtained my MD at UCSF, and received post-graduate medical education in internal medicine, cardiology, and a postdoc in computer science and biomedical data science at Stanford University.

Our group works on multi-modal datasets, linking EHR, ECG, echo, and MRI data for a broad perspective on cardiovascular disease and have diverse backgrounds (ranging from physics, mechanical engineering, computer science to cardiology, anesthesia, and internal medicine). We are recruiting postdoctoral fellows and research scientists with background in computer vision and NLP (extensive prior experience with Pytorch, TorchVision, Huggingfaces libraries). If you're interested in improving cardiovascular imaging and cardiovascular care, please email me!


Precision Phenotyping of Echocardiography

AI Clinical Trials and Deployment

Deep Phenotyping

Healthcare Data Science

Gender Disparities in Medicine

A complete list of publications is available at Google Scholar