High-resolution multiscale modelling of pandemics: COVID-19 and beyond. The project aims to develop high-resolution computational models for pandemic mitigation and control, focussing on the novel coronavirus and its emerging variants, and leveraging demographic, genomic and epidemiological data. It expects to rigorously compare multi-scale effects of complex vaccination and social distancing strategies and quantify optimal responses under the COVID-19 induced uncertainty. The intended outcomes ....High-resolution multiscale modelling of pandemics: COVID-19 and beyond. The project aims to develop high-resolution computational models for pandemic mitigation and control, focussing on the novel coronavirus and its emerging variants, and leveraging demographic, genomic and epidemiological data. It expects to rigorously compare multi-scale effects of complex vaccination and social distancing strategies and quantify optimal responses under the COVID-19 induced uncertainty. The intended outcomes include computational models of how the most infectious viral variants emerge and spread in presence of interventions, how to predict the outbreaks, and which are the most vulnerable communities. This should make a significant economic and social impact, improving population health while maintaining a resilient economy.Read moreRead less
Propagating Neural Waves: Combined Experimental and Modelling Study. The project is designed to measure propagating neural waves in visual areas of the brain to discover why and how they are created, how they interact with sensory inputs, and whether they can support brain plasticity and learning. Recent analysis of the brain’s electrical signals has showed that nerve cell activity is often organised into propagating waves, but how these waves are created, and what role they play in brain inform ....Propagating Neural Waves: Combined Experimental and Modelling Study. The project is designed to measure propagating neural waves in visual areas of the brain to discover why and how they are created, how they interact with sensory inputs, and whether they can support brain plasticity and learning. Recent analysis of the brain’s electrical signals has showed that nerve cell activity is often organised into propagating waves, but how these waves are created, and what role they play in brain information processing, remains unknown. The project plans to develop new methods for processing large-scale neural data, and to apply these methods to learn about propagating neural waves. These results may improve our understanding of how neural circuits function, eventually leading to clinical and technological advances.Read moreRead less
Quantifying emergence and dynamics of foodborne epidemics in Australia. The project aims to greatly improve the accuracy and scope of computational epidemiological models predicting emergence and evolution of foodborne diseases in Australia. It expects to reveal key pathways for both biological evolution of microorganisms, and their spread though food supply chains and human interactions. The intended outcomes include discovering how the most dominant strains of foodborne infection emerge and se ....Quantifying emergence and dynamics of foodborne epidemics in Australia. The project aims to greatly improve the accuracy and scope of computational epidemiological models predicting emergence and evolution of foodborne diseases in Australia. It expects to reveal key pathways for both biological evolution of microorganisms, and their spread though food supply chains and human interactions. The intended outcomes include discovering how the most dominant strains of foodborne infection emerge and self-organise in complex networks, how to predict and contain the epidemics closer to their source, and which are the most vulnerable groups and communities. This should make a significant economic and social impact, improving health of the population, while also safeguarding national and international supply chains.Read moreRead less
Learning the meso-scale organization of complex networks. This project aims to model and learn the organization of online social networks. We will combine mathematical models, inference, and domain knowledge from computational social sciences to obtain interpretable descriptions of the role groups of users play in the network. The expected outcomes are new mathematical models and computational methods that learn from data how to best decompose a complex network into building blocks and their int ....Learning the meso-scale organization of complex networks. This project aims to model and learn the organization of online social networks. We will combine mathematical models, inference, and domain knowledge from computational social sciences to obtain interpretable descriptions of the role groups of users play in the network. The expected outcomes are new mathematical models and computational methods that learn from data how to best decompose a complex network into building blocks and their interactions, linking connectivity to function. This should provide benefits to industries and policy makers interested in how information spreads in social media, including the critical questions of understanding the mechanisms contributing to political polarization and fragmentation.Read moreRead less
Mathematical model reduction for complex networks. This project aims to develop new mathematical methodology to describe the collective behaviour of large networks of oscillators with parameters called collective coordinates. This will allow for the quantitative description of finite-size networks as well as chaotic dynamics, which are both out of reach for current model reduction methods. The project will apply methodology to understand the causes of, and ways to prevent, glitches and failure i ....Mathematical model reduction for complex networks. This project aims to develop new mathematical methodology to describe the collective behaviour of large networks of oscillators with parameters called collective coordinates. This will allow for the quantitative description of finite-size networks as well as chaotic dynamics, which are both out of reach for current model reduction methods. The project will apply methodology to understand the causes of, and ways to prevent, glitches and failure in the emerging modern decentralised power grids. This will develop a framework to address this question, tailored to deal with the hitherto uncharted case of finite-size networks.Read moreRead less
