New mathematical approaches to learn the equations of life from noisy data. New mathematical models and mathematical modelling methods must be continually developed to interpret emerging biotechnology experiments. Contemporary research in tissue engineering involves growing tissues on 3d-printed scaffolds to mimic constrained in vivo geometries. Previous mathematical models of tissue growth focus on computationally expensive discrete mathematical models that are poorly suited for parameter infe ....New mathematical approaches to learn the equations of life from noisy data. New mathematical models and mathematical modelling methods must be continually developed to interpret emerging biotechnology experiments. Contemporary research in tissue engineering involves growing tissues on 3d-printed scaffolds to mimic constrained in vivo geometries. Previous mathematical models of tissue growth focus on computationally expensive discrete mathematical models that are poorly suited for parameter inference and experimental design. This project will deliver and deploy high-fidelity, computationally efficient moving boundary continuum mathematical models that will: (i) predict/interpret new experiments, (ii) provide quantitative insight into biological mechanisms, and (iii) enable reproducible experimental design.Read moreRead less
Computational modelling of nanofluids for industrial applications. The use of nanoparticles in heat transfer fluids, then known as nanofluids, increases their specific heat and thermal conductivity. Recent experimental works highlight that anomalous transport phenomena are evident in nanofluids that cannot be adequately described by classical conservation laws. We will extend these conservation laws to incorporate fractional operators to capture the fluid memory effects and the impact of particl ....Computational modelling of nanofluids for industrial applications. The use of nanoparticles in heat transfer fluids, then known as nanofluids, increases their specific heat and thermal conductivity. Recent experimental works highlight that anomalous transport phenomena are evident in nanofluids that cannot be adequately described by classical conservation laws. We will extend these conservation laws to incorporate fractional operators to capture the fluid memory effects and the impact of particle clustering. Computational modelling and experimental investigations will be undertaken to identify the heat transfer mechanisms of various nanofluids. The outcomes of the work will increase knowledge on nanofluids and offer a significant opportunity to improve the efficiency of many thermal engineering systems.Read moreRead less
Unpacking the immune system with applied mathematics. This project aims to model immune interactions across cells and structures spanning scales of nanometres to millimetres. It expects to develop innovative mathematical insights, improve our understanding of immunology, and consolidate collaborations with top American and European laboratories and groups. Expected outcomes include cutting-edge techniques for multiscale biological modelling and improved prediction and analysis of immune dynami ....Unpacking the immune system with applied mathematics. This project aims to model immune interactions across cells and structures spanning scales of nanometres to millimetres. It expects to develop innovative mathematical insights, improve our understanding of immunology, and consolidate collaborations with top American and European laboratories and groups. Expected outcomes include cutting-edge techniques for multiscale biological modelling and improved prediction and analysis of immune dynamics. The project should provide benefits to industries where highly organised behaviours are important, for example those interested in robot swarming, optimal transportation, and epidemic management. It should also benefit Australian students and researchers with novel overseas training opportunities.Read moreRead less
Mathematics to underpin and drive novel inertial microfluidic technologies. Particles suspended in flow through microfluidic ducts migrate under inertial and drag forcing to different regions in the cross-section depending on particle size, duct geometry and control parameters, enabling isolation of, for example, cancer cells/microplastics from a blood/water sample. Device design needs mathematical models yielding understanding of the particle dynamics, and tools for determining geometry and con ....Mathematics to underpin and drive novel inertial microfluidic technologies. Particles suspended in flow through microfluidic ducts migrate under inertial and drag forcing to different regions in the cross-section depending on particle size, duct geometry and control parameters, enabling isolation of, for example, cancer cells/microplastics from a blood/water sample. Device design needs mathematical models yielding understanding of the particle dynamics, and tools for determining geometry and control parameters. Particle boundary conditions strongly influence the inertial lift and drag forces that drive particle motion. This project will develop these mathematical tools for boundary conditions applicable to both passive and active particles, so driving development of novel devices for existing and new applications.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
