Ph.D., Associate Professor, Paul G. Allen School of Computer Science & Engineering, University of Washington
Prof. Su-In Lee is an Associate Professor in the Paul G. Allen School of Computer Science & Engineering. Her research is at the intersection of computational biology and machine learning with a recent emphasis on precision medicine and interpretable machine learning. Her group recently published papers on a broad range of topics, including cancer precision medicine, explainable blood oxygen prediction during surgery, and theoretical machine learning, in Nature Communications, Nature Biomedical Engineering, and Neural Information Processing Systems. She completed her PhD in 2009 at Stanford University with Prof. Daphne Koller. Before joining the UW in 2010, she was a visiting Assistant Professor in the Computational Biology Department at Carnegie Mellon University. She has received the National Science Foundation CAREER Award and been named an American Cancer Society Research Scholar. She has received a number of generous grants from the National Institutes of Health, National Science Foundation, and American Cancer Society.
Session Abstract – PMWC 2019 Silicon Valley
Session Synopsis: AI methods promise to revolutionize the way we approach medicine, by building and training models that make accurate predictions. But the application of AI in actual biomedical contexts comes with distinct challenges. This session features speakers in the forefront of real-life AI applications, who will discuss challenges such as how to reach an interpretable/explainable AI model and how to apply AI in a regulated context.