Image source: https://www.cell.com/trends/ecology-evolution/abstract/S0169-5347(05)00071-6

My most recent research was on the advancement and application of spatial methods to understand infectious disease epidemiology. I recently developed a localized spatiotemporal random forest model to study COVID-19 dynamics across US counties, capturing how epidemiological, demographic, and environmental drivers shift across regions and periods. I also applied, collaboratively, a spatial Bayesian distributed lag non-linear model to quantify uncertainty and evaluate delayed climatic effects, such as temperature, on Salmonella risk across New South Wales local health districts.

Ecology

Image source: https://www.spatial-ecology.net/

Currently, I am interested in developing and applying spatial methods to better understand patterns of infectious disease ecology, particularly how environmental variability shapes the distribution of hosts, vectors, and pathogens over space and time. I especially want to strengthen approaches that assess the reliability of model-based predictions, including how far insights derived from observed data can be extended across new environmental and temporal contexts.

Biology