TSuNAMi: Time Series Network Animal Modelling. Our proposal is motivated by and based upon the successful representation of time series as a network (or graph). We construct an abstract representation of a system from measurements of its changing behaviour over time. Properties of that structure (the network) then allow us to infer diagnostic information of the system. Specifically, we propose to apply this to livestock welfare during transport. By measuring the biological and environment condi ....TSuNAMi: Time Series Network Animal Modelling. Our proposal is motivated by and based upon the successful representation of time series as a network (or graph). We construct an abstract representation of a system from measurements of its changing behaviour over time. Properties of that structure (the network) then allow us to infer diagnostic information of the system. Specifically, we propose to apply this to livestock welfare during transport. By measuring the biological and environment condition of the animal we construct a network representation of that system. Geometric features of that network can then be used to infer health or duress of the subject. This proposal will develop the generic mathematical machinery to connect geometric features of the network with system behaviour. Read moreRead less
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
A study of the archaeology of Caucasian Iberia with implications for grazing management in Australia. This multi-disciplinary project will promote a younger generation of talented postgraduate and undergraduate students in a wide variety of fields, including archaeology, geomatic engineering, conservation of material culture, environmental and other natural sciences. The highlands of the Caucasus, located in a bioclimatic zone with a long history of alpine grazing, can also provide answers to qu ....A study of the archaeology of Caucasian Iberia with implications for grazing management in Australia. This multi-disciplinary project will promote a younger generation of talented postgraduate and undergraduate students in a wide variety of fields, including archaeology, geomatic engineering, conservation of material culture, environmental and other natural sciences. The highlands of the Caucasus, located in a bioclimatic zone with a long history of alpine grazing, can also provide answers to questions such as the effect of grazing on biodiversity and the rehabilitation of fragile ecosystems, which may inform management and conservation activities in analogous highland country in Australia. The project will also ensure that exhibitions illustrating the rich heritage of Caucasus will reach Australian shores.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
Metaphotonics and metasurfaces for disruptive sensing technologies. This project aims to address a big challenge in nanophotonics by developing revolutionary methods for efficient chiral sensing of molecules without the need for spectrometry, frequency scanning, or moving mechanical parts, and to enhance chiroptical signals a hundredfold with the help of metasurface structures. Resonant metasurfaces are arrays of engineered dielectric nanoparticles with extraordinary characteristics, and they wo ....Metaphotonics and metasurfaces for disruptive sensing technologies. This project aims to address a big challenge in nanophotonics by developing revolutionary methods for efficient chiral sensing of molecules without the need for spectrometry, frequency scanning, or moving mechanical parts, and to enhance chiroptical signals a hundredfold with the help of metasurface structures. Resonant metasurfaces are arrays of engineered dielectric nanoparticles with extraordinary characteristics, and they would allow to overcome current limitations of chiral sensing analytical tools. Detecting chiral molecules in low concentrations is crucially important to many fields of biology, chemistry, and pharmacy, as well as to the food and cosmetics industries, constituting a market of tens of billions of dollars.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
Networks: New links between spectrum, dynamics, rewirings and applications. Modern network science has transformed the study of complex systems and led to innovations in many disciplines. This project intends to develop breakthrough theories for control of complex networked system behaviour via interventions of the link-rewiring type. New approaches will be developed for non-random, assortative and/or structured networks, which are poorly understood and difficult to deal with, despite being the ....Networks: New links between spectrum, dynamics, rewirings and applications. Modern network science has transformed the study of complex systems and led to innovations in many disciplines. This project intends to develop breakthrough theories for control of complex networked system behaviour via interventions of the link-rewiring type. New approaches will be developed for non-random, assortative and/or structured networks, which are poorly understood and difficult to deal with, despite being the real-world norm and despite their impact. The results will give new insights into epidemic outbreaks and their impact on vulnerable groups (e.g., elderly and indigenous), and provides methods to enforce resilience of infrastructure networks such as power grids, thereby providing significant economic and societal benefits. Read moreRead less
Variable Structure Complex Network Systems with Smart Grid Applications. This project aims to establish a breakthrough theory and technology to help deliver reliability and security of complex network systems, which are subject to structure changes, against faults and cyberattacks. Expected outcomes include a new theory that lays the foundation for understanding such systems, innovative algorithms and tools for their design, and a practical software platform used for ensuring reliability and sec ....Variable Structure Complex Network Systems with Smart Grid Applications. This project aims to establish a breakthrough theory and technology to help deliver reliability and security of complex network systems, which are subject to structure changes, against faults and cyberattacks. Expected outcomes include a new theory that lays the foundation for understanding such systems, innovative algorithms and tools for their design, and a practical software platform used for ensuring reliability and security of such systems. It will be applied directly to critical infrastructure such as the national power grid to help maintain lifeline resilience and achieve economic benefits. It will also provide an opportunity to train the next generation engineers in this cutting-edge technology for Australia.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