3D Image segmentation and shape characterisation driven by topological persistence. Tomographic imaging is emerging as a new tool to help tackle a remarkable array of scientific challenges. What distinguishes healthy bone from that of osteoporosis sufferers? How does groundwater contamination spread? Why is a macadamia nut so hard to crack? What causes the iridescence in a butterfly wing? These are just a few of the questions being answered at tomographic facilities in Australia alone. By co ....3D Image segmentation and shape characterisation driven by topological persistence. Tomographic imaging is emerging as a new tool to help tackle a remarkable array of scientific challenges. What distinguishes healthy bone from that of osteoporosis sufferers? How does groundwater contamination spread? Why is a macadamia nut so hard to crack? What causes the iridescence in a butterfly wing? These are just a few of the questions being answered at tomographic facilities in Australia alone. By combining sophisticated mathematics with cutting edge image-processing algorithms, this project will yield a new class of topology driven image analysis techniques that will improve the accuracy and reliability of predictions made from tomographic images.Read moreRead less
Thermo-mechanical interactive atlas of basin evolution. We propose to create a thermo-mechanical interactive atlas of basin evolution as a desktop geodynamic modelling resource for exploration geologists. The atlas will allow the user to iteratively run our 2D/3D basin modelling software ELLIPSIS to alter model parameters until they match observed basin geometries or thermal history. Model iteration will be based on interactive user evaluation of model outputs and genetic algorithms, which pr ....Thermo-mechanical interactive atlas of basin evolution. We propose to create a thermo-mechanical interactive atlas of basin evolution as a desktop geodynamic modelling resource for exploration geologists. The atlas will allow the user to iteratively run our 2D/3D basin modelling software ELLIPSIS to alter model parameters until they match observed basin geometries or thermal history. Model iteration will be based on interactive user evaluation of model outputs and genetic algorithms, which progressively modify the solution set by mimicking the evolutionary behavior of biological systems (selection, cross-over and mutation), until an acceptable result is achieved. The interactive atlas will be applied to Australian and international case studies.Read moreRead less
A Photometric Imaging Model for Mobile Underwater Camera Design. This project aims to develop the first photometric model of computational image formation from a mobile underwater platform, allowing the prediction of performance for conventional and computational cameras in physically grounded scenarios. The model is expected to include sufficient detail to predict key performance metrics relevant to targeted underwater imaging applications, including three-dimensional structure recovery, surfac ....A Photometric Imaging Model for Mobile Underwater Camera Design. This project aims to develop the first photometric model of computational image formation from a mobile underwater platform, allowing the prediction of performance for conventional and computational cameras in physically grounded scenarios. The model is expected to include sufficient detail to predict key performance metrics relevant to targeted underwater imaging applications, including three-dimensional structure recovery, surface reflectance characterisation, and discrimination for automated and human-driven classification of benthic habitats. Novel imaging systems optimised for the requirements of specific marine imaging tasks are intended to be designed and constructed, exploiting the imaging model to rapidly explore the camera design space.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100274
Funder
Australian Research Council
Funding Amount
$415,675.00
Summary
Graph Neural Networks for Efficient Decision-making towards Future Grids. This project aims to develop a breakthrough framework for decision-focused learning by integrating explainable graph neural networks and efficient computational methods. It expects to create new methodologies of graph representation learning for unlocking data insight with spatiotemporal knowledge while to build new accelerated optimisation theories for speeding up decision-focused learning model. The expected outcomes wil ....Graph Neural Networks for Efficient Decision-making towards Future Grids. This project aims to develop a breakthrough framework for decision-focused learning by integrating explainable graph neural networks and efficient computational methods. It expects to create new methodologies of graph representation learning for unlocking data insight with spatiotemporal knowledge while to build new accelerated optimisation theories for speeding up decision-focused learning model. The expected outcomes will advance big spatiotemporal data analytics and nonlinear optimisation theory for solving decision-making tasks towards a future energy system. This should promote the Australian power industry transition to a sustainable future grid based on a digitalisation approach to efficient energy management against climate changes.Read moreRead less
Autonomous service robots in a multi-agent based system for household and industrial environments. This project addresses fundamental research issues required to develop autonomous mobile robots for intelligent cleaning services. As an interdisciplinary project spanning the fields of robotics, mechatronics and AI, it offers potential benefits in bringing robots into less-structured human environments. Robots performing autonomous cleaning (including hazardous waste and spillage) and security tas ....Autonomous service robots in a multi-agent based system for household and industrial environments. This project addresses fundamental research issues required to develop autonomous mobile robots for intelligent cleaning services. As an interdisciplinary project spanning the fields of robotics, mechatronics and AI, it offers potential benefits in bringing robots into less-structured human environments. Robots performing autonomous cleaning (including hazardous waste and spillage) and security tasks in both household and industrial environments has tremendous national/community benefits in cost and time savings, improved efficiency and safety, and facilitating hazardous or labour intensive tasks. Other benefits include research training, strengthening Australia's R&D position in key innovative technologies, and creating jobs and exports.Read moreRead less
An integrated model for assessing health effects of nanoparticle inhalation. This project aims to examine the associated risks of nanoparticle inhalation on heath by developing a toxicological predictive tool for health risk assessment. The outcomes of this research will lead to greatly improved preventative measures, thereby reducing occupational diseases and the health socio-economic burden of Australia.
