My research focuses on the development of modern statistical methodology for inferential and predictive applications. This includes methodological research in combining computationally expensive simulation models with observational data and research in non-parametric Bayesian regression tree models for "big data'.'  My work is generally developed within the Bayesian paradigm and is often motivated by environmental, environmental health, climate or engineering applications.  You can read more about my work at my website.

Matthew Pratola joined the statistics faculty in 2013. He is currently an Associate Editor of Technometrics where he has spearheaded the special issue on Industry 4.0, and has served the profession through various roles in the Section on Physical and Engineering Sciences (SPES) of the American Statistical Association (ASA).