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
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
Efficient Compression and Querying Techniques for Massive Text Collections. Web search services have become a fundamental tool used by governments, businesses, and individuals, and play a key role in our access to knowledge and information. In this project we aim to develop new techniques for representing the indexes at the heart of web search services, and to devise new processing algorithms with reduced resource requirements for resolving queries and providing useful and topical answers. Hig ....Efficient Compression and Querying Techniques for Massive Text Collections. Web search services have become a fundamental tool used by governments, businesses, and individuals, and play a key role in our access to knowledge and information. In this project we aim to develop new techniques for representing the indexes at the heart of web search services, and to devise new processing algorithms with reduced resource requirements for resolving queries and providing useful and topical answers. Higher query throughput and reduced storage load will benefit providers though reduced hardware and electricity costs, and will benefit society through better access to information, enhanced opportunities to connect and collaborate, and greater long-term scalability as on-line resources continue to multiply.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
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
Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical cluste ....Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical clustering algorithms for dynamic networks – with performance guarantees of efficiency and clustering quality – and prototype software, guiding us to pick a good clustering. Expected benefits include better understanding of spread in evolving social networks, accelerating the software testing cycle, and improved topic detection.Read moreRead less
Attribution of Machine-generated Code for Accountability. Machine-generated (or neural) code is usually produced by AI tools to speed up software development. However, such codes have recently raised serious security and privacy concerns. This project aims to attribute these codes to their generative models for accountability purposes. In the process, a series of new techniques are developed to differentiate between the codes generated by different models. The outcomes include analysis of neural ....Attribution of Machine-generated Code for Accountability. Machine-generated (or neural) code is usually produced by AI tools to speed up software development. However, such codes have recently raised serious security and privacy concerns. This project aims to attribute these codes to their generative models for accountability purposes. In the process, a series of new techniques are developed to differentiate between the codes generated by different models. The outcomes include analysis of neural code fingerprints, classification of neural codes, and theories to verify the correctness of code attribution. These will provide significant benefits, ranging from copyright protection to privacy preservation. This project is timely since currently the software community is pervasively using neural codes.Read moreRead less
Multi-phase modelling and characterisation of mudrush hazard in cave mining. A mudrush is a sudden, uncontrolled flow of wet fine particles (mud) into an underground mine that damages equipment, infrastructure, and can even cause fatalities. This project aims to develop cost-effective management and monitoring of mudrush hazards within the at-risk Carrapateena cave mine operated by OZ Minerals. Building on recent technological and numerical advances, a novel experimental–theoretical–numerical ap ....Multi-phase modelling and characterisation of mudrush hazard in cave mining. A mudrush is a sudden, uncontrolled flow of wet fine particles (mud) into an underground mine that damages equipment, infrastructure, and can even cause fatalities. This project aims to develop cost-effective management and monitoring of mudrush hazards within the at-risk Carrapateena cave mine operated by OZ Minerals. Building on recent technological and numerical advances, a novel experimental–theoretical–numerical approach will be used to simulate mudrush risk based on moisture content, particle sizes, compaction, geological conditions, and seismic energy. Outputs will include a practical framework to boost the safety, productivity, and profitability of caving operations to benefit miners and the broader resources industry.Read moreRead less
Interface-aware numerical methods for stochastic inverse problems. This project aims to design novel high-performance numerical tools for solving large-scale forward and inverse problems dominated by stochastic interfaces and quantifying associated uncertainties. In real-world applications such as groundwater, these tools are instrumental for assimilating big datasets into mathematical models for providing reliable predictions. By advancing and integrating high-order polytopal schemes, multileve ....Interface-aware numerical methods for stochastic inverse problems. This project aims to design novel high-performance numerical tools for solving large-scale forward and inverse problems dominated by stochastic interfaces and quantifying associated uncertainties. In real-world applications such as groundwater, these tools are instrumental for assimilating big datasets into mathematical models for providing reliable predictions. By advancing and integrating high-order polytopal schemes, multilevel methods, transport maps, and dimension reduction, this project's anticipated outcomes are highly accurate and cost-efficient numerical schemes, certified by rigorous mathematical analysis. This should provide data-centric simulation tools with enhanced reliability, for engineering and scientific applications.Read moreRead less
Towards predictive 4D computational models for the heart. This project aims to develop novel high-performance numerical algorithms for multiscale and multiphysics PDEs with dynamic interfaces, the development and analysis of a novel PDE system modelling the electromechanics of heart and torso, and the combination of these numerical techniques and models to deliver predictive tools for patient-specific simulations of the cardiac function. It involves the design and mathematical analysis of space- ....Towards predictive 4D computational models for the heart. This project aims to develop novel high-performance numerical algorithms for multiscale and multiphysics PDEs with dynamic interfaces, the development and analysis of a novel PDE system modelling the electromechanics of heart and torso, and the combination of these numerical techniques and models to deliver predictive tools for patient-specific simulations of the cardiac function. It involves the design and mathematical analysis of space-time variational discretisations on embedded meshes, 4D computational geometry algorithms for numerical integration and multilevel solvers. By combining scientific computing and machine learning, one anticipated outcome of this research is a new generation of nonlinear PDE approximations and solvers.Read moreRead less