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Stephen Berg is an Assistant Professor of Statistics at Penn State University. He obtained his PhD in Statistics from the University of Wisconsin-Madison in 2020, an MS in Statistics from the same institution in 2017, and a BS in Mathematics from Iowa State University in 2013. His research focuses on developing statistical tools for analyzing spatial and temporal dependencies, particularly in environmental data. Key areas of interest include simulation-based inference, particularly Markov chain Monte Carlo methods, stochastic approximation methods, modeling landscape ecology related to wildlife diseases, and numerical optimization. Berg has contributed to several notable publications, such as work on latent discrete Markov random fields and studies on readmission and mortality rates among Medicare beneficiaries. He joined Penn State as an Assistant Professor in 2020.
Penn State University • University Park, PA, USA
Teaching and researching in the field of Statistics, focusing on spatial and temporal statistical methods.
GRE scores are highly recommended but not strictly required for Applied Linguistics.