Suchi Saria

Suchi Saria is an associate professor of computer science at Johns Hopkins University's Whiting School of Engineering, where she holds the John C. Malone endowed chair. Saria has joint appointments in the Departments of Biostatistics and Health Policy and Management at the Bloomberg School of Public Health, as well as in health system informatics at the School of Medicine. She directs the university's Machine Learning and Healthcare Lab and serves as the founding research director of the Malone Center for Engineering in Healthcare. Saria completed her doctorate in artificial intelligence at Stanford University, where she trained under Daphne Koller, and has contributed to the integration of AI and data science in clinical care.

Saria's research focuses on developing diagnostic and treatment planning tools for healthcare that leverage advanced artificial intelligence and machine learning techniques. Her work addresses the challenges of extracting actionable insights from complex observational datasets to support individualized care decisions. Saria has authored several foundational papers in machine learning for healthcare and has delivered more than 300 invited keynotes and talks to organizations such as the National Academy of Medicine, National Academy of Sciences, and the National Institutes of Health. She has advised multiple Fortune 500 companies, and her research has received support from organizations including the National Institutes of Health, Food and Drug Administration, National Science Foundation, Defense Advanced Research Projects Agency, and Centers for Disease Control and Prevention.

A significant aspect of Saria's work is in sepsis detection. She developed an artificial intelligence-powered platform that functions as an early warning system for sepsis, a condition responsible for hundreds of thousands of deaths annually. Her hospital-based tool has demonstrated a reduction in mortality rates. The platform, known as the Targeted Real-Time Early Warning System, or TREWS, received clearance from the U.S. Food and Drug Administration, becoming the first continuous AI monitor authorized to alert clinicians to the risk of a medical emergency that contributes to a substantial portion of hospital deaths. Bayesian Health's system analyzes clinical notes, laboratory results, clinical history, and vital signs to identify patients at risk for adverse medical events.

Saria is the founder of Bayesian Health, a clinical AI platform company that integrates artificial intelligence and machine learning technology with responsible AI practices to improve healthcare quality and efficiency. She co-founded the Coalition for Health AI (CHAI) to promote the development of transparent and credible AI systems in healthcare, collaborating with organizations such as Mayo Clinic, CVS Health, Google, Amazon, Microsoft, and regulatory agencies including the Food and Drug Administration to establish consensus on AI evaluation protocols. Saria also serves on the editorial board of the Journal of Machine Learning Research and on the National Academy of Medicine AI Code of Conduct.

Saria's work has been recognized across science, technology, and public policy. Her honors include MIT Technology Review's "35 Innovators Under 35," the DARPA Young Faculty Award, the Sloan Research Fellowship, the National Academy of Medicine's Emerging Leaders in Health and Medicine, and the World Economic Forum Young Global Leader designation. Her work has been featured in TIME's Best Inventions, and she was named among the world's most influential people in artificial intelligence in TIME100 AI. Saria has been featured by The Atlantic, Smithsonian Magazine, Bloomberg News, the Wall Street Journal, and PBS NOVA, and is a public voice on the role of artificial intelligence in healthcare.