About me

I am an environmental systems modeller and research software developer with the Institute for Water Futures at the Australian National University. I was conferred my doctorate in Integrated Environmental Modelling in July 2021. My research primarily focuses on the methods and approaches for the development of integrated multi-system models for use in exploring socio-economic, policy and management futures. I also hold two masters degrees; a Master of Technology and a Master of Environment (Research) in Natural Resource Management.

A copy of my doctoral thesis can be accessed via ANU’s open research repository.

My work involves development and application of models to represent socio-environmental systems that span surface water, groundwater, policy, ecological and social systems, as well as their interactions. I have also contributed to several open-source modelling projects related to environmental research including sensitivity analysis and bibliometric analysis.

I work principally in Python and Julia, although I also have experience with R, Fortran, C and MATLAB.

I am an active contributor to the SALib Python package.

I have developed code and packages to simplify the statistical analysis of spatial data.

I assisted in the independent reviews of the Paddock to Reef Modelling Program and the Source Murray Model

I have run workshops for students and staff on Integrated Modelling and exploratory interactive visualization, including a workshop run at Hohai University, Nanjing China.

I have an interest in linguistics and Natural Language Processing and have applied these in conducting a bibliometric review of tools and methods for uncertainty and sensitivity analysis. For this purpose I developed the Wosis package which supports interaction with the Web of Science web API, data analysis processes including visualization.

I also enjoy working and helping others improve computational performance of their models. Some examples are:

Improvements to a spatial flood damage model to increase usability and reduce runtime in conjunction with a PhD candidate from Fondazione Eni Enrico Mattei (Italy). The model estimates the amount of damage to physical assets, and impact on the economy (in terms of GDP) and population. Runtime was reduced from a reported 20mins to around 5 minutes.
Similarly, I aided a fellow student optimise an ecological response model developed at the CSIRO, including porting some code from Python to Cython. Runtime was reduced from a reported 5 hours to 10-15 minutes.