Bushfire analytics: optimisation of fuel reduction. Bushfires are an integral part of the Australian ecosystem. However, their severity has been worsening rapidly over the past decade. This project aims to develop a principled and scalable methodology for optimising fuel treatment planning to reduce the potential for severe bushfires. This project expects to generate new knowledge in bushfire fuel management using a groundbreaking combination of mathematical modelling techniques and state-of-the ....Bushfire analytics: optimisation of fuel reduction. Bushfires are an integral part of the Australian ecosystem. However, their severity has been worsening rapidly over the past decade. This project aims to develop a principled and scalable methodology for optimising fuel treatment planning to reduce the potential for severe bushfires. This project expects to generate new knowledge in bushfire fuel management using a groundbreaking combination of mathematical modelling techniques and state-of-the-art optimisation methods. The expected outcomes should provide significant benefits to our nation's ability to respond and adapt to the impacts of environmental change on biological systems and urban and rural communities.Read moreRead less
Distributed Optimisation without Central Coordination. This project will develop the mathematical foundations for discovery and analysis of iterative methods for optimisation problems in distributed computing systems. Most methods in distributed optimisation were not designed for distributed computing, rather they were adapted for purpose post-hoc. By building on recent advances in monotone operator splitting, this project expects to develop a mathematical theory for decentralised optimisation a ....Distributed Optimisation without Central Coordination. This project will develop the mathematical foundations for discovery and analysis of iterative methods for optimisation problems in distributed computing systems. Most methods in distributed optimisation were not designed for distributed computing, rather they were adapted for purpose post-hoc. By building on recent advances in monotone operator splitting, this project expects to develop a mathematical theory for decentralised optimisation algorithms specially designed for distributed systems. The framework is expected to produce a suite of algorithms, each customised to exploit a specific network configuration. The project will provide significant benefits in distributed machine learning applications such as federated learning.Read moreRead less
Weather, climate & geological risks: derivative pricing & risk management. This project aims to create new mathematical models and approaches for the fair valuation and hedging of financial derivatives, tackling funding for climate change adaptation and catastrophic disaster risk management. Businesses use derivatives to strategically mitigate financial losses from adverse climate conditions and geological hazards. Expected outcomes are improved models for weather variables and hazard risk asses ....Weather, climate & geological risks: derivative pricing & risk management. This project aims to create new mathematical models and approaches for the fair valuation and hedging of financial derivatives, tackling funding for climate change adaptation and catastrophic disaster risk management. Businesses use derivatives to strategically mitigate financial losses from adverse climate conditions and geological hazards. Expected outcomes are improved models for weather variables and hazard risk assessment; richer methodology from the fusion of mathematical techniques, data analysis and earth sciences perspectives; and quantitative solutions to pressing societal concerns. Significant benefits also include highly qualified personnel training and international collaboration on common multidisciplinary research priorities.Read moreRead less
Development of a novel best approximation theory with applications . The aim of this project is to develop an innovative best approximation theory for complex fractional boundary value problems with discontinuities and with no compactness, and then apply the theory to study two classes of complex partial differential equation boundary value problems with industrial applications. The work will lead to the development of a new theory and a suite of innovative analytical and computational methods f ....Development of a novel best approximation theory with applications . The aim of this project is to develop an innovative best approximation theory for complex fractional boundary value problems with discontinuities and with no compactness, and then apply the theory to study two classes of complex partial differential equation boundary value problems with industrial applications. The work will lead to the development of a new theory and a suite of innovative analytical and computational methods for solving a wide range of nonlinear problems with singularities and non-local properties. The expected outcomes of the project will significantly advance our methods for the modelling and control of many industrial systems and processes.
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Understanding the mechanisms that inhibit and promote biofilm expansion. Yeasts have been used for biotechnology throughout recorded history. They are important human pathogens, and major experimental models of eukaryotic cells. Although yeasts are some of the most studied organisms in biology, their modes of colony biofilm formation are not fully understood. Methods to investigate the environmental and genetic processes that drive colony biofilm formation will be developed in this proposed pro .... Understanding the mechanisms that inhibit and promote biofilm expansion. Yeasts have been used for biotechnology throughout recorded history. They are important human pathogens, and major experimental models of eukaryotic cells. Although yeasts are some of the most studied organisms in biology, their modes of colony biofilm formation are not fully understood. Methods to investigate the environmental and genetic processes that drive colony biofilm formation will be developed in this proposed project. They will provide a deeper understanding of the mechanisms that inhibit and promote biofilm formation, and colonial morphology in the different modes of growth of Saccharomyces cerevisiae, with implications for this and other biofilm-forming yeasts of biotechnological or medical importance.Read moreRead less