Linkage Infrastructure, Equipment And Facilities - Grant ID: LE200100078
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
A particle detector array for the Murchison Widefield Array. The project will construct a particle detector array for the Murchison Widefield Array radio telescope. The array will identify cosmic ray interactions in the Earth's atmosphere, and trigger radio observations. The outcome will be a new capability to study the origin of the highest-energy particles in nature, cosmic rays, and discover new physical processes at energies unreachable by the Large Hadron Collider.
The anticipated benefits ....A particle detector array for the Murchison Widefield Array. The project will construct a particle detector array for the Murchison Widefield Array radio telescope. The array will identify cosmic ray interactions in the Earth's atmosphere, and trigger radio observations. The outcome will be a new capability to study the origin of the highest-energy particles in nature, cosmic rays, and discover new physical processes at energies unreachable by the Large Hadron Collider.
The anticipated benefits are the establishment of the Murchison Widefield Array as a world-leading instrument for astroparticle physics; to lay the foundations for future research with the Square Kilometre Array; and to provide answers to long-standing scientific questions of public interest.Read moreRead less
MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) ne ....MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.Read moreRead less
SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to p ....Next generation garbage collection: discovery, design, and development. This project aims to improve the performance of programming languages used by millions of Australians every day, such as Java, JavaScript and PHP by developing improved memory-management algorithms. These languages use what is referred to as “garbage collection” to ensure memory is managed without data loss, but do so conservatively and consequently cause performance challenges and energy overheads. This project expects to provide these languages with improved memory-management algorithms, and provides researchers and industry with a framework for innovation. This project will enable safe software that is more efficient on today's hardware and able to exploit emerging hardware. This project should lead to better performance and energy savings for server applications, phones, watches, and smart appliances, while ensuring memory safety.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100002
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. Thes ....ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. These dynamic systems will help determine what goal to achieve and the most efficient plan to achieve it. This Hub is expected to contribute to higher farming efficiency, lower production costs and fewer disease risks, giving the Australian industry new business opportunities and an international competitive advantage.Read moreRead less
Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capabili ....Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capability and competitiveness in AI, and deliver robust and trustworthy learning technology. The project should provide significant benefits not only in advancing scientific and translational knowledge but also in accelerating AI innovations, safeguarding cyberspace, and reducing the burden on defence expenses in Australia.Read moreRead less
Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the c ....Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the characteristics of the particles, their sources and spatial and temporal variation across different urban areas and time scales. Further, the impacts of changing fuels, vehicle technologies, and climate on future trends of the particles will be elucidated.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100025
Funder
Australian Research Council
Funding Amount
$4,379,165.00
Summary
ARC Research Hub for Advanced Manufacturing with 2D Materials (AM2D). Australia holds large resources of critical 2D minerals – key enablers of several existing and emerging technologies in Energy Storage, Purification and Printed Electronics. The AM2D hub aims to provide a sophisticated environment for researchers and an industrial translation platform for manufacturers; a hub where leading academics, bright students, and industry partners come together to learn, apply, collaborate, innovate, a ....ARC Research Hub for Advanced Manufacturing with 2D Materials (AM2D). Australia holds large resources of critical 2D minerals – key enablers of several existing and emerging technologies in Energy Storage, Purification and Printed Electronics. The AM2D hub aims to provide a sophisticated environment for researchers and an industrial translation platform for manufacturers; a hub where leading academics, bright students, and industry partners come together to learn, apply, collaborate, innovate, and deliver industry transformation in advanced manufacturing. Anticipated outcomes include the transformation of newly discovered materials into globally traded, high-value 2D products, enabling Australian industries to capture more wealth and jobs from this large and growing market.
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