I am a computational mathematician specialising in the development of statistical methodologies and numerical methods, with applications in scientific computing. My primary areas of application include seismic modelling, medical imaging, and inverse problems related to black hole imaging. My research focuses on developing provably stable and accurate algorithms, ensuring their robustness when applied to these complex scientific challenges.
Currently, my interests lie in generative modelling, Monte Carlo methods, inverse problems, and numerical solutions to partial differential equations (PDEs). In particular, I focus on integrating advanced computational techniques into these domains, with a strong emphasis on the theoretical foundations that guarantee the correctness and stability of the methods in real-world applications.
I was awarded a UKRI scholarship and an Australian Government PhD fellowship to study computational statistics at the University of Oxford, under the supervision of Dr Saif Syed, Professor George Deligiannidis, and Professor Arnaud Doucet.
Before this, I completed my 'COVID MPhil' in computational mathematics and High-Performance Computing (HPC) under the supervision of Dr Kenneth Duru and Professor Markus Hegland, while working as a Research Scientist for the Australian Government in computational mathematics.
Prior to this, I was awarded a research cadetship by the DST Group and worked as a statistical consultant for the Commonwealth Scientific and Industrial Research Organisation (CSIRO). I also spent time as a summer researcher at the Australian Cyber Security Centre (ACSC). I completed my undergraduate studies in pure mathematics at the Australian National University (ANU), graduating with first-class honours under the supervision of Professor Michael Barnsley.
DPhil Statistics
2022-present
Computational Statistics and Machine Learning
Supervision Panel:
MPhil Mathematics
2020-2021
Computational Mathematics and High Performace Computing (HPC)