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Offline Reinforcement Learning for Hospital Patients When Every Patient is Different
Barbara Engelhardt

Tue Dec 14 04:07 PM -- 04:37 PM (PST) @ None

Author Information

Barbara Engelhardt (Princeton University)

Barbara E. Engelhardt is an associate professor in the Princeton Computer Science Department, on leave in 2019-2020 working as a principal scientist at Genomics Plc. Previously, she was an assistant professor at Duke University in Biostatistics and Bioinformatics and Statistical Sciences. She graduated from Stanford University and received her Ph.D. from the University of California, Berkeley, advised by Professor Michael Jordan. She did postdoctoral research at the University of Chicago, working with Professor Matthew Stephens. Interspersed among her academic experiences, she spent two years working at the Jet Propulsion Laboratory, a summer at Google Research, and a year at 23andMe, a DNA ancestry service. Professor Engelhardt received an NSF Graduate Research Fellowship, the Google Anita Borg Memorial Scholarship, and the Walter M. Fitch Prize from the Society for Molecular Biology and Evolution. As a faculty member, she received the NIH NHGRI K99/R00 Pathway to Independence Award, a Sloan Faculty Fellowship, and an NSF CAREER Award. Professor Engelhardt’s research interests involve developing statistical models and methods for the analysis of high-dimensional biomedical data, with a goal of understanding the underlying biological mechanisms and dynamics of complex phenotypes and human disease.

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