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Filippo Ascolani is an Assistant Professor in the Department of Statistical Science at Duke University. His research interests primarily focus on developing Bayesian inference techniques and modeling complex data structures. Ascolani has contributed to various journals, with notable works including studies on nonparametric inference for dynamic populations and the use of Gibbs samplers in Bayesian hierarchical models. He obtained his Ph.D. from Bocconi University in 2024 and holds a Master's degree from the University of Turin, which he completed in 2019. His ongoing research aims to enhance methods for nonnegative borrowing information in Bayesian statistics, seeking to improve empirical performance in statistical modeling. Ascolani is actively involved in disseminating his findings through publications and presentations, reflecting his commitment to advancing the field of statistical science.
Department of Biomedical Engineering (MS program)