Building Australia's next-generation ocean-sea ice model. Ocean and sea ice models are used for predicting future ocean and climate states, and for climate process research. This project aims to bring the next generation of ocean-sea ice models to Australia and configure the models for our local priorities. The ultimate goal is to create a new coupled ocean-sea ice model for Australia that includes surface waves and biogeochemistry. The model will be optimised and evaluated on Australian facilit ....Building Australia's next-generation ocean-sea ice model. Ocean and sea ice models are used for predicting future ocean and climate states, and for climate process research. This project aims to bring the next generation of ocean-sea ice models to Australia and configure the models for our local priorities. The ultimate goal is to create a new coupled ocean-sea ice model for Australia that includes surface waves and biogeochemistry. The model will be optimised and evaluated on Australian facilities, and released for community use. These developments underpin future ocean state forecasts, sea ice forecasts, wave forecasts, decadal climate prediction and climate process studies. The project will benefit search and rescue, Defence and shipping operations, and will enhance future climate projections.Read moreRead less
Quantum optical methods for entangled devices. This project aims to develop experimental quantum optics methods and techniques for enhancing the performance of sensitive devices. Entangled photons will be used to probe separate devices, yielding an improved detection of correlated signals. This new technique will benefit laboratory searches for new fundamental physics effects such as space-time fluctuations due to quantum gravity and exotic dark matter candidates. The project is expected to tr ....Quantum optical methods for entangled devices. This project aims to develop experimental quantum optics methods and techniques for enhancing the performance of sensitive devices. Entangled photons will be used to probe separate devices, yielding an improved detection of correlated signals. This new technique will benefit laboratory searches for new fundamental physics effects such as space-time fluctuations due to quantum gravity and exotic dark matter candidates. The project is expected to train scientists and students in advanced quantum methods, promoting and securing Australia's position as a leader in the development of quantum technologies. Read moreRead less
Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to devel ....Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to develop purely data-driven rules to choose the regularisation parameter and show how they work in theory, and in practice. It will also develop convex framework, acceleration strategies as well as preconditioning and splitting ideas to design efficient regularisation solvers.Read moreRead less
Hybrid Toughening of Carbon Fibre Composites for Liquid Hydrogen Storage. This project aims to develop hybrid toughening technologies to overcome the major problem of transverse matrix cracking and splitting in existing carbon fibre composites when subjected to thermal-mechanical loading at the ultracold liquid hydrogen temperature. Nano-toughened thin-ply carbon fibre layers will be hybridised with standard-ply laminates to sustain internal pressure and external impact loading at cryogenic temp ....Hybrid Toughening of Carbon Fibre Composites for Liquid Hydrogen Storage. This project aims to develop hybrid toughening technologies to overcome the major problem of transverse matrix cracking and splitting in existing carbon fibre composites when subjected to thermal-mechanical loading at the ultracold liquid hydrogen temperature. Nano-toughened thin-ply carbon fibre layers will be hybridised with standard-ply laminates to sustain internal pressure and external impact loading at cryogenic temperatures without leaks. The hybrid composites are expected to enable Australian companies to engineer, manufacture and export lightweight carbon fibre tanks for storing and exporting liquid hydrogen, which is emerging as a transformational opportunity for Australia to become a global supplier of green energy.Read moreRead less
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less
Democratisation of Deep Learning: Neural Architecture Search at Low Cost. The need to manually design Deep Learning-based Neural Networks (DNNs) limits their usage to AI experts and hinders the exploitation of their true potential more broadly, e.g., in farming, humanities. We aim to replace this tedious process through novel AI methods capable of generating DNNs that can perform significantly better and at a lower computational cost than manually designed DNNs. We further expand this idea to so ....Democratisation of Deep Learning: Neural Architecture Search at Low Cost. The need to manually design Deep Learning-based Neural Networks (DNNs) limits their usage to AI experts and hinders the exploitation of their true potential more broadly, e.g., in farming, humanities. We aim to replace this tedious process through novel AI methods capable of generating DNNs that can perform significantly better and at a lower computational cost than manually designed DNNs. We further expand this idea to solve complex real-world problems with both labelled and unlabelled data found in various applications including energy and climate change. The expected outcomes include the novel AI methods, highly trained AI researchers and a number of critical applications that will bring significant benefits to Australia and the world.Read moreRead less
Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, commun ....Machine education for trusted multi-skilled evolutionary learners . Transforming data assets into organisational knowledge assets sits in the hands of a few, highly specialised, data scientists. The aim of this research is to design educational instruments to support non-experts to teach artificial intelligence (AI) systems in a similar way to educating human teachers to teach human learners. The significance of the project lies in affording the wider smart, but not necessarily AI expert, community the ability to contribute to growing our knowledge-based society in a safe, transparent and trustworthy manner. Outcomes will include innovative instruments to teach machines, novel knowledge creation, trusted and transparent AI systems, and a new generation of human teachers specialised in educating AI systems.Read moreRead less
Breaking barriers to high-performance room-temperature quantum technologies. This project aims to break the major barriers to realising high-performance quantum technologies that operate at room temperature by exploiting the unique properties of colour centres in diamond and two-dimensional materials. This project expects to yield profound new knowledge of colour centres and new theoretical methods, experimental techniques and quantum devices. Expected outcomes are significant enhancements of ....Breaking barriers to high-performance room-temperature quantum technologies. This project aims to break the major barriers to realising high-performance quantum technologies that operate at room temperature by exploiting the unique properties of colour centres in diamond and two-dimensional materials. This project expects to yield profound new knowledge of colour centres and new theoretical methods, experimental techniques and quantum devices. Expected outcomes are significant enhancements of existing technologies, invention of novel two-dimensional technologies, and expanded domestic capability and international collaborations in quantum technology. These outcomes will benefit Australia by securing its global competitiveness in quantum industry and providing transformative tools to science, defence and industry.Read moreRead less
Real-time imaging of crystal strengthening mechanisms in metals. The strength limit of a metal is marked by rapid motion of crystalline defects. The associated speeds can locally approach that of sound. To probe the associated mechanisms clearly requires both spatial and temporal resolution. We propose to create a new bulk x-ray technique with an unprecedented combination of temporal and spatial resolution. We plan to exploit the technique to mediate a step change in modelling strength based on ....Real-time imaging of crystal strengthening mechanisms in metals. The strength limit of a metal is marked by rapid motion of crystalline defects. The associated speeds can locally approach that of sound. To probe the associated mechanisms clearly requires both spatial and temporal resolution. We propose to create a new bulk x-ray technique with an unprecedented combination of temporal and spatial resolution. We plan to exploit the technique to mediate a step change in modelling strength based on twinning. The formation of crystalline twins is known to dictate the strength of the light metal magnesium. A fuller understanding of the effect of twinning on strength in this metal will provide much needed confidence to implement it more widely in energy saving applications.Read moreRead less