Suchi Saria is the John C. Malone Associate Professor of computer science at the Whiting School of Engineering and of statistics and health policy at the Bloomberg School of Public Health. She directs \u00a0the Machine Learning and Healthcare Lab and is the founding research director of the Malone Center for Engineering in Healthcare.<\/p>\n
Saria\u2019s goal is to use sophisticated computer science and the deluge of data available in health care and other settings to individualize patient care and to save lives. Her pioneering work centers on enabling new classes of diagnostic and treatment planning tools for health care\u2014tools that use statistical machine-learning techniques to tease out subtle information from \u201cmessy\u201d observational datasets, and provide reliable inferences for individualizing care decisions.<\/p>\n
Saria\u2019s work provides an entry point into a future in which the data collected from a large number of patients may reliably inform physicians about the best treatment plans for individual patients. For instance, algorithms that she created are being used today in hospitals to predict with startling accuracy which patients will succumb to deadly sepsis (a condition that annually kills more people than breast and prostate cancer combined)\u2014 work that led to her being named one of\u00a0Popular Science<\/em>\u00a0magazine\u2019s \u201cBrilliant 10\u201d (2016); one of MIT\u2019s \u201c35 Innovators Under 35\u201d (2017); and a member of the World Economic Forum\u2019s Young Global Leaders (2018).<\/p>\n For another project, Saria and her team created an app that allows patients with Parkinson\u2019s disease to track their symptoms on their personal smartphones. Rather than relying on the subjective observations of a medical staff member in a clinical setting, giving patients the ability to report on their symptoms at any time of day, in a clinic or within their own home, can better capture the day-to-day variability of Parkinson\u2019s symptoms and provide doctors with a clearer picture of their patients\u2019 verall health and how well their medications are working.<\/p>\n This work is considered groundbreaking because though other mobile studies also collect data \u201cin the wild,\u201d few have found ways to validate it clinically because that process requires the expensive and laborious collection of benchmark (also called \u201cgold standard\u201d) data at home. Saria solved this issue by developing a machine learning framework that uses \u201cweak supervision\u201d\u2014information that is inexpensive and readily collected at home\u2014to train algorithms for progression monitoring from mobile data.<\/p>\n Saria\u2019s work has received recognition 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\u2019s \u201c10 to Watch\u201d (2015);; the DARPA Young Faculty Award (2016);; and the Sloan Research Fellowship (2018).<\/p>\n In 2017, Saria\u2019s work was among four research contributions presented by France C\u00f3rdova, Director of the National Science Foundation, to the U.S. House of Representatives\u201d Commerce, Justice Science Appropriations Committee.<\/p>\n She was invited to join the National Academy of Engineering\u2019s Frontiers of Engineering program in 2017 and, in 2018, to join the National Academy of Medicine\u2019s program for Emerging Leaders in Health and Medicine. Saria came to Johns Hopkins in 2012. Prior to that, she received her PhD from Stanford University working with Daphne Koller.<\/p>\n","protected":false},"excerpt":{"rendered":" Suchi Saria is the John C. Malone Associate Professor of computer science at the Whiting School of Engineering and of statistics and health policy at the Bloomberg School of Public Health. She directs \u00a0the Machine Learning and Healthcare Lab and is the founding research director of the Malone Center for Engineering in Healthcare. Saria\u2019s goal<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[56],"tags":[],"class_list":["post-1573","post","type-post","status-publish","format-standard","hentry","category-sme-spotlight"],"acf":[],"yoast_head":"\n