Projects for Students
I am looking for good higher degree research students who are interested in any of the following projects. If you are that student, drop me an email.
Project 1
Machine Learning Prediction of Bluebottle's Presence Along the Australian Coast
Many Australians have had a painful bluebottle sting when swimming at the beach, yet little is known
about the bluebottle, and when they will arrive, and if it will be in large swarms or only a few individuals.
Dr Amandine Schaeffer (UNSW)
and I are looking for a masters/honors student to work on a data driven project to investigate
machine learning techniques to address these challenges. Drop us an email if you are a student and
interested in working on this project. For more details, click here.
Project 2
Statistical and Experimental Approach to Estimation of Tyres in a Stockpile
Stockpiling of tyres poses significant health and environmental risks. Storing an excessive number
of tyres raises the likelihood of a fire, which can have severe repercussions.
Stockpiling of tyres above the allowed limit can be caused by a variety of factors, including
market pressures, mishandling, and illegal behavior.
In this joint project with the Environment Protection Authority (EPA) Victoria,
Prof Samuel Muller, Macquarie University,
and I are developing a practically feasible statistical method for a reliable estimation of number of
tyres in stockpile. I am looking for a masters/honors student
to work on lab-based experiments and to model the collected data using statistics.
Project 3
Deep Learning Models for Spatio-temporal Data
Recent advances in remote sensing has resulted in large volumes of data sets easily available.
As a result, assimilating such large dat sets into numerical hydrological models is often a computationally
demanding task.
In this study, Dr Sreekanth Janardhanan (CSIRO)
and I are aiming to study the application of deep learning models
to investigate the relationship between spatio-temporal data sets and hydrological
processes.