Refreshments are available starting at 10:30 a.m. The seminar will begin at 10:45 a.m.
Abstract
The use of AI in improving medical decision-making is one of the most promising avenues for impact. However, turning these ideas into commonly used tools has been significantly harder and slower than predicted. Suchi Saria’s research has focused on closing fundamental technical gaps related to the development and robust translation of AI-based medical tools from messy, multimodal observational datasets. Her industry experience has given her a firsthand view into hurdles that must be tackled for scaling these solutions in the real world. In 2022, her team published three manuscripts featured on the cover of Nature Medicine that shared results from one of the largest real-world evaluations of a medical AI tool to date; these studies were also the first to show the impact of AI on saving lives. Based on these results, her team achieved FDA Breakthrough status. This talk will give an overview on what it takes to go from an idea to a bedside tool. Along the way, Saria will give pointers on new technical ideas and open research problems in AI safety, human-machine teaming, and modeling multimodal temporal data.
Speaker Biography
Suchi Saria holds a John C. Malone endowed chair and is the director of the AI and Health Lab at the Johns Hopkins University, where she is jointly appointed as faculty in the Departments of Computer Science and Health and Policy Management. She is also the founder of Bayesian Health, a clinical AI platform company spun out of Hopkins that augments care teams by bringing together state-of-the-art AI/ML technology combined with responsible AI best practices to dramatically improve quality while saving clinicians’ time. Dr.
Saria’s work in AI over the last two decades has led to foundational advances in the technology, best practices around translation, and policy. She has written several seminal papers in AI/ML around issues of learning robust models, detecting drifts, and monitoring and learning from messy real-world datasets. Her applied research has built on these technical advances to develop novel next-generation diagnostic and treatment planning tools that use AI/ML to individualize care. Her work has been funded by leading organizations including the NSF, DARPA, the FDA, the National Institutes of Health, and the CDC, and she regularly serves as a scientific advisor to leading Fortune 500 companies.
Saria completed her PhD in AI at Stanford University. In 2024, she received an honorary doctorate from Mount Holyoke College. Saria is a Sloan Research Fellow; has been named to IEEE Intelligent Systems’ “AI’s 10 to Watch,” to Modern Healthcare’s Top 25 Innovators, and a World Economic Forum’s Technology Pioneer; and her work was recognized as one of TIME’s Best Inventions of 2023. Saria is on the board of the Coalition of Health AI, the editorial board of the Journal of Machine Learning Research, and serves on the steering committee of the National Academy of Medicine’s Health Care Artificial Intelligence Code of Conduct.