Bayesian and computational Statistics

Dr. Haziq Jamil Presents Advances in Bayesian Structural Equation Modeling at Psychoco 2026

1 min read ·
Expanding KAUST’s footprint in computational psychometrics, Dr. Haziq Jamil recently shared his latest research on advanced statistical methodologies across two major European academic venues.

BAYESCOMP Group Secures CRG Funding to Revolutionize Latent Variable Modeling

2 min read ·
The KAUST Bayesian Computational Statistics and Modeling (BAYESCOMP) Research Group is pleased to announce the award of a 2025 Competitive Research Grant (CRG) for the project: "Advancing scalable Bayesian methods for latent variable modelling." The project is funded at USD $900,000 for 36 months, with the research program officially commencing in April 2026.

Proper Random Walk Spline Models

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B3 L5 R5209

This dissertation introduces the Proper Random Walk of order 2 (PRW2), a full-rank Gaussian Markov random field that provides a principled alternative to intrinsic random walk (RW2) priors. By construction, RW2 models exhibit heteroscedastic marginal variances, inflated boundary effects, sensitivity to grid design, and unbounded forecast uncertainty—features that undermine the reliability of inference, particularly in sparse-data settings or beyond the observed domain.

MetricGraph

MetricGraph: A Statistical Framework for Modeling Gaussian Fields on Metric Graphs

Eman Kabbas

Deeply passionate about Bayesian statistics, Eman Kabbas is a Math/Statistics Lecturer in the General Studies Department at Jubail Industrial College (JIC). Currently, Eman is a Ph.D. candidate in Applied Mathematics and Computational Sciences at KAUST, specializing in Bayesian statistics under the supervision of Professor Håvard Rue.