Published research
Replicating hypergraph disease dynamics with lower-order interactions
Disease spreading models such as the ubiquitous SIS compartmental model and its numerous variants are widely used to understand and predict the behavior of a given epidemic or information diffusion process. A common approach to imbue more realism to the spreading process is to constrain simulations to a network structure, where connected nodes update their disease state based on pairwise interactions along the edges of their local neighborhood.
Education and Qualifications
BSc (Engineering Science and Mathematics & Statistics)
MPE (Mechanical Engineering)
Awards/Honours
2022-2024 – A.F. Pillow Applied Mathematics Top-Up Scholarship
2021-2024 – Robert and Maude Gledden Research Scholarship
2016-2020 – BHP Engineering Scholar