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.
Industrial Transformation Research Hubs - Grant ID: IH210100040
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC RESEARCH HUB FOR CONNECTED SENSORS FOR HEALTH. This Hub aims to develop, manufacture and deploy high-tech, cyber-secure, medically-certified IoT sensors to global health markets by integrating disparate Australian capabilities into a productive end-to-end value chain. This Hub expects to position Australia at the forefront of connected health by integrating sensor science with cyber-secure data analytics, regulatory approval and certified manufacturing capabilities. Expected outcomes of this ....ARC RESEARCH HUB FOR CONNECTED SENSORS FOR HEALTH. This Hub aims to develop, manufacture and deploy high-tech, cyber-secure, medically-certified IoT sensors to global health markets by integrating disparate Australian capabilities into a productive end-to-end value chain. This Hub expects to position Australia at the forefront of connected health by integrating sensor science with cyber-secure data analytics, regulatory approval and certified manufacturing capabilities. Expected outcomes of this Hub include advanced manufacturing capacity for connected sensors, strategic partnerships and commercialisation skills to translate sensors research to create economic benefits such as jobs and locally-made products for domestic and export markets, as well as improving the health of Australians.Read moreRead less
Sulphate sensor for reverse osmosis integrity and performance monitoring. Sulphate sensor for reverse osmosis integrity and performance monitoring. This project aims to investigate new chemical sensors for sulphate for online reverse osmosis integrity and performance monitoring at an advanced water recycling plant. Wastewater re-use is increasingly important in Australia and worldwide for providing potable water. Demonstrating the integrity and performance of treatment technologies is needed to ....Sulphate sensor for reverse osmosis integrity and performance monitoring. Sulphate sensor for reverse osmosis integrity and performance monitoring. This project aims to investigate new chemical sensors for sulphate for online reverse osmosis integrity and performance monitoring at an advanced water recycling plant. Wastewater re-use is increasingly important in Australia and worldwide for providing potable water. Demonstrating the integrity and performance of treatment technologies is needed to meet health regulations. Sulphate and other surrogates of biological entities enable a rapid, on-line approach to integrity and performance monitoring, but detection with available analytical chemical technology is not feasible. This research is expected to enable better management of water treatment processes and demonstrate compliance to health standards.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC210100056
Funder
Australian Research Council
Funding Amount
$3,975,864.00
Summary
ARC Training Centre for Next-Gen Technologies in Biomedical Analysis . The Centre for Next-Gen Technologies in Biomedical Analysis will deliver workforce trained in the development of transformative technologies that will rapidly expand the Australian pharmaceutical, diagnostic and defence sector. The university-industry partnership will increase Australia’s manufacturing capability by fast tracking screening, by integrating 3D printing, advanced sensing, big data analytics, machine learning an ....ARC Training Centre for Next-Gen Technologies in Biomedical Analysis . The Centre for Next-Gen Technologies in Biomedical Analysis will deliver workforce trained in the development of transformative technologies that will rapidly expand the Australian pharmaceutical, diagnostic and defence sector. The university-industry partnership will increase Australia’s manufacturing capability by fast tracking screening, by integrating 3D printing, advanced sensing, big data analytics, machine learning and artificial intelligence for the delivery of optimal solutions in diagnosis, treatment and wellbeing. The centre will deliver training in Industry 4.0 skills which will boost early-stage scale-up and accelerate the sector’s supply chain, which is pivotal for the Australian industries to maintain a competitive edge. 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
Industrial Transformation Training Centres - Grant ID: IC130100021
Funder
Australian Research Council
Funding Amount
$2,100,000.00
Summary
ARC Training Centre for Advanced Technologies in Food Manufacture. Training Centre for Advanced Technologies in Food Manufacture. This Training Centre for Advanced Technologies in Food Manufacture will enable Australian food processing and manufacturing companies to meet the increasing threats of international competition. It will do this through collaboration between industry and the Training Centre’s food science, nutrition and engineering researchers and the development of innovative technolo ....ARC Training Centre for Advanced Technologies in Food Manufacture. Training Centre for Advanced Technologies in Food Manufacture. This Training Centre for Advanced Technologies in Food Manufacture will enable Australian food processing and manufacturing companies to meet the increasing threats of international competition. It will do this through collaboration between industry and the Training Centre’s food science, nutrition and engineering researchers and the development of innovative technologies.
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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
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.
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