Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in bi ....Efficient learning from multiple brain imaging data sets. Brain imaging data analysis methods have proven to be very effective in the study of brain functions and the identification of brain disorders because they minimise the modelling assumptions on the underlying structure of the problem. Analysis of multiple brain imaging data sets, either of the same modality as in multitask or multisubject data sets or from different modalities as in the case of data fusion, is a challenging problem in biomedical image analysis. This project will lead to fundamental contributions as well as techniques that address both problems: extraction of relevant features information from multisubject brain imaging data sets of the same modality or from fusion of brain imaging data sets collected from multimodalities.Read moreRead less
A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, th ....A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, this project seeks to develop new distributed solutions for statistical estimation, which are specifically designed for dynamic systems with multiple object states, and are inherently scalable and robust. The potential benefits include new technologies for smart cities, autonomous infrastructure, and digital productivity.Read moreRead less
Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expecte ....Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expected outcomes are algorithms for public and private sector data curators to dial up or down their data access arrangements based on privacy risks and fidelity demands linked with different data types and uses. This project intends to enable Australians to securely benefit from valuable data in decision making.Read moreRead less
Ultrahigh-speed optical transport for sustaining the internet growth. Our society has entered an information era centred around the Internet. This project aims to study novel transport technologies to construct optical backbone networks supporting the Internet traffic. The project will keep Australia at the leading edge of exciting Terabit technologies as well as create commercial opportunities in Australia.
Parameter estimation for genetic time-series data: Theory and methods. This project aims to develop a novel computational framework for solving parameter estimation problems in evolutionary modelling by leveraging genetic time-series data measured by Next-Generation Sequencing technologies. It will foster international collaboration, cutting across disciplines. By introducing new techniques from signal processing and tools from random matrix theory commonly employed for mobile wireless communica ....Parameter estimation for genetic time-series data: Theory and methods. This project aims to develop a novel computational framework for solving parameter estimation problems in evolutionary modelling by leveraging genetic time-series data measured by Next-Generation Sequencing technologies. It will foster international collaboration, cutting across disciplines. By introducing new techniques from signal processing and tools from random matrix theory commonly employed for mobile wireless communications, it seeks to design scalable inference methods for resolving mutational fitness effects from genetic time-series measurements of complex evolving populations. This would enable new understanding of complex adaptive systems, such as pathogen evolution, host-immune dynamics, and acquisition of drug resistance. Read moreRead less
Explicit methods in number theory: Computation, theory and application. This project aims to use explicit estimates to unify three problems in number theory: primitive roots, Diophantine quintuples, and linear independence of zeroes of the Riemann zeta-function. It will use computational and analytic number theory to reduce the quintuples problem to a soluble level. Pursuing relations between the zeta zeroes will overhaul many current results. This project will apply its findings about primitive ....Explicit methods in number theory: Computation, theory and application. This project aims to use explicit estimates to unify three problems in number theory: primitive roots, Diophantine quintuples, and linear independence of zeroes of the Riemann zeta-function. It will use computational and analytic number theory to reduce the quintuples problem to a soluble level. Pursuing relations between the zeta zeroes will overhaul many current results. This project will apply its findings about primitive roots to signal processing, cryptography and cybersecurity.Read moreRead less
Real-Time Searches for Gravitational Waves and Identification of Their Radio and Optical Counterparts. The proposed project will directly address the national research priority in development of frontier technologies, directly involve Australians in frontier work in gravitational wave astronomy that will result in break-through sciences and improve the chance of the international Square-Kilometer-Array project being sited at Australia. In addition, it will foster a close collaboration of top int ....Real-Time Searches for Gravitational Waves and Identification of Their Radio and Optical Counterparts. The proposed project will directly address the national research priority in development of frontier technologies, directly involve Australians in frontier work in gravitational wave astronomy that will result in break-through sciences and improve the chance of the international Square-Kilometer-Array project being sited at Australia. In addition, it will foster a close collaboration of top international researchers with an Australian team. The research at The University of Western Australia will attract students from around the world and serve to educate and inspire young people in Australia.Read moreRead less
Improved decoding of human brain activity using advanced functional magnetic resonance imaging at ultra-high field strength. Using advanced MRI methods at ultra-high field, this project aims to enable the decoding and reconstruction of visual stimuli, as well as imagined ones from small functional units (layers and columns) in the human brain in vivo. This will be made possible by the use of a new functional MRI method, concurrent high temporal and spatial resolution and whole brain coverage as ....Improved decoding of human brain activity using advanced functional magnetic resonance imaging at ultra-high field strength. Using advanced MRI methods at ultra-high field, this project aims to enable the decoding and reconstruction of visual stimuli, as well as imagined ones from small functional units (layers and columns) in the human brain in vivo. This will be made possible by the use of a new functional MRI method, concurrent high temporal and spatial resolution and whole brain coverage as well as high sensitivity and specificity. Additionally, it will advance the development of functional connectomics and the aid the parcellation of the human cortex.Read moreRead less
Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected ....Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected outcomes include new-generation theories and methods for the unsupervised learning of complex interactions in real-life big data, which are anticipated to enable the intrinsic processing of big data complexities and substantially enhance Australia’s leadership in frontier data science research and applications. Read moreRead less
The role of human single-stranded binding protein (hSSB1) in DNA damage repair and tumorogenesis. Cancer is a leading cause of disease related death world wide, accounting for over 13% of all deaths in 2007. Approximately 38,000 people died in Australia from cancer in 2005. Cancer results from a single cell losing a vital part of its genetic information, this results in the cell losing its normal programming and initiates a process of rapid growth and multiplication. This research project aims t ....The role of human single-stranded binding protein (hSSB1) in DNA damage repair and tumorogenesis. Cancer is a leading cause of disease related death world wide, accounting for over 13% of all deaths in 2007. Approximately 38,000 people died in Australia from cancer in 2005. Cancer results from a single cell losing a vital part of its genetic information, this results in the cell losing its normal programming and initiates a process of rapid growth and multiplication. This research project aims to look at the mechanisms that exist to prevent this initial loss of genetic material within an individual cell. It further aims to translate theses discoveries into the clinic, providing new tools for diagnosis and prognosis of specific cancers and to establish links with major pharmaceutical companies to develop novel anticancer therapies.Read moreRead less