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Daniel B. Neill is an Associate Professor of Information Systems in the Heinz College at Carnegie Mellon University, where he has been the H.J. Heinz III College Dean's Career Development Professor. He also hold courtesy appointments in the Machine Learning Department and Robotics Institute in CMU's School of Computer Science, and an adjunct appointment in the Department of Biomedical Informatics at the University of Pittsburgh. He received his Ph.D. in Computer Science from CMU in 2006. Before that, he received his B.S.E. from Duke University, M.Phil. from Cambridge University, and M.S. from Carnegie Mellon. At CMU, he directs the Event and Pattern Detection Laboratory, and co-directs the Healthcare Information Technology thrust of Heinz College's iLab. His research is focused on novel statistical and computational methods for discovery of emerging events and other relevant patterns in complex and massive datasets, applied to real-world policy problems ranging from medicine and public health to law enforcement and security. Application areas include disease surveillance (e.g., using electronically available public health data such as hospital visits and medication sales to automatically identify and characterize emerging outbreaks), law enforcement (e.g., detection and prediction of crime patterns using offense reports and 911 calls), health care (e.g., detecting anomalous patterns of care which significantly impact patient outcomes), and urban analytics (e.g., helping city governments to predict and proactively respond to emerging patterns of citizen needs).
Professor Neill may be contacted at: email@example.com