A Multiscale Modelling Platform for Nanoparticle Inhalation Risk Assessment. This project aims to explore the health risks caused by nanoparticle inhalation and its penetration through respiratory mucus and tissue cells. Exposure to nanoparticles has the potential to cause serious and possibly fatal health effects. An understanding of nanoparticle toxicology would enable us to appropriately protect the public’s health and safety. The project plans to consider human respiratory anatomy and physio ....A Multiscale Modelling Platform for Nanoparticle Inhalation Risk Assessment. This project aims to explore the health risks caused by nanoparticle inhalation and its penetration through respiratory mucus and tissue cells. Exposure to nanoparticles has the potential to cause serious and possibly fatal health effects. An understanding of nanoparticle toxicology would enable us to appropriately protect the public’s health and safety. The project plans to consider human respiratory anatomy and physiology and use advanced computer modelling and experimental techniques to evaluate the health risk of exposure to the burgeoning number of nanomaterials found in consumer products. The expected outcome of the project is a predictive tool that determines nanoparticle exposure risk and its health consequences.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100660
Funder
Australian Research Council
Funding Amount
$358,731.00
Summary
Simulating social networks to understand how neighbourhood factors influence health. Where you live and who you know has implications for your health. This study will use social network models to understand how social characteristics of neighbourhoods influence health. The new insights gained will help policy makers to develop better strategies for reducing health inequalities and improving health outcomes.
Modelling the Development and Evolution of Business Relations and Networks as Complex Adaptive Systems using Agent Based Models. This research develops models that will allow managers and policy makers to play more effective roles in the development and evolution of collaborative business relations and networks that lead to greater efficiency, industry innovation, and firm competitiveness, which is a key focus of corporate management and government trade and industry policy. It will also enhance ....Modelling the Development and Evolution of Business Relations and Networks as Complex Adaptive Systems using Agent Based Models. This research develops models that will allow managers and policy makers to play more effective roles in the development and evolution of collaborative business relations and networks that lead to greater efficiency, industry innovation, and firm competitiveness, which is a key focus of corporate management and government trade and industry policy. It will also enhance Australia's resources and expertise in understanding and modelling complex adaptive systems, help develop education resources and training programs for practitioners and researchers in this fast growing area of theory and research, strengthen links with leading researchers and centres, and produce a doctorate in the area.Read moreRead less
Reshaping superannuation practice in Australia using big data analytics. This project aims to reform superannuation investment practices in Australia. Using sophisticated data analytics and machine-learning techniques, combined with economic modelling and quantitative finance. The project will try to understand the broad characteristics of Australian superannuation investors and their practice from a ‘big data’ perspective. The expected outcomes of this project are the identification of key dete ....Reshaping superannuation practice in Australia using big data analytics. This project aims to reform superannuation investment practices in Australia. Using sophisticated data analytics and machine-learning techniques, combined with economic modelling and quantitative finance. The project will try to understand the broad characteristics of Australian superannuation investors and their practice from a ‘big data’ perspective. The expected outcomes of this project are the identification of key determinants for successful superannuation behaviour to inform decision-making for better superannuation practices and policies. It is expected that the insights arising from this project will contribute to safeguarding the future of Australia’s superannuation schemes, and to better financial security at retirement.Read moreRead less