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Debdeep Pati is a Professor in the Department of Statistics at the University of Wisconsin–Madison. His research focuses on the development of machine learning techniques and their applications in high-dimensional data environments. Pati is particularly interested in Bayesian methods, approximate Bayesian computation, and hierarchical modeling, with a strong emphasis on high-dimensional network analysis and Bayesian graphical models. His work includes efficient Bayesian computation and real-time tracking algorithms, as well as novel approaches to modeling point pattern data. Pati's research is also centered around electronic health record data, where he explores complex shapes and data structures. He is committed to advancing statistical methodologies that support fair algorithms in various applications.
Department: Department of Computer Sciences