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
Trisections, triangulations and the complexity of manifolds. This project aims at practical representations of 3-dimensional and 4-dimensional spaces as needed in applications. Topology is the mathematical study of the shapes of spaces. Geometry endows spaces with additional structure such as distance, angle and curvature. Special combinatorial structures, such as minimal triangulations, are often closely connected to geometric structures or topological properties. This project aims to construct ....Trisections, triangulations and the complexity of manifolds. This project aims at practical representations of 3-dimensional and 4-dimensional spaces as needed in applications. Topology is the mathematical study of the shapes of spaces. Geometry endows spaces with additional structure such as distance, angle and curvature. Special combinatorial structures, such as minimal triangulations, are often closely connected to geometric structures or topological properties. This project aims to construct computable invariants, connectivity results for triangulations, and algorithms to recognise fundamental topological properties and structures such as trisections and bundles.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH230100013
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Future Digital Manufacturing. This Hub aims to grow and accelerate Australian digital manufacturing (DM) transformation by devising novel DM technology and commercialisation/adoption pathways. The Hub expects to transform industry by developing novel AI and IoT-powered DM technology that provides for dramatic improvement in manufacturing productivity, resilience and competitiveness. Expected outcomes include novel DM technology for digitally representing, predicting, and imp ....ARC Research Hub for Future Digital Manufacturing. This Hub aims to grow and accelerate Australian digital manufacturing (DM) transformation by devising novel DM technology and commercialisation/adoption pathways. The Hub expects to transform industry by developing novel AI and IoT-powered DM technology that provides for dramatic improvement in manufacturing productivity, resilience and competitiveness. Expected outcomes include novel DM technology for digitally representing, predicting, and improving production and its outcomes via an open platform that supports reusing industry co-created DM solutions. Through supporting advanced manufacturing priorities and Industry 4.0, the Hub should provide significant benefits by increasing Australian manufacturing productivity and resilience by 30%.Read moreRead less
Approximate algorithms and architectures for area efficient system design. This project aims to develop simpler but reliable image recognition systems that can run on low-cost, small-scale platforms, for use in driver monitoring system (DMS) applications. Cheaper reliable DMS will lead to wider availability of this technology to end users and improve safety of motor vehicles. This project will develop approximate algorithmic and circuit techniques, provide training for research students and buil ....Approximate algorithms and architectures for area efficient system design. This project aims to develop simpler but reliable image recognition systems that can run on low-cost, small-scale platforms, for use in driver monitoring system (DMS) applications. Cheaper reliable DMS will lead to wider availability of this technology to end users and improve safety of motor vehicles. This project will develop approximate algorithmic and circuit techniques, provide training for research students and build capability in the area of approximate computing. It is also expected to lead to commercial products, licences and revenue, which will enable new job creation.
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Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric ....Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric graphs, which both advances the knowledge in this field of computer science and make our existing networks more reliable. This should provide significant benefits in the maintenance and utilisation of the communication and transport networks we use every day.Read moreRead less
Quantum computation: through the algorithm and complexity theory lens. This project aims to advance our knowledge of quantum computation through the lens of algorithm and complexity theory. Three core areas of the theory will be examined: interactive computing models, query complexity, and circuit lower bounds. The expected outcomes include: revealing the quantum advantages of interactive computing models; techniques for verifying quantum devices in the cloud and quantum cloud computing in gener ....Quantum computation: through the algorithm and complexity theory lens. This project aims to advance our knowledge of quantum computation through the lens of algorithm and complexity theory. Three core areas of the theory will be examined: interactive computing models, query complexity, and circuit lower bounds. The expected outcomes include: revealing the quantum advantages of interactive computing models; techniques for verifying quantum devices in the cloud and quantum cloud computing in general; sharpening the separation between algorithm performance in quantum and classical query models; establishing both unconditional and conditional hardness results for quantum circuits. This comprehensive understanding will enhance Australia's research portfolio in the theory of quantum computing.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
Internet Timing for the Ages: Establishing the New Timekeeping System. All computers incorporate a software clock, essential to myriad software applications. An economic way to synchronize such clocks is over a network, however the approach the Internet currently depends upon is unreliable and vulnerable. This project aims to establish a new architecture for networked timekeeping, built on future-proofed fundamentals, that will for the first time address each of accuracy, reliability, and trust. ....Internet Timing for the Ages: Establishing the New Timekeeping System. All computers incorporate a software clock, essential to myriad software applications. An economic way to synchronize such clocks is over a network, however the approach the Internet currently depends upon is unreliable and vulnerable. This project aims to establish a new architecture for networked timekeeping, built on future-proofed fundamentals, that will for the first time address each of accuracy, reliability, and trust. The expected outcome is a national prototype, serving the public with accurate and trusted time, that will form the basis of the next generation timekeeping system for the Internet and the Internet of Things. Expected benefits include enhanced productivity across the digital economy, and resilience to GPS failures.Read moreRead less
Inverse problems with partial data. This project aims to use mathematics, in particular the theory of micro-local analysis, to determine the amount of measurements one needs in order to reconstruct an image by some of the tomography methods commonly used in medical imaging. Expected outcomes of this project include showing that an arbitrarily small set of boundary measurements is sufficient to reconstruct the coefficients of various important partial differential equations such as Schrodinger eq ....Inverse problems with partial data. This project aims to use mathematics, in particular the theory of micro-local analysis, to determine the amount of measurements one needs in order to reconstruct an image by some of the tomography methods commonly used in medical imaging. Expected outcomes of this project include showing that an arbitrarily small set of boundary measurements is sufficient to reconstruct the coefficients of various important partial differential equations such as Schrodinger equation, Dirac operators, and Maxwell equations. In addition to providing a theoretical foundation upon which one can build numerical algorithms, this project will also provide the missing link between inverse problems and unique continuation theory. The downstream impact of this research will lead to more efficient and accurate tomography methods which can be implemented in a range of imaging applications.Read moreRead less
Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful ....Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful visualisations, and evaluate using real world social network and biological network data sets. The new models, metrics and algorithms produced by this project will be used in the next generation Visual Analytic tools to enable analysts develop accurate insights and new knowledge of complex data.Read moreRead less