Serena Yeung

Serena Yeung is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. She is also affiliated with Stanford’s Clinical Excellence Research Center, and serves as an Associate Director of Data Science for the Center for Artificial Intelligence in Medicine & Imaging. Dr. Yeung’s research focuses on computer vision, machine learning, and deep learning, for interpreting diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images. She is also active in teaching and education, and her graduate-course lectures on deep learning in computer vision have been publicly released by Stanford and collectively viewed over a million times online. Prior to her current role at Stanford, Dr. Yeung was a Technology for Equitable and Accessible Medicine (TEAM) Fellow at Harvard University, and she has also served on the National Institute of Health's Advisory Committee to the Director Working Group on Artificial Intelligence.

Filter Courses within "Serena Yeung" (Click to filter)
Fundamentals of Machine Learning for Healthcare (Coursera) Coursera
Stanford University

Fundamentals of Machine Learning for Healthcare (Coursera)

Discover how machine learning is revolutionizing healthcare by enrolling in 'Fundamentals of Machine Learning for Healthcare'. This course provides a solid foundation in applying ML to medicine, equipping you with the knowledge to harness AI's potential for transformative change in patient care. Whether you're a healthcare professional or an aspiring data scientist, this program will help bridge the gap between medical expertise and machine learning principles.

Jun 22nd 2026
5-12 Weeks
AI in Healthcare Capstone (Coursera) Coursera
Stanford University

AI in Healthcare Capstone (Coursera)

Embark on a comprehensive journey through Coursera's 'AI in Healthcare Capstone' course. This capstone project synthesizes all the concepts covered throughout the specialization, guiding you through a patient's healthcare journey from symptom onset to diagnosis using AI-driven analytics. Learn how to leverage EHR and image data to build models that support informed decision-making for risk-stratification.

Jun 22nd 2026
5-12 Weeks
Page 1