Asset pricing with social interactions, adaptive learning, and differences in opinion. This project seeks to understand how social interactions and adaptive learning of investors affect asset prices in highly competitive and adaptive financial markets. It will develop an evolutionary asset pricing theory, novel empirical hypotheses and tests of financial market characteristics and provide implications for policy and market regulation.
Uncertainties in coherent transport of particles and intrinsic properties. This Project aims to quantify the uncertainty of a model output in terms of uncertainties in modelling assumptions, by developing new mathematical techniques and applying them to real-world data. This will be in the context of assessing the accuracy of tracking coherently moving structures (e.g., hurricanes, oceanic biodiversity hotspots, pollutant patches, insect swarms) from experimental/observational data sets. Novel, ....Uncertainties in coherent transport of particles and intrinsic properties. This Project aims to quantify the uncertainty of a model output in terms of uncertainties in modelling assumptions, by developing new mathematical techniques and applying them to real-world data. This will be in the context of assessing the accuracy of tracking coherently moving structures (e.g., hurricanes, oceanic biodiversity hotspots, pollutant patches, insect swarms) from experimental/observational data sets. Novel, data-tested, mathematical methods for uncertainty quantification of coherent structures will be developed as Project outcomes. Project benefits include new insights into protecting the environment, improved uncertainty quantification in climate modelling, and the generation of interdisciplinary knowledge and training.Read moreRead less
ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less
The mathematics of novel magnetic memory materials. Magnetic memories are the world’s principal device for storing information. The next generation will have greatly increased access speed and data-storage capacity. This project will develop the mathematical theory of these new magnetic memory materials, a crucial first step in understanding and being able to fine-tune their properties.
Software-defined provisioning of Internet of Things applications in fog computing systems. This project aims to investigate and provide solutions for the realisation of a seemingly integrated Fog Computing (FC) paradigm with cloud environments, networking devices and Internet of Things devices. Fog Computing (FC) is an emerging paradigm with great promises for advancing Information and Communications Technologies. Using interdisciplinary approaches, the project expects to generate new knowledge ....Software-defined provisioning of Internet of Things applications in fog computing systems. This project aims to investigate and provide solutions for the realisation of a seemingly integrated Fog Computing (FC) paradigm with cloud environments, networking devices and Internet of Things devices. Fog Computing (FC) is an emerging paradigm with great promises for advancing Information and Communications Technologies. Using interdisciplinary approaches, the project expects to generate new knowledge for optimising both hardware and software resources of a FC system. Outcomes of this project include practical solutions through building novel mathematical frameworks and optimisation objectives. The project is expected to provide efficient monitoring and control of intelligent spaces, management of urban and rural environments and will have applications in the areas of energy, security, transport and public health.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100741
Funder
Australian Research Council
Funding Amount
$382,274.00
Summary
Tractable Bayesian algorithms for intractable Bayesian problems. This project seeks to develop computationally efficient and scalable Bayesian algorithms to estimate the parameters of complex models and ensure inferences drawn from the models can be trusted. Bayesian parameter estimation and model validation procedures are currently computationally intractable for many complex models of interest in science and technology. These include biological processes such as the efficacy of heart disease, ....Tractable Bayesian algorithms for intractable Bayesian problems. This project seeks to develop computationally efficient and scalable Bayesian algorithms to estimate the parameters of complex models and ensure inferences drawn from the models can be trusted. Bayesian parameter estimation and model validation procedures are currently computationally intractable for many complex models of interest in science and technology. These include biological processes such as the efficacy of heart disease, wound healing and skin cancer treatments. Potential outcomes of the project include new algorithms to significantly economise computations and improved understanding of the mechanisms of experimental data generation. Improved models of wound healing, skin cancer growth and heart physiology supported by these algorithms could improve population health.Read moreRead less
Random network models with applications in biology. Complex biological systems consist of a large number of interacting agents or components, and so can be studied using mathematical random network models. We aim to gain deeper insights into the laws emerging as the random networks evolve in time. This can help us to deal with dangerous disease epidemics and better understand the human brain.
Modelling dynamics in spatial ecology. This project addresses how birth, death and movement drive patterns of plants and animals in space and time. We aim to apply and extend dynamical statistical models grounded in theory. Dynamical models are needed for us to understand how species and ecological communities respond to environmental change and disturbance including bushfires, climate change and extremes and species invasion. Using data from forest plots and animal movement, we aim to understan ....Modelling dynamics in spatial ecology. This project addresses how birth, death and movement drive patterns of plants and animals in space and time. We aim to apply and extend dynamical statistical models grounded in theory. Dynamical models are needed for us to understand how species and ecological communities respond to environmental change and disturbance including bushfires, climate change and extremes and species invasion. Using data from forest plots and animal movement, we aim to understand influences on individuals and species, and how to use that to generate robust predictions. The project is expected to produce statistical models and software for use by ecologists. This should help predict, and manage, ecological impacts of environmental change and disturbances.Read moreRead less
Retirement income product innovation. This project aims to develop and assess comprehensive retirement income products to support sustainable retirement income streams for the Australian superannuation system. It will provide a framework to develop flexible structured retirement income products, taking into account the fair and effective allocation of costs and risks. Actuarial and financial analysis will highlight savings in Age Pension and aged care costs arising from more effective design of ....Retirement income product innovation. This project aims to develop and assess comprehensive retirement income products to support sustainable retirement income streams for the Australian superannuation system. It will provide a framework to develop flexible structured retirement income products, taking into account the fair and effective allocation of costs and risks. Actuarial and financial analysis will highlight savings in Age Pension and aged care costs arising from more effective design of retirement income products incorporating investment and longevity risk. It intends to develop risk sharing retirement products, risk management strategies, and longevity index-based hedging contracts to share and mitigate financial and longevity risk.Read moreRead less
Stochastic modelling of genetic regulatory networks with burst process. This project will develop the next generation of stochastic modelling to study the fundamental principles of genetic regulation. Simulations will yield deeper insight into the origin of bistability and oscillation in gene networks.