RESEARCH

I've had the opportunity to work on a wide range of research topics over my time in Academia.

†: My main research area.

See below for a selection of my research projects. For a complete listing of my publications (across all domains), see my ORCID page.

ASTRONOMY

DRAGONS

The Dark-ages Reionisation and Galaxy Observables from Numerical Simulations programme

The aim of DRAGONS is to explore the formation end evolution the first galaxies and, in particular, their role in the reionisation of Universe. To do this we developed a new semi-analytic galaxy formation model, Meraxes, which is tightly coupled with a semi-numerical scheme in order to describe the growth and structure of ionised regions. I was the author and lead developer of Meraxes.

HIGHLIGHTED WORKS

Dark-ages reionization and galaxy formation simulation - XXI. Constraining the evolution of the ionizing escape fraction

Dark-ages reionization & galaxy formation simulation VI: The origins and fate of the highest known redshift galaxy

Dark-ages reionization and galaxy formation simulation III: Modelling galaxy formation and the Epoch of Reionization

Find a complete listing of all my astronomy research on my ADS page.

MULTI-DISCIPLINARY

MULTI-DISCIPLINARY

HIGHLIGHTED WORKS

Orthoflow logo

Phylogenomics is a powerful tool for evolutionary species tree inference. However, these analyses be complex, involving many interconnected steps which are often difficult to stitch together and maintain. To address this problem, we developed, a Snakemake based pipeline for end-to-end phylogenomic analysis.

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Phytest logo

In the era of SARS-CoV-2 and proliferation of real-time phylogenetic pipelines, it is more important than ever to ensure that phylogenetic analyses can be easily verified for correctness. Phytest is a tool for automating quality control checks on sequence, tree and metadata files during phylogenetic analyses. It ensures that phylogenetic analyses meet user-defined quality control tests.

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DE-IDENTIFICATION TOOLS FOR GP PATIENT NOTES

In order for digitized general practice patient notes to be used for research, they must first be de-identified. Doing so in an automated and accurate way poses significant challenges. Whilst a number of open-source tools exist, they are typically developed internationally (outside Australia) where variations in conventions, standard record details (such as phone number formating) etc. are different. In this project, we evaluated the performance of four open-source clinical text de-identification tools applied to an Australian setting.

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AGGREGATED AND PREPROCESSED CMIP-CLIMATE DATA

The Sixth Coupled Model Intercomparison Project (CMIP6) comprises a huge collection of simulated climate experiments and is forecast to produce in the order of 20PB of data. In order to utilise the output of these complex simulations for reduced complexity models, the data must be preprocessed and homogenised, requiring significant domain and 'big-data' expertise. In this work we created a dataset of stitched and de-drifted annual, monthly, global, hemispheric and land/ocean mean values derived from a selection of CMIP6 experiments. The resulting dataset is presented via a website with accompanying API, for use by the community.

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