Advanced Bayesian Inversion Algorithms for Wave Propagation. This project aims to improve algorithms for detecting hidden items by developing new computational mathematical techniques capable of reconstructing the shape and location of objects using electromagnetic waves. This project expects to generate new knowledge in the areas of Bayesian Inversion and computational wave propagation. Expected outcomes of this project are algorithms that can be developed for use in nonintrusive radio wave sec ....Advanced Bayesian Inversion Algorithms for Wave Propagation. This project aims to improve algorithms for detecting hidden items by developing new computational mathematical techniques capable of reconstructing the shape and location of objects using electromagnetic waves. This project expects to generate new knowledge in the areas of Bayesian Inversion and computational wave propagation. Expected outcomes of this project are algorithms that can be developed for use in nonintrusive radio wave security scanners. This should provide benefits such as the capability to scan a crowd without a checkpoint, which will have the potential to improve security in public places.Read moreRead less
Interface-aware numerical methods for stochastic inverse problems. This project aims to design novel high-performance numerical tools for solving large-scale forward and inverse problems dominated by stochastic interfaces and quantifying associated uncertainties. In real-world applications such as groundwater, these tools are instrumental for assimilating big datasets into mathematical models for providing reliable predictions. By advancing and integrating high-order polytopal schemes, multileve ....Interface-aware numerical methods for stochastic inverse problems. This project aims to design novel high-performance numerical tools for solving large-scale forward and inverse problems dominated by stochastic interfaces and quantifying associated uncertainties. In real-world applications such as groundwater, these tools are instrumental for assimilating big datasets into mathematical models for providing reliable predictions. By advancing and integrating high-order polytopal schemes, multilevel methods, transport maps, and dimension reduction, this project's anticipated outcomes are highly accurate and cost-efficient numerical schemes, certified by rigorous mathematical analysis. This should provide data-centric simulation tools with enhanced reliability, for engineering and scientific applications.Read moreRead less
Uncertainty on spheres and shells: mathematics and methods for applications. This project aims to develop new mathematics and mathematically rigorous approximation methods for physical problems on spherical geometries in the presence of uncertainty. Many physical phenomena are modelled on either a sphere or a spherical shell. Such models typically have large uncertainty in the input data, through uncertainty in model coefficients, forcing terms, geometry or boundary conditions. Yet their stochas ....Uncertainty on spheres and shells: mathematics and methods for applications. This project aims to develop new mathematics and mathematically rigorous approximation methods for physical problems on spherical geometries in the presence of uncertainty. Many physical phenomena are modelled on either a sphere or a spherical shell. Such models typically have large uncertainty in the input data, through uncertainty in model coefficients, forcing terms, geometry or boundary conditions. Yet their stochastic modelling and subsequent numerical analysis in the presence of uncertainty are still in their infancy. This project will conduct numerical analysis, stochastic analysis and approximation to address such problems.Read moreRead less
Novel Mathematics and Efficient Computational Techniques for Human Vision. This project aims to develop a new mathematical framework to understand elastic properties of human corneas. The project expects to generate new knowledge in understanding bio-mechanical models for human corneas, as well as other engineering applications involving materials with random fluctuations of elasticity. Expected outcomes of this project include new mathematics and computational algorithms for solving complex mat ....Novel Mathematics and Efficient Computational Techniques for Human Vision. This project aims to develop a new mathematical framework to understand elastic properties of human corneas. The project expects to generate new knowledge in understanding bio-mechanical models for human corneas, as well as other engineering applications involving materials with random fluctuations of elasticity. Expected outcomes of this project include new mathematics and computational algorithms for solving complex mathematical equations which describe elastic and hyper-elastic materials such as human corneas. This project will benefit Australia by enhancing the standing in cutting edge research trends in computational mathematics such as uncertainty quantification and machine learning.Read moreRead less
High Dimensional Approximation, Learning, and Uncertainty. This project aims to develop next-generation computational methods for complex problems in science and engineering that have many uncertain parameters, using advanced high-dimensional strategies and deep learning to enhance computational speed. The significance of the project is that these methods will help address important applications that at present are not feasible or at the edge of feasibility. The expected outcomes are powerful me ....High Dimensional Approximation, Learning, and Uncertainty. This project aims to develop next-generation computational methods for complex problems in science and engineering that have many uncertain parameters, using advanced high-dimensional strategies and deep learning to enhance computational speed. The significance of the project is that these methods will help address important applications that at present are not feasible or at the edge of feasibility. The expected outcomes are powerful methods that will be mathematically rigorous and suitable for a wide variety of applications. The benefits are that the project will boost Australia’s position as a leader in innovation, and contribute to future developments over a wide area, from aerospace engineering to personalised computational oncology.Read moreRead less
