James Zou

James Zou is an Associate Professor of Biomedical Data Science at Stanford University, with courtesy appointments in Computer Science and Electrical Engineering. His research focuses on advancing machine learning methodologies for healthcare and biomedicine, emphasizing reliability, human compatibility, and statistical rigor. He leads the Stanford AI Lab and is a Chan-Zuckerberg Investigator.

Educated at Harvard (PhD 2014), he has held positions at Microsoft Research and U.C. Berkeley. His work bridges foundational ML theory with clinical applications, such as AI-driven cardiac function assessment (EchoNet-Dynamic), spatial transcriptomics (TISSUE), and oncology trial optimization (Trial Pathfinder).

Research interests include generative AI for biomedical discovery, AI ethics, and scalable healthcare algorithms. His team collaborates with industry and academia to translate innovations into clinical tools. Notable achievements include FDA-cleared EchoNet AI and the BABEL framework for multiomic data integration.

Awards include the Sloan Fellowship, NSF CAREER Award, and multiple grants from Google/Adobe/Amazon. He advises over 20 students and has published 69+ papers in top journals like Nature, Science, and PNAS. Current courses include Foundation Models for Healthcare and Deep Learning in Genomics.