Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This projec ....Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This project aims to examine how police and prosecutors decide which cases proceed and why, and how they confer with each other as well as when and how they consult with complainants and their families. This project plans to also develop and test practice tools and principles for police and prosecutors with expected benefits for both them and the families involved.Read moreRead less
Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inf ....Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inferential quantities in an incremental manner. The proposed stochastic algorithms encompass and extend upon a wide variety of current algorithmic frameworks for fitting statistical and machine learning models, and can be used to produce feasible and practical algorithms for complex models, both current and future.
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New Directions in Bayesian Statistics: formulation, computation and application to exemplar challenges. Bayesian statistics is a fundamental statistical and machine learning approach for density estimation, data analysis and inference. However, there remain open questions regarding the formulation of the model, the likelihood and priors, and efficient computation. This project proposes new approaches that address these issues, and applies them to two exemplar challenges: the impact of climate ch ....New Directions in Bayesian Statistics: formulation, computation and application to exemplar challenges. Bayesian statistics is a fundamental statistical and machine learning approach for density estimation, data analysis and inference. However, there remain open questions regarding the formulation of the model, the likelihood and priors, and efficient computation. This project proposes new approaches that address these issues, and applies them to two exemplar challenges: the impact of climate change on the Great Barrier Reef and better understanding neurological diseases related aging, in particular Parkinson's Disease. Read moreRead less
Statistical methods for detection of non-coding RNAs in eukaryote genomes. Understanding how eukaryotic cells work is a major goal of 21st century biology. A crucial step will be to catalogue the functional components of eukaryotic genomes. Australian researchers must be involved in this process at an early stage, in order to maximise commercial opportunities, attract quality researchers and position ourselves for further advances. This project will make major contributions to international effo ....Statistical methods for detection of non-coding RNAs in eukaryote genomes. Understanding how eukaryotic cells work is a major goal of 21st century biology. A crucial step will be to catalogue the functional components of eukaryotic genomes. Australian researchers must be involved in this process at an early stage, in order to maximise commercial opportunities, attract quality researchers and position ourselves for further advances. This project will make major contributions to international efforts in this area, via the development of statistical methods for segmenting genomes, classification of those segments, and study of the resulting classes. In the long term, enhanced understanding of eukaryotic cells will lead to breakthroughs in biology, and to medical, pharmaceutical, agricultural and scientific advances.Read moreRead less
Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi ....Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.Read moreRead less
Simulating viral evolution and genetic complexity. This project has direct relevance to understanding the growth of viral infections, and therefore has possible practical applications in disease research and control. Examples of these are emerging diseases in humans such as those caused by HIV-1, SARS coronavirus and Dengue virus, which cause considerable human suffering throughout the world. A major part of current research into these diseases involves attempts to model the evolutionary geneti ....Simulating viral evolution and genetic complexity. This project has direct relevance to understanding the growth of viral infections, and therefore has possible practical applications in disease research and control. Examples of these are emerging diseases in humans such as those caused by HIV-1, SARS coronavirus and Dengue virus, which cause considerable human suffering throughout the world. A major part of current research into these diseases involves attempts to model the evolutionary genetics and dynamics of virus populations in order to understand how to control epidemics, develop vaccines and design drugs. The research program is designed to provide new computational modelling tools for this purpose, which may have wider applications as well.
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Determining elements that underpin learning of child-witness interviewing. This project aims to investigate the elements that underpin the learning of child witness interviewing skills. Preliminary indications from pioneering research suggest that positive change in interviewer behaviour is achievable. This project aims to extend that work on a larger scale. Expected outcomes include knowledge about the conditions under which skill acquisition is effective for different learners in disparate con ....Determining elements that underpin learning of child-witness interviewing. This project aims to investigate the elements that underpin the learning of child witness interviewing skills. Preliminary indications from pioneering research suggest that positive change in interviewer behaviour is achievable. This project aims to extend that work on a larger scale. Expected outcomes include knowledge about the conditions under which skill acquisition is effective for different learners in disparate contexts, and how skills can be maintained over the long term. The findings will guide the planning and implementation of interviewer training programs and contribute to improved interview quality and better justice outcomes for child complainants of abuse.Read moreRead less
The demographic consequences of migration to, from and within Australia. The long-term demographic consequences of migration to, from and within Australia, and the dynamic pathways that produced them, will be studied. This will involve the identification of the specific contributions made by international and internal migration to the age and sex population compositions of nine birthplace-specific populations from 1981 to 2011. To do this, publically available data will be collected and augmente ....The demographic consequences of migration to, from and within Australia. The long-term demographic consequences of migration to, from and within Australia, and the dynamic pathways that produced them, will be studied. This will involve the identification of the specific contributions made by international and internal migration to the age and sex population compositions of nine birthplace-specific populations from 1981 to 2011. To do this, publically available data will be collected and augmented with statistical methods to provide a complete, consistent account of population change for around 60 subnational areas. As migration and population change underpins many aspects of societal change in Australia, this research aims to provide an invaluable resource to other scientists and policy makers.Read moreRead less
New Methods in Theory and Cosmic Applications of Spherical Random Fields. This project aims to investigate and model spherical random fields which are described as solutions of stochastic differential equations on a sphere or a ball. The project plans to study properties and develop spectral analysis of these solutions. It then plans to use the obtained theoretical results to construct new methods for numerical approximation and statistical estimation of these random fields. In particular, it pl ....New Methods in Theory and Cosmic Applications of Spherical Random Fields. This project aims to investigate and model spherical random fields which are described as solutions of stochastic differential equations on a sphere or a ball. The project plans to study properties and develop spectral analysis of these solutions. It then plans to use the obtained theoretical results to construct new methods for numerical approximation and statistical estimation of these random fields. In particular, it plans to develop novel asymptotic and statistical methodology for tensor random fields. The project will apply the results to model and analyse cosmic microwave background data. Expected outcomes will improve the accuracy in determining cosmological parameters and provide novel tools for better understanding of the universe during its early stages.Read moreRead less