David Ouyang

David Ouyang

Research Scientist and Cardiologist, Kaiser Permanente Northern California, Division of Research
Assistant Professor, Cedars-Sinai Medical Center
david.ouyang@kp.org
[CV]

About

I am a cardiologist and researcher in the Santa Clara Homestead Medical Center Department of Cardiology and Division of Research at Kaiser Permanente Northern California. Our group works on applications of deep learning, computer vision, and the statistical analysis of large datasets within cardiovascular medicine. We focus on development (see section 'Precision Phenotyping'), understanding (see section 'Interpretable Medical AI'), and deployment of AI (see section 'AI Clinical Trials'). Our work has been published in Nature, Nature Medicine, NEJM AI, Circulation, JAMA Cardiology, EHJ, 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. As an echocardiographer, I apply deep learning for precision phenotyping in cardiac ultrasound and the deployment and clinicial trials of AI models. We are interested in all forms of cardiovascular data, including ECG, MRI, radiological imaging, and particicularly interested in novel insights from pre-existing data.

Research

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!

The best part of the job are the poeple I get work with. I have the good fortune of working with a great group of motivated, talented, and creative individuals from a wide range of backgrounds.

Members of the lab include:

  • Kai Christensen, Data Scientist
  • Milos Vukadinovic, UCLA Bioengineering PhD Student
  • Yuki Sahashi, Postdoctoral Fellow, Electrophysiologist
  • Justin Rhee, Brown University Medical Student
  • Victoria Yuan, UCLA Medical Student, Sarnoff Fellow
  • Meenal Rawlani, Data Scientist
  • Christina Binder-Rodriguez, Postdoctoral Fellow, Cardiologist
  • David Choi, Data Scientist
  • Rishi Truvedi, Cardiology Fellow

  • Alumni of the lab include:
  • Yu Sun, Assistant Professor, ECE, Johns Hopkins University
  • Grant Duffy, Data Scientist, Meta
  • I-Min Chiu, Data Scientist, Apple
  • Ting Qi, Software Engineer, Amazon
  • John Theurer, Software Engineer, Zither Labs
  • Amey Vrudhula, Internal Medicine Resident, Stanford
  • Gauri Renjith, Undergraduate, UCSD
  • Ishan Jain, Undergraduate, UCSB


  • Select Publications

    Precision Phenotyping


    AI Clinical Trials


    Foundation Models in Cardiovascular Medicine


    Interpreting Medical AI

    AI Echocardiography


    Healthcare Data Science


    Gender Disparities in Medicine

    A complete list of publications is available at Google Scholar