Suchi Saria is the Founder and CEO of Bayesian Health, the John C. Malone Associate Professor of computer science, statistics, and health policy, and the Director of the Machine Learning and Healthcare Lab at Johns Hopkins University. She has published over 50 peer-reviewed articles with over 3000 citations and was recently described as “the future of 21st century medicine” by The Sloan Foundation. Her research has pioneered the development of next-generation diagnostic and treatment planning tools that use statistical machine learning methods to individualize care.
At Bayesian Health, Dr. Saria is leading the charge to unleash the full power of data to improve healthcare, unburdening caregivers and empowering them to save lives. Backed by 21 patents and peer-reviewed publications in leading technical and clinical journals, Bayesian leverages best-in-class machine learning and behavior change management expertise to help health organizations unlock improved patient care outcomes at scale by providing real-time precise, patient-specific, and actionable insights in the EMR.
Dr. Saria’s work has received recognition in numerous forms including best paper awards at machine learning, informatics, and medical venues, a Rambus Fellowship (2004-2010), an NSF Computing Innovation Fellowship (2011), selection by IEEE Intelligent Systems to Artificial Intelligence’s “10 to Watch” (2015), the DARPA Young Faculty Award (2016), MIT Technology Review’s ‘35 Innovators under 35’ (2017), the prestigious Sloan Research Fellowship (2018), and the World Economic Forum Young Global Leader (2018). In sepsis, a life-threatening condition, her work first demonstrated the use of machine learning to integrate diverse signals to make early detection possible (Science Trans. Med. 2015). In Parkinson's, her work showed a first demonstration of using readily-available sensors to easily track and measure symptom severity at home, which can serve to optimize treatment management (JAMA Neurology 2018).
Dr. Saria has traveled worldwide to conduct lectures and keynotes and most recently was an invited speaker at TEDMED 2020. In the past, she has given invited keynotes at several prestigious meetings including at The Royal Society, TEDxBoston, the International Conference in Health Policy and Statistics (ICHPS), the National Academy of Medicine (NAM) Annual Meeting, the Montreal AI Symposium, the Uncertainty in Artificial Intelligence (UAI) meeting, the International Conference on Machine Learning (ICML), International Conference on Learning Representations (ICLR), and the Oxford Statistics Distinguished Seminar Series, to name a few.
Dr. Saria earned her M.Sc. and Ph.D. from Stanford University working with Professor Daphne Koller. She visited Harvard University as an NSF Computing Innovation Fellow and joined the Johns Hopkins faculty in 2012. Currently, Dr. Saria is serving as an advisor to the FDA on AI/machine learning.