High Dimensional Computation and Uncertainty. This project aims to establish powerful computational methods for high-dimensional problems - methods that are rigorous, and carefully tailored to specific applications, from physics, environment, manufacturing and finance, and often driven by uncertainty. The project will generate new knowledge in the area of high-dimensional computation, and develop technological innovations in key areas of science and industry. Expected outcomes include improved c ....High Dimensional Computation and Uncertainty. This project aims to establish powerful computational methods for high-dimensional problems - methods that are rigorous, and carefully tailored to specific applications, from physics, environment, manufacturing and finance, and often driven by uncertainty. The project will generate new knowledge in the area of high-dimensional computation, and develop technological innovations in key areas of science and industry. Expected outcomes include improved control of uncertainty in industry, enhanced international and interdisciplinary collaborations, and significant publications and presentations in international forums. The technological advancements will help boost Australia's position as a world leader in innovation.Read moreRead less
Geometry in projection methods and fixed-point theory. This project aims to resolve mathematical challenges arising from problems with specific structure typical for key modern applications, such as big data optimisation, chemical engineering and medical imaging. We focus on developing new mathematical tools for the analysis of projection methods and accompanying fixed point theory, specifically targeting the refinement of the geometric intuition for algorithm design techniques to inform the imp ....Geometry in projection methods and fixed-point theory. This project aims to resolve mathematical challenges arising from problems with specific structure typical for key modern applications, such as big data optimisation, chemical engineering and medical imaging. We focus on developing new mathematical tools for the analysis of projection methods and accompanying fixed point theory, specifically targeting the refinement of the geometric intuition for algorithm design techniques to inform the implementation of optimal methods for huge-scale optimisation problems.Read moreRead less
Mathematics for future magnetic devices. The aim of this project is to develop a mathematical theory and numerical models of stochastic partial differential
equations for magnetic nano-structures. Such materials will yield next-generation magnetic memories with up to
three orders of magnitude faster switching speeds and dramatically increased data storage density. New
mathematical theories will help understand their sensitivity to small random fluctuations that can destroy stored
information. Th ....Mathematics for future magnetic devices. The aim of this project is to develop a mathematical theory and numerical models of stochastic partial differential
equations for magnetic nano-structures. Such materials will yield next-generation magnetic memories with up to
three orders of magnitude faster switching speeds and dramatically increased data storage density. New
mathematical theories will help understand their sensitivity to small random fluctuations that can destroy stored
information. This project aims to revolutionise mathematical modelling of magnetic memories and put Australia at
the forefront of international research. Technological advances to create much smaller and faster memory devices
are expected to enable groundbreaking ways of managing and mining big dataRead moreRead less
Approximate algorithms and architectures for area efficient system design. This project aims to develop simpler but reliable image recognition systems that can run on low-cost, small-scale platforms, for use in driver monitoring system (DMS) applications. Cheaper reliable DMS will lead to wider availability of this technology to end users and improve safety of motor vehicles. This project will develop approximate algorithmic and circuit techniques, provide training for research students and buil ....Approximate algorithms and architectures for area efficient system design. This project aims to develop simpler but reliable image recognition systems that can run on low-cost, small-scale platforms, for use in driver monitoring system (DMS) applications. Cheaper reliable DMS will lead to wider availability of this technology to end users and improve safety of motor vehicles. This project will develop approximate algorithmic and circuit techniques, provide training for research students and build capability in the area of approximate computing. It is also expected to lead to commercial products, licences and revenue, which will enable new job creation.
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Pseudorandomness in Number Theory, Dynamics and Cryptography. The aim of the project is to investigate various aspects of randomness, design new and analyse previously known constructions of randomness extractors of practical use. As a dual aim, we will also investigate the pseudorandomness of some classical number-theoretic objects. The significance of this project is in a large number of theoretical and practical applications and in new methods which will be developed. Expected outcomes includ ....Pseudorandomness in Number Theory, Dynamics and Cryptography. The aim of the project is to investigate various aspects of randomness, design new and analyse previously known constructions of randomness extractors of practical use. As a dual aim, we will also investigate the pseudorandomness of some classical number-theoretic objects. The significance of this project is in a large number of theoretical and practical applications and in new methods which will be developed. Expected outcomes include new cryptographically strong hash functions and progress towards several famous open conjectures such as Sarnak’s conjecture. These new results and methods will be highly beneficial for both theoretical mathematics and also for such practical areas as cryptography and information security.Read moreRead less