Dr. Matt Moores is a Lecturer in Statistical Science at the University of Wollongong (UOW), affiliated with the School of Mathematics and Applied Statistics within the Faculty of Engineering and Information Sciences. He joined UOW in 2018 and holds a Docent title in Computational Statistics from LUT University (2021) and is an Elected Member of the International Statistical Institute (2022). He leads research in Bayesian computation, uncertainty quantification, and spatial statistics, with applications in energy infrastructure, environmental modeling, and spectroscopy. His academic roles include Academic Program Director for the Bachelor of Data Science & Analytics and Subject Coordinator for courses such as DSAA301 and MATH205. He co-leads a 2023 Learning & Teaching Innovation Grant focusing on work-integrated learning (WIL) and serves as an Associate Editor for Statistics & Computing . Moores is a Chief Investigator in the ARC Research Hub for Transforming Energy Infrastructure (TIDE), contributing to digital engineering advancements. Research interests span Bayesian inverse problems in oceanography, combining neural networks with Bayesian methods, sequential Monte Carlo, and approximate Bayesian computation (ABC). His publications reflect expertise in Gaussian processes, spatial statistics, and computational algorithms for intractable likelihoods. Awards include the 2023 L&TIG and recognition for contributions to statistical methodology. Teaching and supervision focus on integrating practical industry experiences with theoretical foundations, supported by grants advancing pedagogical innovation. Collaborations span academia and industry, emphasizing interdisciplinary problem-solving in energy, environment, and data science.










