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Dylan Fitzpatrick joined the Urban Labs Crime Lab as a Research Director and DSI as a postdoctoral scholar in summer 2020. He is currently a PhD candidate in Machine Learning and Public Policy at Carnegie Mellon University, where he is a member of the Event and Pattern Detection Lab. His research is in development of new ML methods that leverage large spatiotemporal data sets to improve public health, safety, and security. For his dissertation, Dylan has designed novel algorithms for disease outbreak detection and crime forecasting. Most recently, Dylan has focused on patient-level opioid use monitoring, developing a semi-supervised approach for evaluating risk of opioid misuse in settings with few training labels. Dylan was a Researcher at the 2019 NASA Frontier Development Lab, where his research team developed generalizable, multi-basin models of flood susceptibility designed to overcome limitations of physics-based hydraulic and hydrologic models. Dylan earned a BA in Economics from Middlebury College and an MS in Computer Science from Carnegie Mellon University. Dylan’s PhD advisor is Daniel B. Neill, Associate Professor of Computer Science and Public Service and Director of the Machine Learning for Good Laboratory at New York University.