Trisections, triangulations and the complexity of manifolds. This project aims at practical representations of 3-dimensional and 4-dimensional spaces as needed in applications. Topology is the mathematical study of the shapes of spaces. Geometry endows spaces with additional structure such as distance, angle and curvature. Special combinatorial structures, such as minimal triangulations, are often closely connected to geometric structures or topological properties. This project aims to construct ....Trisections, triangulations and the complexity of manifolds. This project aims at practical representations of 3-dimensional and 4-dimensional spaces as needed in applications. Topology is the mathematical study of the shapes of spaces. Geometry endows spaces with additional structure such as distance, angle and curvature. Special combinatorial structures, such as minimal triangulations, are often closely connected to geometric structures or topological properties. This project aims to construct computable invariants, connectivity results for triangulations, and algorithms to recognise fundamental topological properties and structures such as trisections and bundles.Read moreRead less
Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require c ....Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require computational techniques that run extremely efficiently. The project expects to develop and improve approximate data structures that operate in tight resource bounds. Anticipated outcomes are improved event recognition and dramatic speedup in analysis of streams in areas such as finance, health, transport, and urban data.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.
Read moreRead less
Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results th ....Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results that depend on the perceived state of the querier. This project will develop indexing and search techniques for massive structured data sets. The new search methods will incorporate theoretical advances and will be experimentally validated using industry-standard open-source distributed systems.Read moreRead less
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.
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
Efficient Compression and Querying Techniques for Massive Text Collections. Web search services have become a fundamental tool used by governments, businesses, and individuals, and play a key role in our access to knowledge and information. In this project we aim to develop new techniques for representing the indexes at the heart of web search services, and to devise new processing algorithms with reduced resource requirements for resolving queries and providing useful and topical answers. Hig ....Efficient Compression and Querying Techniques for Massive Text Collections. Web search services have become a fundamental tool used by governments, businesses, and individuals, and play a key role in our access to knowledge and information. In this project we aim to develop new techniques for representing the indexes at the heart of web search services, and to devise new processing algorithms with reduced resource requirements for resolving queries and providing useful and topical answers. Higher query throughput and reduced storage load will benefit providers though reduced hardware and electricity costs, and will benefit society through better access to information, enhanced opportunities to connect and collaborate, and greater long-term scalability as on-line resources continue to multiply.Read moreRead less
Efficient and effective algorithms for searching strings in secondary storage. Pattern searching is fundamental to a wide range of computing applications, including web search and bioinformatics. In this project we will develop compression algorithms and hybrid memory-disk search structures that allow fast pattern matching on sequences of textual and numeric data, including when approximate search is required.
On effectively modelling and efficiently discovering communities from large networks. Finding and maintaining close communities from very large scale, dynamically changing networks is interesting and challenging. This project aims to develop new techniques to identify such communities as fast as possible through exploiting the rich semantics and individual relationships within the communities.