suinlee AT cs.washington.edu
Prof. Su-In Lee, University of Washington, Seattle
Professor, Paul G. Allen School of Computer Science & Engineering
Adjunct Professor of Genome Sciences (GS), Electrical and Computer Engineering (ECE), and Biomedical Informatics and Medical Education (BIME)
Director, AI Technology for Health (AI4health)
Director, Computational Molecular Biology Program
AI Core Director, NIH Nathan Shock Center of Excellence in Basic Biology of Aging
Associate Director, Resuscitation Engineering Science Unit, UW Medicine
PhD Electrical Engineering, Stanford University, Jan 2009
"Machine learning approaches to understand the genetic basis for complex traits" with Dr. Daphne Koller
MS Electrical Engineering, Stanford University, June 2003
BS Electrical Engineering and Computer Science, KAIST, Feb 2001
"Biologically inspired neural network approach using feature extraction and top-down selective attention for robust optical character recognition" with Prof. Soo-Young Lee
Prof. Su-In Lee is a Paul G. Allen Professor of Computer Science & Engineering at the UW. She completed her PhD in 2009 at Stanford University with Prof. Daphne Koller in the Stanford Artificial Intelligence Laboratory in Computer Science. Before joining the UW in 2010, Lee was a visiting Assistant Professor in the Computational Biology Department at Carnegie Mellon University School of Computer Science. She has received the National Science Foundation CAREER Award and has been named an American Cancer Society Research Scholar. She has received numerous generous grants from the National Institutes of Health (NIH), the National Science Foundation (NSF), and the American Cancer Society.
Prof. Lee's research has conceptually and fundamentally advanced the way AI is integrated with biomedicine by addressing novel, forward-looking, and stimulating scientific questions, enabled by AI advances. While the primary focus of AI applications in biomedicine was on making accurate predictions using machine learning (ML) models, she uniquely focused on why a certain prediction was made by developing novel AI theories, principles, and techniques to improve the interpretability of ML models, which are applicable to a broad spectrum of problems beyond biomedicine. This line of work has led to highly cited seminal publications in the fields of foundational AI, clinical medicine, and computational molecular biology. Her research aims to push the boundaries of both foundational AI and biomedicine, to address new questions, and make novel discoveries from high-throughput molecular data and electronic medical record data.
Prof. Su-In Lee is a Paul G. Allen Professor of Computer Science at the UW. She completed her PhD in 2009 at Stanford University with Prof. Daphne Koller. Before joining the UW in 2010, Prof. Lee was a visiting Assistant Professor in the Computational Biology Department at Carnegie Mellon University School of Computer Science. She has received the National Science Foundation CAREER Award and has been named an American Cancer Society Research Scholar.
Prof. Lee is a leading AI researcher and computational biologist, renowned for her pioneering work in developing AI and ML algorithms to advance biomedical sciences. She is widely recognized as a pioneer in explainable AI (XAI), greatly enhancing ML model interpretability. Her recent contributions to the biomedical fields span two aspects: first, her work on essential XAI tools in biomedicine, including her groundbreaking work on the SHAP framework; and second, her innovative biomedical research across various domains spanning from basic biology to clinical medicine, enabled by XAI advancements.