Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so ....Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals. Read moreRead less
Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in mi ....Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in microscale tissue properties are lacking. The tools developed by this project will be used to generate new magnetic resonance image based maps to convey information on tissue microstructure changes in the human brain. Additionally, the mathematical tools developed will be transferable to other applications where diffusion and transport in heterogeneous porous media play a role.Read moreRead less
Personalised public transport. This project aims to address urban congestion by utilising people’s travel plans to coordinate journeys. The project expects to generate new knowledge in scalable optimisation, based on innovative modelling of urban transport, and tested on historical data from Melbourne. The expected outcomes of the project are an active transport database and optimised mode choice and routing system, with predicted reductions in congestion based on simulation of its use. This pro ....Personalised public transport. This project aims to address urban congestion by utilising people’s travel plans to coordinate journeys. The project expects to generate new knowledge in scalable optimisation, based on innovative modelling of urban transport, and tested on historical data from Melbourne. The expected outcomes of the project are an active transport database and optimised mode choice and routing system, with predicted reductions in congestion based on simulation of its use. This project aims to design an urban trip advisory system that could be followed by automated vehicles as well as human drivers, to reduce the financial and environmental cost of current urban congestion.Read moreRead less
Individualisation for 3D Audio. The project aim is to allow the general listener to enjoy high-fidelity 3-D sound over headphones. Such 3-D audio is of paramount importance when inter-personal communication requires situational awareness, (eg search and rescue, fire-fighting, and air traffic control). To achieve this, the project aims to address one of the toughest problems in audio signal processing: deriving high-fidelity 3-D audio headphone filters from photos and/or 3D scans of ears. The pro ....Individualisation for 3D Audio. The project aim is to allow the general listener to enjoy high-fidelity 3-D sound over headphones. Such 3-D audio is of paramount importance when inter-personal communication requires situational awareness, (eg search and rescue, fire-fighting, and air traffic control). To achieve this, the project aims to address one of the toughest problems in audio signal processing: deriving high-fidelity 3-D audio headphone filters from photos and/or 3D scans of ears. The project plans to address fundamental research questions in statistical shape and data analysis and to perceptually evaluate the 3-D audio methods developed.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100892
Funder
Australian Research Council
Funding Amount
$419,889.00
Summary
Next-generation, prefabricated, modular, solar heating and cooling system. This project aims to develop a new window design that can reduce the heating of buildings caused by the sun in warm weather and reduce heat loss from buildings in cool weather. This project expects to generate new knowledge on the interaction between solar radiation and the convection of air inside a cavity within the window design. The expected outcome is a framework that can be used to optimize window designs for buildi ....Next-generation, prefabricated, modular, solar heating and cooling system. This project aims to develop a new window design that can reduce the heating of buildings caused by the sun in warm weather and reduce heat loss from buildings in cool weather. This project expects to generate new knowledge on the interaction between solar radiation and the convection of air inside a cavity within the window design. The expected outcome is a framework that can be used to optimize window designs for buildings under various weather conditions. This should allow quick and easy fabrication and implementation of the designs in existing and new buildings, and the windows should significantly reduce building heating and cooling costs.Read moreRead less
Dynamics and control of complex social networks. This project aims to understand the extent to which a given complex social network can be controlled and how different control mechanisms influence network structure and dynamics. There is a great interest in controlling complex networks including social networks as it might contribute to solving important societal challenges. Using gender imbalance, minority marginalisation, and criminal behaviour as case studies, this project will investigate t ....Dynamics and control of complex social networks. This project aims to understand the extent to which a given complex social network can be controlled and how different control mechanisms influence network structure and dynamics. There is a great interest in controlling complex networks including social networks as it might contribute to solving important societal challenges. Using gender imbalance, minority marginalisation, and criminal behaviour as case studies, this project will investigate the direction of networks controllability and mechanisms that would enable alteration of the network in a desired way. This project will have an impact on our current understanding of network's behaviour, and will contribute to solving a range of societal challenges.Read moreRead less
Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact netw ....Managing infectious disease through partial wildlife social networks. This project aims to investigate the dynamics of the spread of infectious disease in wildlife, derived from incomplete information about contact networks. Infectious diseases in wildlife are difficult to track and control, because it is not feasible to monitor each individual in a population and know the contact network for a population. The project will create ways to best utilise incomplete observational data of contact networks to develop robust predictions of disease spread and population fate, and to reliably predict the outcomes of management interventions. These robust prediction methods will provide better insights for conservation of Australian wildlife.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101549
Funder
Australian Research Council
Funding Amount
$395,775.00
Summary
A virtual platform for animal–human inhalation toxicity extrapolation. This project aims to remove the long-lasting barrier in extrapolating data from animals to humans by developing an integrated virtual platform. This project expects to fully resolve inhalation exposure differences in nasal airways between commonly used animal surrogates and humans, which could lay scientific underpinnings in developing rigorous interspecies data conversion schemes. Expected outcomes include a versatile inhala ....A virtual platform for animal–human inhalation toxicity extrapolation. This project aims to remove the long-lasting barrier in extrapolating data from animals to humans by developing an integrated virtual platform. This project expects to fully resolve inhalation exposure differences in nasal airways between commonly used animal surrogates and humans, which could lay scientific underpinnings in developing rigorous interspecies data conversion schemes. Expected outcomes include a versatile inhalation exposure risk assessment tool that can be implemented for any airway compartment, enhanced reliability of animal tests, reduced number of animals for testing. This should provide significant benefits in improving occupational health and safety and promoting National/International regulatory changes. Read moreRead less
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less