Research focus
About the research
How can patterns in complex data help researchers anticipate events and make better decisions?
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The group works on applied machine learning, data science and urban analytics. Research interests include recommender systems, computational epidemiology and visual analytics. Documented projects examine optimization of school boundaries and tools that support interactive redistricting, while related work investigates information extraction from scholarly literature. Participation in pandemic research connects data science with models of disease spread, bringing computational methods to problems that involve both technical predictions and real-world consequences.
Selected publications
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People & alumni
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