Iron - a solution for uranium resource recovery and pollution response. This project aims to determine key processes controlling uranium transport and fate in natural and engineered environments. This will result in improved efficiency in extracting uranium from tailings and subsurface deposits, reduced risk of contamination of water supplies, and improved management of radioactive waste repositories.
An assessment of carbon dioxide storage capacity of water bearing sedimentary basins. Dealing with the problems caused by climate change and global warming is among the greatest challenges facing Australia today. One of the approaches being considered to minimise anthropogenic influence over climate is the geo-sequestration of carbon dioxide (CO2). The proposed project will lead to greater understanding of storage capacity of sedimentary basins and identification of optimum injection conditions ....An assessment of carbon dioxide storage capacity of water bearing sedimentary basins. Dealing with the problems caused by climate change and global warming is among the greatest challenges facing Australia today. One of the approaches being considered to minimise anthropogenic influence over climate is the geo-sequestration of carbon dioxide (CO2). The proposed project will lead to greater understanding of storage capacity of sedimentary basins and identification of optimum injection conditions for geo-sequestration in such aquifers, and any potential mechanisms that could lead to migration of CO2 from the source rock back to the atmosphere.This will contribute to national efforts to reduce global warming, safeguard the Australian economy, and allow continued electricity generation from coal-fired plants.Read moreRead less
Advanced hydrodynamics for next generation of offshore infrastructure. This project aims to develop rigorous and precise prediction models for next generation offshore infrastructure, by capturing nonlinear wave-structure interaction. This project expects to generate new knowledge in offshore hydrodynamics (a branch of fluid mechanics) applicable to Ocean Engineering, using cutting-edge numerical technology, state-of-the-art physical modelling, and unique full-scale field data. The expected outc ....Advanced hydrodynamics for next generation of offshore infrastructure. This project aims to develop rigorous and precise prediction models for next generation offshore infrastructure, by capturing nonlinear wave-structure interaction. This project expects to generate new knowledge in offshore hydrodynamics (a branch of fluid mechanics) applicable to Ocean Engineering, using cutting-edge numerical technology, state-of-the-art physical modelling, and unique full-scale field data. The expected outcomes include enhanced capacity to estimate hydrodynamic response and advanced design tools for floating wind, floating solar and offshore aquaculture. This will provide significant benefit by enabling cost-efficient and viable designs, thereby accelerating the development of offshore renewable energy.Read moreRead less
Water sensitive mining. The project aims to provide tools that can identify how mining projects, including associated land use and infrastructure, can play a positive role in sustainable water management. This will be based on new knowledge about mine-land-water relationships, novel approaches to modelling mine site hydrology within regional models and greater emphasis on risk evaluation. This work is essential if resource-rich regions in Australia and beyond are to be developed with sustainabil ....Water sensitive mining. The project aims to provide tools that can identify how mining projects, including associated land use and infrastructure, can play a positive role in sustainable water management. This will be based on new knowledge about mine-land-water relationships, novel approaches to modelling mine site hydrology within regional models and greater emphasis on risk evaluation. This work is essential if resource-rich regions in Australia and beyond are to be developed with sustainability as a goal, and for mining to live comfortably alongside other strategically important water and land users. The main outcome aims to be the development of new tools for predicting and optimising the regional water management opportunities provided by mining.Read moreRead less
Data-driven modelling of complex reactive flows. Complex reactive flow is dominant in many chemicals, physical and biological processes and should be optimised online for operational efficiency and stability, yet it is hindered by the lack of reliable model techniques. The project tackles this challenge by developing a next-generation data-driven modelling approach via integrating continuum/discrete-scale fluid-particle dynamics with system/control theories, supported by lab/plant experiments. D ....Data-driven modelling of complex reactive flows. Complex reactive flow is dominant in many chemicals, physical and biological processes and should be optimised online for operational efficiency and stability, yet it is hindered by the lack of reliable model techniques. The project tackles this challenge by developing a next-generation data-driven modelling approach via integrating continuum/discrete-scale fluid-particle dynamics with system/control theories, supported by lab/plant experiments. Driven by online data, the generic approach can open up a powerful way to reliably describe the inner state of reactors and online predict operation anomalies. The outcomes can help transform a range of industries to smart manufacturing and design, which is vital to Australia's technological future.Read moreRead less
