BRAG aims to foster frontier research in Bayesian methodology and computation and the application of these approaches to real-world problems.
Director, Professor Kerrie Mengersen has nurtured a group of around thirty postgraduate and postdoctoral researchers on statistical methodology and its applications and has maintained this Bayesian Research and Applications Group (BRAG) group for around fifteen years.
This group is arguably the largest in Bayesian Statistics in Australia under a single researcher. It includes students of different nationalities who have progressed through traditional routes to postgraduate research; those who have come from other professions to train or retrain in statistics, thus expanding their expertise and that of the whole group, and both international and off-campus students. Substantial portions of the cohort are women who are returning to research after career breaks.
Most of the researchers in the BRAG group are funded by collaborative grants and have collaborators in academia, government and industry, thus facilitating the translation of research to practice.
Current areas of methodological focus include:
- complex systems modelling via Bayesian networks,
- hierarchical and mixture models,
- elicitation and representation of expert opinion as prior information and
- spatio-temporal modelling. Current industry-partnered projects are targeted to problems in the fields of environment, health, industry and genetics.
Professor Mengersen’s commitment to training the next generation of researchers is reflected by 30 postgraduate researchers in statistics completed under her direct supervision and over 22 further graduate students completed at Australian and International Universities (Malaysia, France) under her associated supervision. She is currently the primary supervisor for 12 PhD and 2 Research Masters students and associate supervisor for 5 PhD students.
Our research interests are wide-ranging.
Here is a list of our current and past interests.
- ABC
- Adaptive design for ecological monitoring
- Air quality
- Alzheimer’s disease
- Antarctic soils
- Antarctic spatial scale
- Barrow island surveillance
- Bayesian modelling
- Bayesian networks
- Beyond compliance
- Big data analytical
- Big data experimental design
- Biomass
- Biosecurity
- Black cockatoos
- Breast screening
- Cancer atlas
- Cheetahs
- Child health and vehicles
- Choice of university
- Cognition after chemotherapy
- Complex systems
- Coral reef trends
- Dairy sustainability
- Ecological windows
- Elicitation
- Empirical likelihood
- Energy peak demand
- Exponential random graph models
- Exposomics
- Eyes
- Fire ants
- Forest value
- Gene expression analysis
- Genetic epidemiology
- H1N1
- Harbour scorecards
- Health mapping
- Health resource allocation
- Healthy water play
- Healthy waterways
- How many species on a reef
- Immersive environments
- Jaguars
- Lao
- Marine spatial scale
- Meta-analysis
- Methylation
- Mixtures
- Mixtures for hypothesis testing
- Monitoring in hospitals
- Mosquito-borne diseases
- Occupational health
- Orangutans
- Overfitting mixtures
- Parkinson’s disease
- PhD supervision
- Pymcmc
- Radiotherapy
- Rail delays
- Risk stratification
- Sheep and cat scans
- Soil carbon
- Spiralling whitefly
- Vegetation mapping
- Water quality index in Malaysia
- Water quality on the reef
- Wellness
- Which species to save