Harmonic analysis of differential operators in Banach spaces. This proposal aims to develop harmonic analysis (the mathematical tools used in digital music and photography) in new contexts. It focuses on boundary value problems (the theory behind medical or geological imaging) and stochastic equations (which describe phenomena with random components such as the behaviour of financial markets).
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
Fundamental investigation of heat and mass transfer in nanofluids: a mechanistic approach. This project aims to develop a mathematical model in order to predict complex boiling in using nanofluids as new coolant for heat removal. Implementation and resultant computer codes thereafter will provide industries with significant benefits and reduce times and costs in their future design of ultra-high efficient heat removal systems.
Discovery Early Career Researcher Award - Grant ID: DE120100163
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Modelling and simulation of instabilities in unsaturated soils due to wetting. Ground instabilities due to wetting are a critical issue that will be investigated through this project via the development of risk assessment tools. A rational engineering approach and calculation framework will be developed in order to predict failures and facilitate the design of new safer structures.
Discovery Early Career Researcher Award - Grant ID: DE210101344
Funder
Australian Research Council
Funding Amount
$364,981.00
Summary
Advancing genomic-driven infectious diseases modelling. Emerging infectious diseases and antimicrobial resistance are among the greatest threats to Australian health and agriculture, and current surveillance tools may fail to detect and mitigate infectious disease outbreaks in real time. This project will develop advanced phylodynamic methods (i.e., mathematical models of infectious disease transmission and pathogen evolution) to enable real-time surveillance of infectious disease outbreaks as t ....Advancing genomic-driven infectious diseases modelling. Emerging infectious diseases and antimicrobial resistance are among the greatest threats to Australian health and agriculture, and current surveillance tools may fail to detect and mitigate infectious disease outbreaks in real time. This project will develop advanced phylodynamic methods (i.e., mathematical models of infectious disease transmission and pathogen evolution) to enable real-time surveillance of infectious disease outbreaks as they emerge and monitor levels of drug resistance.Read moreRead less
Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provi ....Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provide a new way of fitting a wide class of statistical models to evolutionary data, in a very general setting. Further, this project will unite current methodology in a broader framework so that the proposed new methods are a generalisation of currently accepted theory. The outcomes will include a freely-available software package that implements the methods in a user-friendly form.Read moreRead less
Congestion control of networks: a unified stochastic framework. Systems such as the internet, wireless networks and the power grid require efficient allocation of shared resources. This research will develop ways to reduce delays in the internet and allow for growth in the power grid, without requiring additional infrastructure.
Advanced matrix-analytic methods with applications. Over the last twenty-five years, matrix-analytic methods have proved to be very successful in formulating and analysing certain classes of stochastic models. Motivated by applications, this project will investigate more advanced matrix-analytic methods than have hitherto been studied.
Discovery Early Career Researcher Award - Grant ID: DE160100999
Funder
Australian Research Council
Funding Amount
$295,020.00
Summary
Applying forward-backward stochastic differential equations to optimisation. This project intends to develop new ways to solve optimisation problems that are currently difficult to solve because of their complexity and size. In particular, forward–backward stochastic differential equations (FBSDEs) are a new technique that is showing ways to solve problems for which there is yet to be a solution. This project's focus will be on problems that cannot use existing software because the decision-maki ....Applying forward-backward stochastic differential equations to optimisation. This project intends to develop new ways to solve optimisation problems that are currently difficult to solve because of their complexity and size. In particular, forward–backward stochastic differential equations (FBSDEs) are a new technique that is showing ways to solve problems for which there is yet to be a solution. This project's focus will be on problems that cannot use existing software because the decision-making processes require intensive consideration of all possible outcomes in the modelled environment. In comparison to previous optimisation methods, the FBSDE approach is easier to work with and much more informative. The project's main potential applications are multiplayer games with mean-field interaction and financial markets with partial information.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