Data Science and AI Colloquium

Jenna Wiens is an Associate Professor of Computer Science and Engineering (CSE) at the University of Michigan in Ann Arbor. She currently heads the MLD3: Machine Learning for Data-Driven Decisions research group. Her primary research interests lie at the intersection of machine learning and healthcare. Dr. Wiens is particularly interested in time-series analysis, transfer/multitask learning, and causal inference.

The overarching goal of her research agenda is to develop the computational methods needed to help organize, process, and transform data into actionable knowledge. For several years now, Prof. Wiens has been focused on developing accurate patient risk stratification approaches that leverage spatiotemporal data, with the ultimate goal of reducing the rate of healthcare-associated infections among patients admitted to hospitals in the US. In addition to her research in the healthcare domain, she also spends a portion of my time developing new data mining techniques for analyzing player tracking data from the NBA.

She received her Ph.D. in 2014 from MIT. At MIT, Dr. Wiens worked with Professor John Guttag in the Computer Science and Artificial Intelligence Lab (CSAIL). Her Ph.D. research focused on developing accurate patient risk-stratification approaches that leverage spatiotemporal patient data, with the ultimate goal of discovering information that can be used to reduce the incidence of healthcare-associated infections. In 2015, she was named Forbes 30 under 30 in Science and Healthcare; she received an NSF CAREER Award in 2016; in 2017 she was named to the MIT Tech Review's list of 35 Innovators Under 35; and most recently she received a Sloan Fellowship in Computer Science.