Interrogation and estimation of differential equation networks. Complex networks occur in many physical processes, in bridges and buildings and in small nanoscale systems like carbon nanotubes. Similar systems arise in electronics, photonics, and social networks. This project aims to determine optimal measurement regimes to estimate their dynamical states, and to find the limits of that estimation process.
Perturbations in Complex Systems and Games. This project aims to: advance the perturbation theory of dynamic and stochastic games; further develop approximations of infinite dimensional linear programs by their finite dimensional counterparts, and by finding asymptotic limits of spaces of occupational measures, by solution of successive layers of fundamental equations; explain and quantify the "exceptionality" of instances of systems that are genuinely difficult to solve; and, capitalise on the ....Perturbations in Complex Systems and Games. This project aims to: advance the perturbation theory of dynamic and stochastic games; further develop approximations of infinite dimensional linear programs by their finite dimensional counterparts, and by finding asymptotic limits of spaces of occupational measures, by solution of successive layers of fundamental equations; explain and quantify the "exceptionality" of instances of systems that are genuinely difficult to solve; and, capitalise on the outstanding performance of our Snakes-and-Ladders Heuristic (SLH) for the solution of the Hamiltonian cycle problem to identify its "fixed complexity orbits" and generalise this notion to other NP-complete problems.Read moreRead less
Modelling, forecasting, and control for econometrics based on generalized dynamic factor models: a system theoretic approach. The project will provide a tool that will assist organizations wishing to understand the dynamics of a national economy to model it, and to forecast future econometric time series values. Such ability will provide another tool to econometric managers, including the Reserve Bank , Treasury and fund managers, that should benefit the Australian nation.
Information theoretic approaches to optimise genome wide association studies with application to continuous and discrete traits. This project aims to develop new mathematical methods to find genetic associations from new genome-wide studies of colorectal cancer and breast cancer risk factors. If successful, this will result in improved use of expensive genetic data to better predict and understand diseases, conditions and other characteristics for humans, animals and plants.
Discovery Early Career Researcher Award - Grant ID: DE210101352
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Inverting the Signature Transform for Rough Paths and Random Processes. The signature transform provides an effective summary of the essential information encoded in multidimensional paths that are highly oscillatory and involve complicated randomness. The main goal of this project is to develop new algorithmic methods to reconstruct rough paths and random processes from the signature transform at various quantitative levels. This project expects to make theoretical breakthrough on the significa ....Inverting the Signature Transform for Rough Paths and Random Processes. The signature transform provides an effective summary of the essential information encoded in multidimensional paths that are highly oscillatory and involve complicated randomness. The main goal of this project is to develop new algorithmic methods to reconstruct rough paths and random processes from the signature transform at various quantitative levels. This project expects to make theoretical breakthrough on the significant open problem of signature inversion, thereby advancing knowledge in the areas of rough path theory and stochastic analysis. The newly developed methods will be utilised in combination with the emerging signature-based approach to study important problems in financial data analysis and visual speech recognition.
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Generalised Linear Mixed Models: Theory, Methods and New Areas of Application. This project will aid the analysis of complex data sets throughout Australia. The ensuing methodology and software products will be applicable to data arising from longitudinal and geo-referenced public health and biomedical studies being conducted in Australia. It will also aid analysis of complex survey data from the Australian Bureau of Statistics and other agencies. Part of this project is geared towards smart inf ....Generalised Linear Mixed Models: Theory, Methods and New Areas of Application. This project will aid the analysis of complex data sets throughout Australia. The ensuing methodology and software products will be applicable to data arising from longitudinal and geo-referenced public health and biomedical studies being conducted in Australia. It will also aid analysis of complex survey data from the Australian Bureau of Statistics and other agencies. Part of this project is geared towards smart information use in Australian industries and will help foster collaboration between mathematical scientists and members of the Australian business sector. Cancer research in Australia will also benefit from this project.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102388
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
From Bayesian filtering to smoothing and prediction for multiple object systems. This project will develop new and improved algorithms for tracking multiple targets, such as tanks, submarines or planes, using the state of the art in mathematical and computational design. These will enable more efficient and accurate technologies for defence related applications including intelligence, surveillance and reconnaissance.
Parameter estimation for multi-object systems. Parameter estimation in multi-object system is essential to the application of multi-object filtering to a wider range of practical problems with social and commercial benefits. This project develops the necessary parameter estimation techniques for complete 'plug-and-play' multi-object filtering solutions that facilitates widespread applications.
Australian Laureate Fellowships - Grant ID: FL110100281
Funder
Australian Research Council
Funding Amount
$2,777,066.00
Summary
Large-scale statistical machine learning. This research program aims to develop the science behind statistical decision problems as varied as web retrieval, genomic data analysis and financial portfolio optimisation. Advances will have a very significant practical impact in the many areas of science and technology that need to make sense of large, complex data streams.
Modelling patient flows through hospitals: optimizing effective use of resources. Hospitals are complex, dynamic systems confronted by increased demand in the face of shrinking real capacity. Managing such systems is currently undertaken with sub-optimal analytical support, particularly when demand and capacity are changing and resources must be manipulated to respond to such changes. In this project, the investigators will apply a mathematical modelling approach to the analysis of hospital pati ....Modelling patient flows through hospitals: optimizing effective use of resources. Hospitals are complex, dynamic systems confronted by increased demand in the face of shrinking real capacity. Managing such systems is currently undertaken with sub-optimal analytical support, particularly when demand and capacity are changing and resources must be manipulated to respond to such changes. In this project, the investigators will apply a mathematical modelling approach to the analysis of hospital patient flows. Furthermore, they will employ statistical process control methodologies to the problem of recognising and responding to changes in the flows, so that performance objectives are met. In doing this, they will give health service managers and clinicians a significant advantage in deciding how best to manage a constrained resource to maximize access, throughput and patient outcomes.Read moreRead less