Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require c ....Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require computational techniques that run extremely efficiently. The project expects to develop and improve approximate data structures that operate in tight resource bounds. Anticipated outcomes are improved event recognition and dramatic speedup in analysis of streams in areas such as finance, health, transport, and urban data.Read moreRead less
New Insights on Modelling Time Trends with Panel Data: Theory and Practice. This project aims to tackle important challenges in time trend modelling by taking advantage of panel data structures. This project expects to propose flexible models in time trend modelling to retrieve reliable inference. The expected outcomes include innovative econometric models and methods that have a wide range of applications, and are particularly suited for empirical problems within large and complex systems. This ....New Insights on Modelling Time Trends with Panel Data: Theory and Practice. This project aims to tackle important challenges in time trend modelling by taking advantage of panel data structures. This project expects to propose flexible models in time trend modelling to retrieve reliable inference. The expected outcomes include innovative econometric models and methods that have a wide range of applications, and are particularly suited for empirical problems within large and complex systems. This will provide significant benefits to all fields in which data displays any form of trending behaviour. The proposed model is used to evaluate the economic consequences of climate change and global housing market contagion, which provide strong evidence-based insights to the environmental and economic policies in Australia.Read moreRead less
Devising tools for big data sets to support computational movement analysis. This project aims to devise practical fundamental algorithms and multi-purpose data structures with performance guarantees for big spatio-temporal data sets. Systematic analysis of trajectory data has been occurring since the 1950s, but with the recent technological advances the size of the data sets has recently soared. Existing computational tools were developed for small to mid-size data sets. This project aims to d ....Devising tools for big data sets to support computational movement analysis. This project aims to devise practical fundamental algorithms and multi-purpose data structures with performance guarantees for big spatio-temporal data sets. Systematic analysis of trajectory data has been occurring since the 1950s, but with the recent technological advances the size of the data sets has recently soared. Existing computational tools were developed for small to mid-size data sets. This project aims to devise practical fundamental algorithms that will enable the development of domain specific tools for a wide range of applications, including sports, behavioural ecology, transport, and surveillance.Read moreRead less
Insecure Work and the Mental Health of Workers and their Families. This project aims to explore the relationship between insecure work and mental health by applying advanced econometric methods to large survey and administrative datasets, and newly collected survey data. This project expects to provide causal policy-relevant estimates of how insecure work is affecting the wellbeing of workers and their families, and for whom the effects are most harmful. It also expects to inform on how poor men ....Insecure Work and the Mental Health of Workers and their Families. This project aims to explore the relationship between insecure work and mental health by applying advanced econometric methods to large survey and administrative datasets, and newly collected survey data. This project expects to provide causal policy-relevant estimates of how insecure work is affecting the wellbeing of workers and their families, and for whom the effects are most harmful. It also expects to inform on how poor mental health influences the types of jobs that people enter into. This should provide significant benefits, including evidence needed to improve existing workplace and employment programs, and evidence ensuring that assistance is efficiently targeted to those workers and industries with the greatest need.Read moreRead less
The Role Of Preconception And Perinatal Substance Use And Misuse In Childhood Social, Emotional And Behavioural Problems
Funder
National Health and Medical Research Council
Funding Amount
$1,562,250.00
Summary
This project will use perinatal and preconception data from three long-running Australian studies that have tracked the health and wellbeing of several thousand participants prior to parenthood. The aim is to understand how parental histories of substance use, and patterns of use during pregnancy, and in early life, shape offspring social, emotional and behavioural outcomes across childhood. Results will inform new approaches to preventing substance-related harms within and across generations.
Econometric studies of the dynamics of loneliness and social isolation. This project aims to provide new insights into the socioeconomic dynamics of loneliness and social isolation using advanced econometric modelling techniques applied to longitudinal data from Australia and the UK. This project will apply advanced econometric modelling techniques to data from four nationally-representative longitudinal surveys to substantively help address these knowledge gaps, giving policy-makers new informa ....Econometric studies of the dynamics of loneliness and social isolation. This project aims to provide new insights into the socioeconomic dynamics of loneliness and social isolation using advanced econometric modelling techniques applied to longitudinal data from Australia and the UK. This project will apply advanced econometric modelling techniques to data from four nationally-representative longitudinal surveys to substantively help address these knowledge gaps, giving policy-makers new information about how to address these growing societal concerns. The expected outcomes will provide policy-makers with a better understanding of the socioeconomic triggers for loneliness and social isolation; quantify the costs of loneliness and social isolation on health and wellbeing; and identify policy interventions aimed at reducing loneliness and social isolation.Read moreRead less
Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge compu ....Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge computing. The expected outcome of the project is a set of solutions to the myriad of services relying on mobile edge computing including e-Health, autonomous vehicles, and Internet of Things. This project will develop key fundamental technologies to improve Australia’s standing in the international research community.
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Discovery Early Career Researcher Award - Grant ID: DE180100438
Funder
Australian Research Council
Funding Amount
$402,996.00
Summary
Children's time investments, cognitive development and health. This project aims to understand time investment decisions of children and adolescents. There is a need for more robust evidence on the combination of time investments that improve early cognitive skills and well being. Using advanced econometric techniques and longitudinal data, this project expects to generate new knowledge on how children and adolescents spend their time, and how such time investments affect their health and cognit ....Children's time investments, cognitive development and health. This project aims to understand time investment decisions of children and adolescents. There is a need for more robust evidence on the combination of time investments that improve early cognitive skills and well being. Using advanced econometric techniques and longitudinal data, this project expects to generate new knowledge on how children and adolescents spend their time, and how such time investments affect their health and cognitive development. Expected outcomes of this project include a greater understanding of the early determinants of health and economic inequalities. This will contribute to the development of effective policies for improving educational outcomes, preventing harmful behaviours and promoting health and well being.Read moreRead less
Microeconometric Analysis of Socioeconomic Inequity in Mental Healthcare. The project aims to describe the extent of socioeconomic inequity in Australian mental healthcare use, identify the causal pathways that drive inequities, and conduct economic evaluations of programs aimed at increasing healthcare access. Microeconometric methods will be used to analyse large, longitudinal datasets that have not previously been used for this purpose. The project expects to provide a greater understanding o ....Microeconometric Analysis of Socioeconomic Inequity in Mental Healthcare. The project aims to describe the extent of socioeconomic inequity in Australian mental healthcare use, identify the causal pathways that drive inequities, and conduct economic evaluations of programs aimed at increasing healthcare access. Microeconometric methods will be used to analyse large, longitudinal datasets that have not previously been used for this purpose. The project expects to provide a greater understanding of the barriers that people face in accessing treatment and how to overcome them. Such understanding is currently missing from academic literatures and policy inquiries. Ultimately, the research should aid in the design of cost-effective policies that improve health outcomes and that reduce inequities in treatment access.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101329
Funder
Australian Research Council
Funding Amount
$432,355.00
Summary
Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven d ....Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven decision systems and rigorously analyse their performance and privacy guarantees. Privacy of individuals' information in data analytics pipelines is a key societal concern. This project should lead to significant benefits by strengthening privacy in these pipelines while also improving accuracy and cost-efficiency.Read moreRead less