Darsy Darssan

Model-based disease mapping

In public health and epidemiology, understanding population-based human diseases on counts of observed cases at different residential areas with relevant characteristics such as age distribution, socioeconomic status, and environmental exposure is essential to provide better patient care and support. Such understanding involves estimating the disease risk in a small geographic area on a spatial domain of interest. Often too low observed cases in some small geographical areas will provide unreliable disease risk estimation. Unreliable estimates raise the question of whether the underlying disease risk of a geographical location is much higher or lower than the rest. This project will answer the question above through rigorous statistical modelling. The models will use the information from the neighbouring observations at various dimensions to better predict disease risk. The underlying philosophy is known as the first law of geostatistics – “everything is related to everything else, but near things are more related”.

For this research, based on individual research interests, the potential future PhD student can choose a data set from Australian children, overall health survey, women’s health, birth cohort, kidney disease, the study of health and aging, and large-scale biomedical databases. The datasets mentioned above are available for research, but some will need permission to access them. Based on the individual student interest in a particular disease and dataset, we will submit an expression of interest to the data custodians.

As a principal advisor, I provide many benefits to new PhD students. I am readily available to listen more, care more, closely observe student progress and act quickly as necessary. The advisory team will also have a professor-level co-advisor who will bring disease-specific knowledge to the research. Once established, possibly from the second year of the candidature, the student will have the opportunity to lead the project.

Potential future PhD students will need to contact me via email, attend a meeting, write a proposal, and apply to the subsequent UQGSS scholarship round.

Experiments in higher education

You will design and conduct a controlled trial in undergraduate and postgraduate teaching. High interest in the design of experiments, survey design, psychometrics and innovative higher education is essential.

As a principal advisor, I provide many benefits to new PhD students. I am readily available to listen more, care more, closely observe student progress and act quickly as necessary. The advisory team will also have a professor-level co-advisor who will bring expertise in higher education research. Once established, possibly from the second year of the candidature, you will have the opportunity to lead the project.

Potential future PhD students will need to contact me via email, attend a meeting, write a proposal, and apply to the subsequent UQGSS scholarship round.