Situated Anomaly Detection in an Open Environment. This project aims to investigate situated anomaly detection in an open environment. Existing anomaly detection techniques follow the setting of conventional machine learning and discover anomalies from a set of collected data. In contrast, this project proposes to develop the next-generation of anomaly detection algorithms by learning from interactions with an open environment, which enables the discovery of new anomalies and the early detection ....Situated Anomaly Detection in an Open Environment. This project aims to investigate situated anomaly detection in an open environment. Existing anomaly detection techniques follow the setting of conventional machine learning and discover anomalies from a set of collected data. In contrast, this project proposes to develop the next-generation of anomaly detection algorithms by learning from interactions with an open environment, which enables the discovery of new anomalies and the early detection of anomalies. The established theories and developed algorithms will advance frontier technologies in machine intelligence. The success of the project will contribute to a wide range of real applications in cybersecurity, defence and finance, bringing massive social and economic benefits. Read moreRead less
Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collabor ....Adapting Deep Learning for Real-world Medical Image Datasets. The project aims to investigate new deep learning modelling approaches to leverage real-world large-scale image data sets that contain noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers. Expected outcomes include an innovative method for modelling deep learning classifiers. The research will involve new inter-disciplinary and international collaborations with machine learning and medical image analysis research institutions. This should provide significant benefits, such as better understanding of deep learning theory, new deep learning applications that can use previously unexplored data sets, and training for the future Australian workforce.Read moreRead less
Multi-modal virtual microscopy for quantitative diagnostic pathology. This project will contribute to the next generation of virtual microscopy systems that provide innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of diagnostic pathology. These tools will especially contribute to the screening and diagnosis of cervical, lung and bladder cancer.
Rethinking Topological Persistence. This project aims to address the lack of transferability and uncertainty-awareness in AI models. Despite their success, AI models are met with bias and uncertainty when deployed in the real world. As a result, they are rarely used in high-risk industries like cybersecurity or transport. This project expects to build uncertainty-awareness into models by teaching them to return UNKNOWN when they encounter a previously unseen thing, instead of misclassifying it. ....Rethinking Topological Persistence. This project aims to address the lack of transferability and uncertainty-awareness in AI models. Despite their success, AI models are met with bias and uncertainty when deployed in the real world. As a result, they are rarely used in high-risk industries like cybersecurity or transport. This project expects to build uncertainty-awareness into models by teaching them to return UNKNOWN when they encounter a previously unseen thing, instead of misclassifying it. Further, the evaluation methods to be developed will not rely on access to test data, allowing cost-effective, private, and safe AI for high-stakes decision support. The outcomes will benefit Australia by accelerating economic investment and fostering greater social acceptance of AI.Read moreRead less
The many lives and deaths of high redshift massive quiescent galaxies. This Fellowship will investigate the recent discovery of very massive, extremely early forming quiescent galaxies and explain their exceptional origin, death, and ultimate place in the local Universe. It is a multidisciplinary project that seeks to produce new knowledge using high-performance computing, software engineering, and sophisticated data analysis techniques. Expected outcomes include novel and improved supercomputer ....The many lives and deaths of high redshift massive quiescent galaxies. This Fellowship will investigate the recent discovery of very massive, extremely early forming quiescent galaxies and explain their exceptional origin, death, and ultimate place in the local Universe. It is a multidisciplinary project that seeks to produce new knowledge using high-performance computing, software engineering, and sophisticated data analysis techniques. Expected outcomes include novel and improved supercomputer simulations of several billions of galaxies processed through a virtual observatory, providing tools and fundamental knowledge for observational, theoretical, and computational astrophysics.Read moreRead less