I am Associate Professor with the School of Mathematics and Statistics at the University of New South Wales and Honorary Associate Professor with the School of Mathematics and Applied Statistics at the University of Wollongong. My research interests lie in spatio-temporal modelling and the tools that enable it. During my PhD at the University of Sheffield, (2008-2011), I focused on variational Bayesian methods for approximate inference of spatio-temporal log-Gaussian Cox process models. The methods I developed were successfully applied in conflict modelling. Following my PhD and a brief postdoc at the University of Edinburgh, I joined the University of Bristol (2012-2014). In my work there I used well-established approximations to spatio-temporal multivariate processes to assess the Antarctic contribution to sea-level rise. The project involved fusing multiple data products (from diverse satellites and research groups) through the use of a large-scale spatio-temporal model. Work involved the use of the message-passing interface on a high-performance computer, parallel Gibbs sampling methods, and sparse linear algebra methods.

In my early years at Wollongong (2014-2017), my work focused on developing nonstationary, non-Gaussian, multivariate spatial models and software for spatial modelling. In 2018, I took up a Discovery Early Career Research Award (DECRA) from the Australian Research Council (ARC), to investigate deep learning methods in spatio-temporal statistics, which is my current research focus. As of 2023 I am Chief Investigator on three other projects: a Discovery Project on estimating the sources and sinks of greenhouse gases; an ARC Special Research Initiative on Securing Antartica's Environmental Future (SAEF); and an ARC Industrial Transformation Research Hub on Transforming Energy Infrastructure through Digital Engineering (TIDE), for which I am also Data Science Coordinator. I joined the University of New South Wales in 2026.