Suchi Saria, an assistant professor in the Department of Computer Science at the Whiting School of Engineering and the Department of Health Policy and Management at the Bloomberg School of Public Health, has been selected to participate in the National Academy of Engineering’s 23rd annual U.S. Frontiers of Engineering (USFOE) symposium. Saria will discuss her research on statistical machine learning and its application to developing data-driven systems for augmenting human decision-making capability for diagnostics and treatment planning.
The event, to be held in East Hartford, Ct. Sept. 25 through 27, brings together nearly 100 of the nation’s outstanding young engineers (under 45 years of age) from academia, industry, and government. The goal: To facilitate cross-disciplinary exchange and promote the transfer of new techniques and approaches across fields in order to sustain and build US innovative capacity. Participants were nominated by fellow engineers or organizations.
Hosted by United Technologies Research Center in East Hartford, Conn., the 2017 USFOE will cover cutting-edge developments in four areas: Mega-Tall Buildings and Other Future Places of Work, Unraveling the Complexity of the Brain, Energy Strategies to Power Our Future, and Machines That Teach Themselves.
“The Frontiers of Engineering program brings together a particularly talented group of young engineers whose early-careers span different technical areas, perspectives and experiences,” says NAE President C. D. Mote, Jr. “But when they come together in this program, their mutual excitement is palpable, and a process of creating long-term benefits to society is often initiated.”
Saria will participate in the Machines That Teach Themselves area with her presentation on teaching machines to spot diseases using electronic health record data. In August 2017, Saria was named to the annual MIT Technology Review list of 35 Innovators Under 35 for her work creating algorithms that hospitals can use to predict the onset of sepsis in patients before doctors can identify it. In 2016, Saria was awarded the DARPA Young Faculty Award for her work on counterfactual reasoning from continuous, noisy data streams. That year, she was also named to Popular Science’s Brilliant 10 list for her work on computer-based approaches to develop diagnoses and treatments tailored to individual patients’ needs.
Saria leads the Machine Learning and Healthcare Lab that devises data-driven strategies and systems to identify patterns within vast quantities of patient information that hospitals compile – including clinical history, vital signs, and laboratory tests.
In addition to her departmental affiliations, Saria also holds appointments in the department of statistics, and biostatistics, and is a core faculty at the Armstrong Institute for Patient Safety and Quality, the Malone Center for Engineering in Healthcare, and the Institute for Computational Medicine. She joined Johns Hopkins in 2012.