Profiles

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.

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.

Haziq Jamil is a Research Specialist at the KAUST, currently on leave from his position as Assistant Professor in Statistics at Universiti Brunei Darussalam (UBD). He obtained his Ph.D. and M.S. in Statistics from the London School of Economics and Political Science (LSE), and his B.S. from Warwick University. At KAUST, he works with Prof. Håvard Rue in the BAYESCOMP group, tackling the computational challenges of Bayesian inference for modern psychometric applications of latent variable modelling.

Haziq's research focuses on statistical theory, methods and computation, with a special inclination towards social science applications.  He is passionate about bringing data and technology to the forefront of our daily interaction with the world. Using the R programming language, he builds statistical models for data analysis in order to gain insights, make predictions, and aid decision-making. He is frequently engaged in cross-disciplinary research collaborations and statistical consultations.

Janet van Niekerk is a Research Scientist in the Bayesian Computational Statistics and Modeling group. She works on Bayesian methods including prior construction and computational framework development for various applications, with a focus on Biostatistics.

Efficient Bayesian methods for practical implementation, statistics for medical applications, complex survival analysis, INLA.

Lisa Gaedke-Merzhäuser is a Postdoctoral Fellow in the BayesComp group at KAUST, led by Prof. Håvard Rue. She holds a PhD in Computational Science from Università della Svizzera italiana (USI) in Lugano, Switzerland. Her research interests lie in fusing statistical learning techniques with methods from high-performance computing. She has been developing INLA_DIST, a distributed memory GPU-accelerated version of INLA for large-scale spatio-temporal models.

Combining statistical learning techniques with methods from high-performance computing, large-scale Bayesian modeling, computationally efficient methods for INLA.

Bayesian and computational Statistics.

Eman Kabbas is a Saudi researcher specializing in Bayesian statistics and modeling. She earned her Bachelor’s degree in Mathematics from Imam Abdulrahman bin Faisal University, then continued her studies in the United States through the King Abdullah Scholarship Program, obtaining a Master’s degree in Applied Mathematics from the University of North Carolina. Supported by scholarships from KAUST and the Royal Commission of Jubail and Yanbu, Eman is currently a PhD student in Applied Mathematics and Computational Science (AMCS) at King Abdullah University of Science and Technology (KAUST), supervised by Professor Håvard Rue. Beyond her research, Eman is a Mathematics and Statistics faculty member at Jubail Industrial College under the Royal Commission of Jubail and Yanbu, and co-founder of Sorat Alardh, a startup advancing environmental monitoring and climate analytics. She envisions combining theory and real-world application by transforming scientific research into practical tools that enhance environmental resilience and data-driven innovation in Saudi Arabia. Eman enjoys reading, learning new languages, playing the piano, and exploring strategic games like chess.

Eman Kabbas's research interests focus on developing and applying spline models in non-parametric regression. She addresses the limitations of splines in prediction tasks with insufficient data by proposing a spline model suitable for both regular and irregular observations, leverages Bayesian techniques to ensure efficient modeling and reliable predictions.

His research interest is mainly in Bayesian and computational Statistics, currently working on Directional Statistics and applications with R-INLA. He is also interested in Deep/Machine Learning algorithms.

Małgorzata Forystek is a Statistics Master's student at the Bayesian Computational Statistics & Modeling research group  (BAYESCOMP) under the supervision of Professor Håvard Rue. She received her B.Sc. degree in Applied Mathematics from AGH University of Science and Technology in Kraków, Poland, in 2023.

Her research interest is mainly in Bayesian and computational Statistics and Data Science.

Hanan Alahmadi is a Ph.D. candidate in the Statistics program (CEMSE) at King Abdullah University of Science and Technology (KAUST), specializing in spatial methods for health surveillance in Saudi Arabia, with a focus on data integration and cluster detection under the supervision of Professor Paula Moraga. Her research combines satellite and health data to monitor disease and environmental risks and to develop GIS platforms that support data-driven decision-making. She holds a master’s degree in statistics from KAUST, where she was supervised by Professor Håvard Rue. Hanan is also a lecturer at King Saud University and the founder of Sorat Alardh, a space-tech startup that harnesses Earth observation data for environmental and health applications. Her work has been recognized with several honors, including a grant from the Communications, Space & Technology Commission (CST) and her selection as a finalist in the Falling Walls competition.

• Geospatial data analysis and health surveillance
• Spatio-temporal disease data
• Statistics and spatial epidemiology
• Geospatial modeling
• Disease mapping