About Me

I am a scientist and an innately curious person, driven to help build a sustainable world by providing insight into the physical and socio-economic environments in which we live. Throughout my career I have done so by fusing together numerical simulations and real world data. 

I have had the pleasure to work with many brilliant researchers at multiple institutions, and across varied fields including turbulence, climate modelling, data assimilation and machine learning. I completed a PhD with the University of Melbourne and the Université de Poitiers on fluid dynamical stability and model reduction of aerospace flows. I then undertook post-doctoral research with the CSIRO Oceans and Atmosphere division and the Monash University Laboratory for Turbulence Research in Aerospace and Combustion, on the numerical simulation and stochastic parameterisation of atmospheric, oceanic and boundary layer turbulence. I then held an industrial research position at a hedge fund developing trading algorithms on the basis of macroeconomic themes and market conditions. I then rejoined CSIRO, to undertake research on the data assimilation and stochastic modelling methods for improved climate state / parameter estimation and forecasting.

My most recent research involves the use of machine learning to quantify the influence of climate variability and change on financial markets, health indicators, social unrest and conflict. The transcript of a talk I gave at a careers event about my somewhat unconventional journey can be found here.