Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algori ....Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algorithms for applied researchers. This project benefits not only advanced manufacturing by finding optimal stopping time for wood panel compression, but also superior forecasting for mortality in demography, climate data in environmental science, asset returns in finance, and electricity consumption in economics. Read moreRead less
New mathematical and statistical methods that inform the control of infectious disease outbreaks. Emerging infectious diseases are an ever-present threat to our community, as highlighted by the recent SARS epidemic and current fears concerning avian influenza. The research proposed by this project will help policy makers implement effective border control and outbreak control against a variety of emerging and re-emerging infectious diseases, including SARS, influenza and the deliberate release o ....New mathematical and statistical methods that inform the control of infectious disease outbreaks. Emerging infectious diseases are an ever-present threat to our community, as highlighted by the recent SARS epidemic and current fears concerning avian influenza. The research proposed by this project will help policy makers implement effective border control and outbreak control against a variety of emerging and re-emerging infectious diseases, including SARS, influenza and the deliberate release of an infectious disease such as smallpox. The project will enhance preparedness through a better understanding of the relative merits of different control strategies, and provide new methodology that can dynamically guide border and outbreak control in the midst of an outbreak by making effective use of data. Read moreRead less
Surveillance and sampling to maintain absence of pests and diseases. This project aims to develop empirically validated statistical and mathematical methods for industry and government to deliver more efficient biosecurity surveillance programs. The project endeavours to enhance biosecurity at the border and within Australia, while minimising the costs and burden of testing. Expected project outcomes include effective surveillance and sampling for high-priority threats, accessible software for d ....Surveillance and sampling to maintain absence of pests and diseases. This project aims to develop empirically validated statistical and mathematical methods for industry and government to deliver more efficient biosecurity surveillance programs. The project endeavours to enhance biosecurity at the border and within Australia, while minimising the costs and burden of testing. Expected project outcomes include effective surveillance and sampling for high-priority threats, accessible software for decision-makers, and generalisable approaches to address rapidly increasing biosecurity risks. Significant benefits include maintaining absence of key pathogens and pests in Australia.Read moreRead less