Discovery Early Career Researcher Award - Grant ID: DE120101266
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Low-complexity factor-graph-based receiver design for bandwidth-efficient communication systems over doubly selective channels. This project aims to solve challenging problems in future wireless communications using graph-based signal processing techniques. It will provide practical solutions for future broadband mobile communications to the bush and high-speed underwater acoustic communications in the oceans that are particularly important to Australia.
Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there ....Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there a major changes to existing series, improving the analysis of such series and the decisions based on them.Read moreRead less
Temporal Trends In The Incidence, Site And Survival Of Metastatic Breast Cancer In Australia
Funder
National Health and Medical Research Council
Funding Amount
$190,494.00
Summary
There have been major advances in breast cancer treatment over the last decade. This project will use information collected from the NSW cancer registry and hospitals to report on changes in the type and risk of breast cancer spread and survival for women with a new diagnosis of breast cancer before and after new treatments introduced since 2005. This information is essential for doctors to provide women with up-to-date information; and for planning appropriate health services and research.
Discovery Early Career Researcher Award - Grant ID: DE210100256
Funder
Australian Research Council
Funding Amount
$415,283.00
Summary
Extracting the hidden structure of glass from particle vibrations. Predicting the rigid behaviour of glass from its disordered, amorphous atomic structure remains a challenge in materials science. This project aims to define an innovative measure of structure based on how constrained each particle is, which can be quantified by measuring the particles’ vibrations. Using this new measure of structure, this project expects to link the microscopic structure of glass to its macroscopic properties v ....Extracting the hidden structure of glass from particle vibrations. Predicting the rigid behaviour of glass from its disordered, amorphous atomic structure remains a challenge in materials science. This project aims to define an innovative measure of structure based on how constrained each particle is, which can be quantified by measuring the particles’ vibrations. Using this new measure of structure, this project expects to link the microscopic structure of glass to its macroscopic properties via computer simulations. Expected outcomes of this project include a new methodology for characterising amorphous materials and an improved understanding of the nature of glass. This should provide significant benefits, such as an increased ability to rationally design amorphous materials with desired properties.Read moreRead less
Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
ARC Financial Integrity Research Network. The integrity of the financial system is constantly under stress because of the development of ever more complex financial instruments, structures and strategies, and the associated research technologies that continues to accelerate worldwide. FIRN's vision is to harness the considerable strengths of Australia's internationally renowned finance, accounting and economics researchers into a research agenda to address issues concerning the integrity of the ....ARC Financial Integrity Research Network. The integrity of the financial system is constantly under stress because of the development of ever more complex financial instruments, structures and strategies, and the associated research technologies that continues to accelerate worldwide. FIRN's vision is to harness the considerable strengths of Australia's internationally renowned finance, accounting and economics researchers into a research agenda to address issues concerning the integrity of the financial system. It will enable Australian research in this area to match the scale and impact of similar research in other major international financial centres, and play an essential role in placing Australia among the world's leaders in financial markets related research.Read moreRead less
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Deep ocean thermodynamics and climate change. This project aims to obtain new insights into the thermodynamic and transport properties of mixtures containing water, particularly at high pressures, that impact directly on our understanding of climate change processes. The project will involve the use of a polarisable potential for water which has recently been demonstrated to yield predictions of high accuracy. It will be used to model saline water mixtures containing carbon dioxide, resulting in ....Deep ocean thermodynamics and climate change. This project aims to obtain new insights into the thermodynamic and transport properties of mixtures containing water, particularly at high pressures, that impact directly on our understanding of climate change processes. The project will involve the use of a polarisable potential for water which has recently been demonstrated to yield predictions of high accuracy. It will be used to model saline water mixtures containing carbon dioxide, resulting in valuable data for thermodynamic properties of the world's oceans. These data are of crucial importance for accurate climate change predictions and as such the project will have an important impact on understanding our changing environment.Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less