The effective treatment of drug using offenders: the impact of treatment modality, coercion and treatment readiness on criminal recidivism. Drug use is associated with significant health, social, and economic costs. Given the established drug-crime connection and the high rate of relapse among drug-using offenders, the outcomes of this research will assist policymakers in identifying clinically and cost effective approaches to service delivery. Moreover, in view of the debate that surrounds the ....The effective treatment of drug using offenders: the impact of treatment modality, coercion and treatment readiness on criminal recidivism. Drug use is associated with significant health, social, and economic costs. Given the established drug-crime connection and the high rate of relapse among drug-using offenders, the outcomes of this research will assist policymakers in identifying clinically and cost effective approaches to service delivery. Moreover, in view of the debate that surrounds the efficacy of coerced treatment, and the extent to which Australia should follow the United States of America’s lead of mandating treatment for all substance using offenders, the project will test the proposition that compulsory treatment has positive outcomes in terms of reductions in recidivism.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL150100150
Funder
Australian Research Council
Funding Amount
$2,413,112.00
Summary
Bayesian learning for decision making in the big data era. Bayesian learning for decision making in the big data era: This fellowship project aims to develop new techniques in evidence-based learning and decision-making in the big data era. Big data has arrived, and with it a huge global demand for statistical knowledge and skills to analyse these data for improved learning and decision-making. This project will seek to address this need by creating a step-change in knowledge in Bayesian statist ....Bayesian learning for decision making in the big data era. Bayesian learning for decision making in the big data era: This fellowship project aims to develop new techniques in evidence-based learning and decision-making in the big data era. Big data has arrived, and with it a huge global demand for statistical knowledge and skills to analyse these data for improved learning and decision-making. This project will seek to address this need by creating a step-change in knowledge in Bayesian statistics and translating this knowledge to real-world challenges in industry, environment and health. The new big data statistical analysts trained through the project could also create much needed capacity at national and international levels.Read moreRead less
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
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
Aboriginal and non-Aboriginal sex-offenders in Australia: Assessing risk for practice and policy. A key priority of Australian governments is to improve community safety through reducing the risk of sex offenders re-offending after release from prison. This project will assess the validity of tools used to predict the risk of sexual offender recidivism and identify alternate risk assessment tools for Indigenous and non-Indigenous sex offenders.
Discovery Early Career Researcher Award - Grant ID: DE170101134
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Feasible algorithms for big inference. This project aims to develop algorithms for computationally-intensive statistical tools to analyse Big Data. Big Data is ubiquitous in science, engineering, industry and finance, but needs special machine learning to conduct correct inferential analysis. Computational bottlenecks make many tried-and-true tools of statistical inference inadequate. This project will develop tools including false discovery rate control, heteroscedastic and robust regression an ....Feasible algorithms for big inference. This project aims to develop algorithms for computationally-intensive statistical tools to analyse Big Data. Big Data is ubiquitous in science, engineering, industry and finance, but needs special machine learning to conduct correct inferential analysis. Computational bottlenecks make many tried-and-true tools of statistical inference inadequate. This project will develop tools including false discovery rate control, heteroscedastic and robust regression and mixture models, via Big Data-appropriate optimisation and composite-likelihood estimation. It will make open, well-documented, and accessible software available for the scalable and distributable analysis of Big Data. The expected outcome is a suite of scalable algorithms to analyse Big Data.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100115
Funder
Australian Research Council
Funding Amount
$180,000.00
Summary
Confocal microscope for high-resolution microtopographic analysis of surfaces in historical, forensic and polymer sciences. High-resolution analyses of microscopic patterns on surfaces using confocal microscopy can provide vital clues into the nature of ancient diets and environments, adaptive evolution, weapons used in crimes, and properties of polymers. This instrument will heighten Australia’s capacity for world-leading research in areas of major national importance.
Improving Productivity and Efficiency of Australian Airports – A Real Time Analytics and Statistical Approach. Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity; however, complex dependencies and differing operational objectives complicate t ....Improving Productivity and Efficiency of Australian Airports – A Real Time Analytics and Statistical Approach. Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity; however, complex dependencies and differing operational objectives complicate this task. This project aims to develop a real-time, whole-of-system operational performance framework that can help operators in finding and evaluating solutions to maximise throughput, reduce wait times and mitigate flow-on effects. Innovative new video analytic and Bayesian Network based tools are integrated to address the challenges of adaptability and uncertainty.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
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100154
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
The Advanced DNA Identification and Forensics Facility. The advanced DNA identification and forensics facility:
The project aims to establish a national integrated facility for cutting-edge forensic genetic research, resources and expertise in wildlife, forest and environmental DNA identification to improve our capacity to identify unknown biological material. The project’s goal will be to enhance synergies between academic research, service delivery and forensic application of DNA identificati ....The Advanced DNA Identification and Forensics Facility. The advanced DNA identification and forensics facility:
The project aims to establish a national integrated facility for cutting-edge forensic genetic research, resources and expertise in wildlife, forest and environmental DNA identification to improve our capacity to identify unknown biological material. The project’s goal will be to enhance synergies between academic research, service delivery and forensic application of DNA identification technologies, addressing vital questions such as: From which individual or species did this material originate? Where in the world is it from? Is it legal? The proposed facility may deliver applied outcomes for government, the criminal justice system, and industry, such as improved pest and threatened species identification; biosecurity, prosecutions of wildlife crime and illegal logging; and missing person and disaster victim identification.Read moreRead less