معرفی
Sally Paganin is an Assistant Professor of Statistics at The Ohio State University, affiliated with the Department of Statistics within the College of Arts and Sciences. She joined the faculty in 2023 and holds a PhD from the University of Padova (2019). Her research focuses on Bayesian statistics, computational methods, and latent variable modeling, with recent emphasis on genomic data analysis for cancer detection and software development for hierarchical models.
Her expertise spans Bayesian nonparametrics, statistical computing, and domain knowledge integration in modeling frameworks. She actively contributes to the NIMBLE project, an R-based platform for hierarchical modeling, and has developed open-source tools like the compareMCMCs package for MCMC efficiency analysis.
Dr. Paganin serves as an Associate Editor for the software section of The New England Journal of Statistics in Data Science and previously served as Treasurer of j-ISBA (2021–2022). Her work bridges theoretical advancements with practical applications in healthcare and computational statistics.
Key research themes include Bayesian model assessment, latent variable models, and statistical methods for complex data structures. Her publications reflect contributions to MCMC algorithms, semiparametric IRT models, and prior-driven clustering techniques.
