Quantification of whole brain structural connectivity and fibre densities. The project is intended to develop and improve accuracy in tools used to measure brain connections. Its overall aim is to produce definitive evidence of the biological accuracy of quantitative measures of brain structural connectivity as derived from diffusion magnetic resonance imaging (MRI). Discovery in the quantitative field of MRI research is important to worldwide efforts to identify the human ‘connectome’. The proj ....Quantification of whole brain structural connectivity and fibre densities. The project is intended to develop and improve accuracy in tools used to measure brain connections. Its overall aim is to produce definitive evidence of the biological accuracy of quantitative measures of brain structural connectivity as derived from diffusion magnetic resonance imaging (MRI). Discovery in the quantitative field of MRI research is important to worldwide efforts to identify the human ‘connectome’. The project plans to bring together novel diffusion MRI post-processing methods and state-of-the-art 3-D glass-brain histology techniques using mice. Investment in MRI research that specifically addresses methods to accurately measure structural brain connectivity may ultimately contribute to improving non-invasive imaging methods.Read moreRead less
Cloud-data centres resource allocation under bursty conditions. Cloud-data centres resource allocation under bursty conditions. The project aims to design, implement, and integrate solutions to manage resources in cloud data centres (CDCs), especially when operating under bursty workload conditions. CDCs are expected to assure performance whilst optimising resource usage at a minimum cost, but efficiently providing resources with specific performance requirements can be difficult. This project i ....Cloud-data centres resource allocation under bursty conditions. Cloud-data centres resource allocation under bursty conditions. The project aims to design, implement, and integrate solutions to manage resources in cloud data centres (CDCs), especially when operating under bursty workload conditions. CDCs are expected to assure performance whilst optimising resource usage at a minimum cost, but efficiently providing resources with specific performance requirements can be difficult. This project intends to develop scalable solutions with industry approved software plug-ins. This is expected to affect both trustworthy information and communications technology (ICT) infrastructure (delivering more resilient CDCs) and economic sustainability (reducing CDC usage cost for both users and providers) of today’s computerised society.Read moreRead less
Contention-Aware Scheduling in Cloud Data Centres. This project aims to design, implement, and integrate solutions to improve resource use of private cloud data centres (CDCs). CDCs are expected to guarantee performance while optimising resource usage at a minimum cost. This incurs technical challenges that must be tackled to efficiently provision on-demand resources with specific performance requirements. The project intends to push the applicability of both current techniques and the ones to b ....Contention-Aware Scheduling in Cloud Data Centres. This project aims to design, implement, and integrate solutions to improve resource use of private cloud data centres (CDCs). CDCs are expected to guarantee performance while optimising resource usage at a minimum cost. This incurs technical challenges that must be tackled to efficiently provision on-demand resources with specific performance requirements. The project intends to push the applicability of both current techniques and the ones to be designed in this project to industry-scale CDCs, and identify metrics and variables to holistically control service-level agreements of hosted applications. Scalable solutions with industry approved software plug-ins are the major outcomes of this project. The outcomes of this project will have a substantial impact on both environmental (lowering energy consumption to lead to greener infrastructure) and economic sustainability (reducing cloud usage cost for both users and providers) of today’s much computerised society.Read moreRead less
Energy-Efficient Computing: Expanding the Role of Scheduling in Cloud Data Centres. Cloud data centres have become increasingly large-scale to meet ever increasing computing and storage capacity. The requirement of uninterrupted service availability has also contributed to such expansion. However, this relentless pursuit of high performance and high availability has led to serious resource over-provisioning and, in turn, low performance to energy consumption ratios. The impact of this poor resou ....Energy-Efficient Computing: Expanding the Role of Scheduling in Cloud Data Centres. Cloud data centres have become increasingly large-scale to meet ever increasing computing and storage capacity. The requirement of uninterrupted service availability has also contributed to such expansion. However, this relentless pursuit of high performance and high availability has led to serious resource over-provisioning and, in turn, low performance to energy consumption ratios. The impact of this poor resource management goes beyond the issue of cloud data centre efficiency, including excessive carbon footprint. This project aims to develop new energy-aware scheduling and resource allocation algorithms to provide energy-efficient solutions. These solutions exploit both workload and system diversity in cloud data centres.Read moreRead less
