Peter Mueller received his Ph.D. in statistics from Purdue University. He is a professor of mathematics with an appointment as core faculty of the Division of Statistics and Scientific Computation. He is a member of the ICES Center for Numerical Analysis. Mueller has authored more than 120 scientific and technical publications, and has served on the editorial board of three scientific journals and technical series.

His research accomplishments include the development of novel probability models for non-parametric Bayesian inference, principled Bayesian multiplicity adjustments, simulation-based approaches to Bayesian decision problems, and innovative Bayesian clinical trial designs.

Mueller’s areas of expertise include the development and analysis of simulation-based methods for Bayesian inference, including posterior inference and design, and applications in biostatistics and bioinformatics.