Bayesian copula modelling of multivariate dependence: getting to grips with data that is far from normal. Copula models are very popular tools that are changing the way analysts deal with information rich data in fields as diverse as marketing, finance and transport studies. This project aims to improve and extend these tools, so that more accurate and reliable models can be employed, resulting in improved evidence-based decision-making.
Flexible Models and Methods for Longitudinal Data. The availability of increasingly large data sets offers the potential to improve understandings of many phenomena. However, without models for these phenomenon and methods to analyse the data generated by them, information contained in such data cannot be extracted. This project aims to advance statistical methods and models for analysing data that are collected on a large number of individuals at many time points. In particular, data collected ....Flexible Models and Methods for Longitudinal Data. The availability of increasingly large data sets offers the potential to improve understandings of many phenomena. However, without models for these phenomenon and methods to analyse the data generated by them, information contained in such data cannot be extracted. This project aims to advance statistical methods and models for analysing data that are collected on a large number of individuals at many time points. In particular, data collected from mobile phone applications will be used to understand the effect that training regimes have on cognitive functioning and how these effects vary with individual characteristics.Read moreRead less
A Bayesian State Space Methodology for Forecasting Stock Market Volatility and Associated Time-varying Risk Premia. Accurate prediction of stock market volatility is critical for effective financial risk management. Along with information on volatility embedded in historical stock market returns, the prices of options written on the underlying stocks also reflect the option market's assessment of future volatility. This project will exploit this dual data source in a completely new way, using it ....A Bayesian State Space Methodology for Forecasting Stock Market Volatility and Associated Time-varying Risk Premia. Accurate prediction of stock market volatility is critical for effective financial risk management. Along with information on volatility embedded in historical stock market returns, the prices of options written on the underlying stocks also reflect the option market's assessment of future volatility. This project will exploit this dual data source in a completely new way, using it to produce forecasts of both volatility itself and the premia factored into asset prices as a result of traders' perceptions of volatility risk. State-of-the-art statistical methods will be used to produce up-dates of the probability of extreme volatility and/or extreme risk aversion, as new market data becomes available each trading day.Read moreRead less
Improved theory and practice in econometric modelling of nonlinear spatial time series. Modern Australia faces many challenges in economic and global climate changes, which require advanced statistical technologies in modeling and forecasting of econometric spatial time series data. This project will provide flexible models and methods that enable practitioners to more accurately measure and manage economic and climatic risks.
Frontiers in Data Science: Analysing Distributions as Data. This project aims to develop the statistical foundations of a new approach to analysing large and complex data, based on building distributional approximations of the data, which can then be analysed by standard statistical methods. The need to analyse very large and complex datasets has become a vital part of everyday life, particularly in the analysis of national problems in public health, environmental pollution, computer network sec ....Frontiers in Data Science: Analysing Distributions as Data. This project aims to develop the statistical foundations of a new approach to analysing large and complex data, based on building distributional approximations of the data, which can then be analysed by standard statistical methods. The need to analyse very large and complex datasets has become a vital part of everyday life, particularly in the analysis of national problems in public health, environmental pollution, computer network security and climate extremes. The project expects to change our way of thinking in how to be smarter about what data we use (and collect) for analysis, rather than relying on brute force analysis of large datasets. The project is expected to transform the knowledge base of the discipline, and the resulting techniques will enable across-the-board research advances for many industries and disciplines.Read moreRead less
Solid-state light sources for bio-imaging and microfluidics. Solid state light sources are the light sources of the 21st century. This project will allow us to find new ways of bioimaging in living organisms applicable to diagnosing disease, and for microfluidic chip based portable instruments for on-site and point-of-care analysis in medical diagnostics, environmental monitoring, and manufacturing processes.
Maximizing solid state Nuclear Magnetic Resonance (NMR) with maximum entropy. Nuclear magnetic resonance is an essential technology for the characterisation of important industrial and biomedical molecules, molecular chains and complexes. This project aims to considerably expand the fundamental capability of experimental techniques for the study of materials in the solid state, in particular for a new class of biological nanoparticle. These advances will have important global implications for re ....Maximizing solid state Nuclear Magnetic Resonance (NMR) with maximum entropy. Nuclear magnetic resonance is an essential technology for the characterisation of important industrial and biomedical molecules, molecular chains and complexes. This project aims to considerably expand the fundamental capability of experimental techniques for the study of materials in the solid state, in particular for a new class of biological nanoparticle. These advances will have important global implications for research into life-saving therapeutic strategies aimed at many pharmaceutical targets embedded in cell membranes, protein misfolding disorders such as Alzheimer's disease and Huntington's disease, as well as development of the next generation of "green" plastics and other advanced polymers.Read moreRead less
Minimally invasive monitoring of sleep for disease management. Sleep, diet and exercise are the three pillars of wellbeing with poor sleep associated with medical issues such as obesity and congestive heart failure. This project will advance sleep analysis by researching new ways of monitoring that are highly accurate and convenient, enabling physicians to improve the monitoring of significant health issues.
New nonparametric statistical methods for imperfectly observed data. Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutriti ....New nonparametric statistical methods for imperfectly observed data. Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutrition, this project aims to develop novel and highly effective statistical methodology for solving contemporary problems involving new types of imperfectly observed data. The expected outcomes will solve frontier problems, where information can only be accessed through sophisticated computer intensive methods.Read moreRead less
Hybrid Imaging System for Breast Cancer Detection. Due to the ever increasing number of breast cancer mortalities in Australia, there is an urgent need for an efficient and reliable diagnostic imaging system. This research utilises a novel method to build an imaging system, which is accurate and reliable in the early detection of tumours. The work of this fellowship will improve quality of life of Australian women and put us at the international forefront of research in medical imaging, enhancin ....Hybrid Imaging System for Breast Cancer Detection. Due to the ever increasing number of breast cancer mortalities in Australia, there is an urgent need for an efficient and reliable diagnostic imaging system. This research utilises a novel method to build an imaging system, which is accurate and reliable in the early detection of tumours. The work of this fellowship will improve quality of life of Australian women and put us at the international forefront of research in medical imaging, enhancing our already significant international presence in the area. The project will potentially lead to valuable intellectual property for commercialisation opportunities besides strengthening key international collaborations.Read moreRead less