​Professor Rue's research interests lie in computational Bayesian statistics and Bayesian methodology such as priors, sensitivity and robustness. His main body of research is built around the R-INLA project (www.r-inla.org), which aims to provide a practical tool for approximate Bayesian analysis of latent Gaussian models, often at extreme data scales. This project also includes efforts to use stochastic partial differential equations to represent Gaussian fields, for the use in spatial statistics.