It is well known that petrol prices in Australia follow a regular pattern termed Edgeworth cycles by which prices suddenly increase every couple of weeks followed by longer periods of slow decrease. These patterns can be identified in publicly available in publicly available (Queensland) Fuel Pricing data. In this project we will rely on publicly available data and use mathematical modelling and Bayesian inference techniques to identify the type of coordination between retailers which may drive the petrol price cycles.
The University of Queensland
Gurushey (Guru) is a dual degree student at the University of Queensland, specialising in Mathematics (Research/Data Analytics) and Computer Science (Machine Learning). He has a strong interest in the intersection of applied mathematics and explainable ML, particularly in how these fields together can drive advancements in applied maths research. Currently, Guru is working on applying novel modelling techniques to Queensland fuel pricing data to better understand market behaviours and trends.
Throughout his studies, he has developed a diverse toolkit of mathematical and ML techniques, which he aims to apply in research focused on developing models that capture natural and economic trends to gain deeper insights. Guru also works as a Junior Developer in the biotech industry, where he is gaining hands-on experience in industry-level R&D.
Outside his academic and professional pursuits, Guru enjoys travelling, watching and playing football, and exploring diverse cuisines and cultures. He plans to pursue an Honours year in applied mathematics after his bachelor’s degree to keep his options open for a research-focused HDR program.