Intelligent pattern recognition of water end uses enabling recommendations. This project aims to develop a hybrid machine learning method for autonomously disaggregating high- and low-resolution water flow data received from smart meters into discrete end-use events, and a customised recommender system for efficient resource demand management. Project novelty and significance relates to this coupling and autonomous disaggregation of datasets from advanced sensors, enabling more efficient utility ....Intelligent pattern recognition of water end uses enabling recommendations. This project aims to develop a hybrid machine learning method for autonomously disaggregating high- and low-resolution water flow data received from smart meters into discrete end-use events, and a customised recommender system for efficient resource demand management. Project novelty and significance relates to this coupling and autonomous disaggregation of datasets from advanced sensors, enabling more efficient utility services delivery and lower customer utility bills. Project benefits include enabling utilities to better manage and plan resources in the information age, while empowering customers with real-time water end-use data and behaviour changing consumption recommendations.Read moreRead less
Hydraulic Systems and State Development in Early Cambodia: Mapping the Engineered Landscapes of the Khmer Using Remote Sensing. Due to recent discoveries, Australian research at Angkor, in Cambodia, has gained increasing visibility worldwide. The ARC-funded Greater Angkor Project (Discovery) and Living With Heritage project (Linkage) have produced results of international significance, developed strong long-term partnerships with Cambodian agencies and UNESCO, and have pioneered the large-scale ....Hydraulic Systems and State Development in Early Cambodia: Mapping the Engineered Landscapes of the Khmer Using Remote Sensing. Due to recent discoveries, Australian research at Angkor, in Cambodia, has gained increasing visibility worldwide. The ARC-funded Greater Angkor Project (Discovery) and Living With Heritage project (Linkage) have produced results of international significance, developed strong long-term partnerships with Cambodian agencies and UNESCO, and have pioneered the large-scale mapping of World Heritage-listed sites using airborne imaging radar systems in collaboration with NASA. This project will extend these partnerships, consolidate Australia's leading position in radar analysis methods, and continue to produce results with global implications for the understanding and management of World Heritage sites.Read moreRead less
Integrated data-tested theory and modelling of type three solar radio emissions. Type three solar radio emissions, the Sun's most powerful and common, are the archetypal collective radio phenomenon in space physics and astrophysics. The project will integrate new theoretical work and simulations into a first integrated data-tested theory that can explain type three bursts, resolve long standing issues, and constrain solar physics.
Congestion control in complex networks with higher-order interactions. Traffic congestion significantly costs the Australian economy and environment. This project aims to develop ground-breaking network models of urban traffic systems to build a new congestion control framework. The purpose of network modelling is to capture the interdependence between different parts of traffic systems, which facilitates studying congestion cascade within the network. The project expects to generate next genera ....Congestion control in complex networks with higher-order interactions. Traffic congestion significantly costs the Australian economy and environment. This project aims to develop ground-breaking network models of urban traffic systems to build a new congestion control framework. The purpose of network modelling is to capture the interdependence between different parts of traffic systems, which facilitates studying congestion cascade within the network. The project expects to generate next generation of network models for more effective congestion control. Expected outcomes include novel congestion control technologies that adjust traffic signals in real-time to optimally utilise the available road space. This should provide significant economic and environmental benefits to Australians by easing traffic jams.Read moreRead less
Functional magnetic resonance imaging: Decoding the palimpsest. This project aims to model the dynamics of functional magnetic resonance imaging (fMRI) to image new physiology and attain higher resolution. This will enable new aspects of brain dynamics to be imaged, achieving higher resolution and improving interpretation. This project is expected to improve the use and power of fMRI, unlock new avenues for probing brain function and save experimental costs. This will have many uses in neuroscie ....Functional magnetic resonance imaging: Decoding the palimpsest. This project aims to model the dynamics of functional magnetic resonance imaging (fMRI) to image new physiology and attain higher resolution. This will enable new aspects of brain dynamics to be imaged, achieving higher resolution and improving interpretation. This project is expected to improve the use and power of fMRI, unlock new avenues for probing brain function and save experimental costs. This will have many uses in neuroscience, brain imaging technology and fMRI analysis software.Read moreRead less