Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can g ....Algorithms for hard graph problems based on auxiliary data. When solving computational problems, algorithms usually access only the data that is absolutely necessary to define the problem. However, much more data is often readily available. Especially for important or slowly evolving data, such as road networks, social graphs, company rankings, or molecules, more and more auxiliary data becomes available through computational processes, sensors, and simple user entries. This auxiliary data can greatly speed up an algorithm and improve its accuracy. This project aims to design improved algorithms that harness auxiliary data to solve selected high-impact NP-hard graph problems, and will build a new empowering theory to discern when auxiliary data can be used to improve algorithms.Read moreRead less
Development of methods and algorithms to support multidisciplinary optimisation. This project will aim to develop a number of novel and computationally efficient schemes to deal with the key challenges facing multidisciplinary optimisation. These advancements will allow us to solve a number of challenging and intractable problems in science and engineering.
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.
A New Optimization Approach for Tensor Extreme Eigenvalue Problems: Modern Techniques
for Multi-relational Data Analysis. Nowadays, we often encounter complex multi-relational data whose objects have interactions among themselves based on different relations. These multi-relational data can be mathematically modelled as tensors. The tensor extreme eigenvalue problem, which is concerned with extracting the most significant qualitative information from multi-relational data, plays a key role in m ....A New Optimization Approach for Tensor Extreme Eigenvalue Problems: Modern Techniques
for Multi-relational Data Analysis. Nowadays, we often encounter complex multi-relational data whose objects have interactions among themselves based on different relations. These multi-relational data can be mathematically modelled as tensors. The tensor extreme eigenvalue problem, which is concerned with extracting the most significant qualitative information from multi-relational data, plays a key role in modern data analysis. This project aims at developing innovative global optimisation frameworks and reliable numerical methods for tensor extreme eigenvalue problems, and applying the proposed methods to solve various practical problems arising from important application areas such as modern data analysis, medical imaging science and signal processing.Read moreRead less
Optimisation for next generation machine learning. As more and more data are being collected, it is important to build intelligent systems which will can analyse these data efficiently. This project will take design and analyse new algorithms which take advantage of emerging paradigms in hardware such as multicore processors, graphic processing units (GPU), and cluster computers to achieve this goal.
Low emission road transportation: harnessing the potential of alternative fuels and advanced vehicle technologies through online optimisation. This project will develop fundamental mathematical theory and use it to enable the best possible CO2 reduction capability in road vehicles. The cost of different technologies and fuels will then be compared to determine the most cost effective approaches to reduce road transport emissions.
Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to devel ....Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to develop purely data-driven rules to choose the regularisation parameter and show how they work in theory, and in practice. It will also develop convex framework, acceleration strategies as well as preconditioning and splitting ideas to design efficient regularisation solvers.Read moreRead less
Optimal maintenance planning for critical mining and energy infrastructure. This project aims to develop cutting-edge mathematical algorithms for optimising maintenance activities in the mining and energy sectors. Such maintenance activities are prone to budget and time overruns due to poor planning - the result of outdated, inefficient manual processes. The project is expected to result in new maintenance planning methods, underpinned by rigorous mathematical theory, for reducing manual interve ....Optimal maintenance planning for critical mining and energy infrastructure. This project aims to develop cutting-edge mathematical algorithms for optimising maintenance activities in the mining and energy sectors. Such maintenance activities are prone to budget and time overruns due to poor planning - the result of outdated, inefficient manual processes. The project is expected to result in new maintenance planning methods, underpinned by rigorous mathematical theory, for reducing manual intervention and optimising both short- and long-term maintenance based on real-time sensor data. These new methods will be powerful tools for tackling the complexity of large-scale, time-critical maintenance projects, driving productivity in the resources industry and fostering collaboration between mathematicians and engineers.Read moreRead less
Decentralisation and robustness for practical control of complex systems. This project aims to develop the theory and tools to address the control of complex interconnected systems. There is currently an enormous disconnect in decentralised control between the celebrated theoretical advances and the concepts that are used for implementation, or even for computation. The project expects to isolate the key reasons for this disconnect and develop ways to address the control of complex interconnecte ....Decentralisation and robustness for practical control of complex systems. This project aims to develop the theory and tools to address the control of complex interconnected systems. There is currently an enormous disconnect in decentralised control between the celebrated theoretical advances and the concepts that are used for implementation, or even for computation. The project expects to isolate the key reasons for this disconnect and develop ways to address the control of complex interconnected systems. The expected outcome is a tool which can observe information from only a small portion of a network but which may ultimately effect a large portion of the network. This includes smart building management, multi-vehicle systems and convoys, irrigation networks, large array telescopes, and the power distribution grid.Read moreRead less