As a Research Associate in the Curtin for Agribusiness Profitability (C4AP) team, I am using my experience in data science and statistical modelling to help farmers and agronomists to take advantage of their big data.
My work focuses on the research needed to underpin the Agri-Analytics Hub and, in particular, understanding intra-paddock variability and how it changes across different crop types. I am also exploring new statistical methods to help farmers apply insights from their "On-Farm Experiments" (OFEs) conducted in small regions of a paddock to larger areas across their farms.
I bring a strong foundation in data-driven problem-solving to this role, with prior experience as a Data Scientist working on grain yield predictions for WA using machine learning. Before transitioning into agricultural research, I completed a PhD in Astrophysics, where I studied the relationship between atomic hydrogen and angular momentum in over 500 nearby galaxies.