Search results
Suchi Saria is a John C. Malone Associate Professor and the director of the Machine Learning and Healthcare Lab at Johns Hopkins University. She works on developing artificial intelligence and statistical machine learning techniques for healthcare applications, such as diagnosis, treatment planning, and policy.
- Suchi Saria - Johns Hopkins Whiting School of Engineering
Suchi Saria is the John C. Malone Associate Professor of...
- Suchi Saria
Bio: Suchi Saria, PhD, holds the John C. Malone endowed...
- Suchi Saria | Johns Hopkins | Bloomberg School of Public Health
Research Interests. Big data analytics, machine learning,...
- Suchi Saria - Johns Hopkins Whiting School of Engineering
Suchi Saria is a machine learning expert who applies data science to healthcare problems. She directs the Machine Learning and Healthcare Lab and the Malone Center for Engineering in Healthcare at Johns Hopkins.
- 4.1B
- John C. Malone Associate Professor
- mailto:ssaria1@jhu.edu
Suchi Saria is an Associate Professor of Machine Learning and Healthcare at Johns Hopkins University, where she uses big data to improve patient outcomes. She is a World Economic Forum Young Global Leader. From 2022 to 2023, she was an investment partner at AIX Ventures.
Dr. Suchi Saria. John C. Malone Endowed Chair; Computer Science, Statistics, Medicine, Health Policy, Johns Hopkins. Verified email at cs.jhu.edu - Homepage. AI Health AI Machine Learning...
Suchi Saria is a leading researcher and entrepreneur in machine learning and healthcare. She is the John C. Malone endowed chair and the founder of Bayesian Health, a company that uses AI to improve patient care.
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.
Suchi Saria is a faculty member of the Bloomberg School of Public Health and the Whiting School of Engineering. Her research interests include big data analytics, machine learning, informatics, patient safety and quality, multimorbidity, mhealth, predictive modeling, and ICU informatics.
