Dr. Serena Yeung Levy

Assistant Professor

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Biography

Serena Yeung-Levy is an Assistant Professor in the Department of Biomedical Data Science, courtesy of Electrical Engineering and Computer Science at Stanford University. Her research primarily focuses on developing artificial intelligence and machine learning algorithms that enhance capabilities in biomedicine and healthcare. She possesses extensive expertise in deep learning and computer vision, having developed algorithms to analyze various types of visual data, including video captures of human behavior and medical images, such as cell microscopy images. Additionally, Dr. Yeung-Levy leads the Medical AI Computer Vision Lab at Stanford and is affiliated with the Stanford Artificial Intelligence Laboratory, Clinical Excellence Research Center, and the Center for Artificial Intelligence in Medicine and Imaging. She has also served as an investigator at the Chan Zuckerberg Biohub and was a member of the NIH Advisory Committee Director's Working Group on Artificial Intelligence. Her academic journey includes a Postdoctoral Fellowship at Harvard University following her Ph.D. from Stanford University in 2018.

Research Interests

Courses

BMDS 281 MED 216 CS 499 CME 390 BMDS 299 CS 390A CS 390B CS 390C BIOE 391 CS 399 CS 199 CS 390D CME 400 CS 192 CS 191 CS 195 CS 191W BIODS 276 CS 286 BIODS 216 BIOD 220 CS 271 BIODS 210 OTOHNS 209

Requirements for Stanford University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:26
Reading
Required:26
Writing
Required:26
Speaking
Required:26
Total
Required:100
GRE General
Verbal
Required:160
Quantitative
Required:165
Analytical Writing
Required:4.5
Overall
Required:4.5
Prerequisites
Bachelor degree from an accredited institution Strong background in mathematics and programming
Application Checklist
  • Statement of Purpose
  • Three letters of recommendation
  • Official transcripts
  • Resume/CV
Specialization Notes

The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.