Haavard Rue
- Program Chair, Statistics
- Professor, Statistics
- Principal Investigator, Bayesian Computational Statistics and Modeling
Professor Haavard Rue is an internationally recognized expert in Bayesian computational statistics.
Biography
Professor Rue earned his Ph.D. in 1993 from the Norwegian University of Science and Technology. He began his academic career at the same institution in 1994 and was promoted to full professor in 1997. He has also held adjunct positions at the Norwegian Computing Center and the Arctic University of Norway. Rue is an elected member of the Norwegian Academy of Science and Letters, the Royal Norwegian Society of Science and Letters, the Norwegian Academy of Technological Sciences and the International Statistical Institute.
Upon joining KAUST in 2017, Rue established the Bayesian Computational Statistics & Modeling research group. The group develops efficient Bayesian inference schemes and tools to improve Bayesian inference and modeling using latent Gaussian models. He received the Guy Medal in Silver from the Royal Statistical Society in 2021 for his groundbreaking work in this area.
Research Interests
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—a project aimed at providing a practical way to analyze latent Gaussian models at extreme data scales using approximate Bayesian analysis. The work also includes efforts to model Gaussian fields with stochastic partial differential equations, which are applied to spatial statistics.
Awards and Distinctions
- Guy Medal in Silver, Royal Statistical Society, 2021
- Member of the Norwegian Academy of Science and Letters , Norwegian Academy of Science and Letters , 2013
- Member of the Norwegian Academy of Technological Sciences, Norwegian Academy of Technological Sciences, 2015
- Member of the Royal Norwegian Society of Science and Letters, Royal Norwegian Society of Science and Letters, 2007
- Elected member of the International Statistical Institute (ISI), International Statistical Institute (ISI), 2015
- Bahadur Memorial Lecture, Univ of Chicago, 2018
Quote
Do one thing, and do it well
Questions and Answers
Why KAUST?
What attracted me most to KAUST, was the strong focus on research and the ability to create and maintain a research group, additional to the quality of the faculty, students and life on campus in general.
Why Bayesian computational statistics?
I did my MSc degree in Marine Hydrodynamics but switched to the field of Statistics for the Ph.D. My research activity has always been very computational in style, which goes well with my interest in the field of computing in general. The current research topic, which is about all the aspects of latent Gaussian models, is huge and the perfect blend of statistics, statistical modeling, and computing. It is a highly relevant area where what we do have an impact on how statistics is done.