Unlocking the potential for linear and discrete optimisation in knot theory and computational topology. Computational topology is a young, energetic field that uses computers to solve complex geometric problems, such as whether a loop of string is tangled. Such computations are becoming increasingly important in mathematics, and applications span biology, physics and information sciences, however many core problems in the field remain intractable for all but the simplest cases. This project unit ....Unlocking the potential for linear and discrete optimisation in knot theory and computational topology. Computational topology is a young, energetic field that uses computers to solve complex geometric problems, such as whether a loop of string is tangled. Such computations are becoming increasingly important in mathematics, and applications span biology, physics and information sciences, however many core problems in the field remain intractable for all but the simplest cases. This project unites geometric techniques with powerful methods from operations research, such as linear and discrete optimisation, to build fast, powerful tools that can for the first time systematically solve large topological problems. Theoretically, this project has significant impact on the famous open problem of detecting knottedness in fast polynomial time.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100762
Funder
Australian Research Council
Funding Amount
$309,609.00
Summary
The interplay between structures and algorithms in combinatorial optimisation. Networks are ubiquitous in science, technology, and virtually all aspects of life. The project aims to make progress on central questions in the mathematical theory of networks. These include designing efficient algorithms for approximating the Hadwiger number, which is a key measure of the complexity of a network.
Discovery Early Career Researcher Award - Grant ID: DE120101375
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
The Tutte polynomial of a graph: correlations, approximations and applications. The Tutte polynomial is a mathematical function of central importance to diverse fields of research, such as network reliability and statistical mechanics, that involve natural (and often difficult) counting problems. This project aims to obtain useful close approximations of this function with immediate applications in all these research fields.
New Efficient Cryptographic Tools for Data Privacy and Software Protection. Online services for collaborative communication and software distribution are commonplace today, but their use is hampered by data privacy breaches and intellectual property violations via software reverse engineering. Recent theoretical breakthroughs in cryptography promise to provide new powerful tools for solving these problems, but these tools are not yet suitable for practical use, due to their low efficiency and a ....New Efficient Cryptographic Tools for Data Privacy and Software Protection. Online services for collaborative communication and software distribution are commonplace today, but their use is hampered by data privacy breaches and intellectual property violations via software reverse engineering. Recent theoretical breakthroughs in cryptography promise to provide new powerful tools for solving these problems, but these tools are not yet suitable for practical use, due to their low efficiency and a lack of solid security foundations. This project aims to apply algebraic and probabilistic techniques to improve efficiency of existing tools, and the understanding of their security. Outcomes are expected to include new insights in cryptographic theory, and new practical tools for cyber security.Read moreRead less
Identifying technological trajectories using machine learning algorithms. This project aims to improve our understanding of why scientific knowledge progresses in certain directions and what causes it to grow faster or slower across fields. The project will create new neural-network machine-learning algorithms to scan patent and scientific article texts (specifications and claims) for natural language concepts. The results will potentially be used by patent offices to improve their own database ....Identifying technological trajectories using machine learning algorithms. This project aims to improve our understanding of why scientific knowledge progresses in certain directions and what causes it to grow faster or slower across fields. The project will create new neural-network machine-learning algorithms to scan patent and scientific article texts (specifications and claims) for natural language concepts. The results will potentially be used by patent offices to improve their own database search, by business analytics companies to reveal new technologies and potential collaborators, and by academic economists to understand how knowledge travels and accumulates.
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Next-generation techniques for analysing massive data sets. To process enormous amounts of data, leading computing companies are turning to modern computing frameworks, for which little theory of efficient computational techniques has been developed. This project will resolve key theoretical questions and provide fast techniques for poorly understood pattern recognition and bioinformatics problems.