Evolutionary computation for expensive bilevel multiobjective problems. This project aims to develop an evolutionary computation framework to solve computationally expensive bilevel multiobjective problems. The research is fundamental in nature and will address key open challenges in solving such problems, including hierarchical decision-making, multiple performance criteria, uncertainties and computational expense. The proposed research has applications in diverse domains such as environmental ....Evolutionary computation for expensive bilevel multiobjective problems. This project aims to develop an evolutionary computation framework to solve computationally expensive bilevel multiobjective problems. The research is fundamental in nature and will address key open challenges in solving such problems, including hierarchical decision-making, multiple performance criteria, uncertainties and computational expense. The proposed research has applications in diverse domains such as environmental policy formulation, network design, engineering, defence and cybersecurity; offering significant benefits to the researchers and practitioners in these fields. In addition to research outputs, it will strengthen international collaboration and build research capacity to put Australia at the forefront of this research.
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Evolutionary computation for robust multi-objective engineering design. This project aims to develop an evolutionary computation framework for robust multi-objective design, a critical pursuit in engineering industries. Such problems are characterised by multiple conflicting performance objectives
and constraints which are highly nonlinear, often black-box, and prone to unavoidable real-life uncertainties. The existing evolutionary algorithms are often computationally impractical and have a numb ....Evolutionary computation for robust multi-objective engineering design. This project aims to develop an evolutionary computation framework for robust multi-objective design, a critical pursuit in engineering industries. Such problems are characterised by multiple conflicting performance objectives
and constraints which are highly nonlinear, often black-box, and prone to unavoidable real-life uncertainties. The existing evolutionary algorithms are often computationally impractical and have a number of fundamental
shortcomings which restrict their use in real applications. This project aims to investigate and overcome the underlying key challenges to advance knowledge and contribute towards diverse domains such as energy, transport and space research, helping deliver high quality robust designs.
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Learning deep resilient behaviour for uncertainty-aware autonomy. This research project aims to propose a novel framework for developing uncertainty-aware autonomous systems using deep learning. There are fundamental gaps in our knowledge of deep uncertainty quantification and its application for risk-aware decision making. Novel algorithms will be proposed to reliably generate deep uncertainty estimates with low computational overhead. These estimates will be then exploited by safety-critical s ....Learning deep resilient behaviour for uncertainty-aware autonomy. This research project aims to propose a novel framework for developing uncertainty-aware autonomous systems using deep learning. There are fundamental gaps in our knowledge of deep uncertainty quantification and its application for risk-aware decision making. Novel algorithms will be proposed to reliably generate deep uncertainty estimates with low computational overhead. These estimates will be then exploited by safety-critical systems such as autonomous robots to identify risky actions and avoid catastrophise. Developed algorithms will be implemented on an autonomous robotic system to make it averse to uncertainties. The outcomes will greatly increase reliable telerobotic applications in mining, manufacturing, defence, and health.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.
Breathing and snoring sound analysis in sleep apnea. About 800,000 Australians suffer from the disease sleep Apnoea (OSA) which has snoring as its earliest symptom. We develop electronics and snore processing algorithms to classify snorers into OSA-positive and OSA-negative classes, based on advanced technology derived from speech recognition systems.
Hardware Acceleration for Neural Systems. To really understand how brains work, we need to simulate neural networks of a size similar to that of the human brain (100 billion neurons, 100 trillion connections). Simulating such a network on standard computers in not possible because of its sheer size. Several groups are currently building very expensive and proprietary hardware to solve this, but the output from these projects will not be accessible to other researchers. In order to make real prog ....Hardware Acceleration for Neural Systems. To really understand how brains work, we need to simulate neural networks of a size similar to that of the human brain (100 billion neurons, 100 trillion connections). Simulating such a network on standard computers in not possible because of its sheer size. Several groups are currently building very expensive and proprietary hardware to solve this, but the output from these projects will not be accessible to other researchers. In order to make real progress in neuroscience, many more researchers need to be enabled to participate. To do this, the project will build a system from commercial hardware (FPGAs) that will cost only a few ten thousand dollars and it will make this design and software available for free. Read moreRead less
Bragg-Edge neutron transmission strain tomography. This project aims to use neutron strain tomography to improve solid mechanics research and advanced manufacturing techniques. The investigators have developed a tensor reconstruction algorithm, similar to an enhanced CT or MRI scan, which can determine the finely grained three-dimensional triaxial stress distribution inside solid objects by measuring neutron transmission. Using energy-resolved neutron detector technology, this project intends to ....Bragg-Edge neutron transmission strain tomography. This project aims to use neutron strain tomography to improve solid mechanics research and advanced manufacturing techniques. The investigators have developed a tensor reconstruction algorithm, similar to an enhanced CT or MRI scan, which can determine the finely grained three-dimensional triaxial stress distribution inside solid objects by measuring neutron transmission. Using energy-resolved neutron detector technology, this project intends to realise and extend this technique to transform several areas of applied mechanics research.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100104
Funder
Australian Research Council
Funding Amount
$1,175,000.00
Summary
An aberration corrected analytical Transmission Electron Microscope for nanoscale characterisation of materials. This new-generation scanning transmission electron microscope enables selective determination of atomic and chemical structure within sub-nanometre regions of materials. It will enable cutting-edge developments in nanotechnology, materials science and engineering; technologies which underpin progress in our modern society.
The neural dynamics of real-time processing in the brain. The aim of this project is to investigate a new model for predictive coding of sensory processing in the brain in which the brain compensates for the time delays in neural transmission by maintaining a real-time temporal alignment of the neural activity. This results in a representation of sensory information that is aligned in time across the cortex, offering a new fundamental principle for how the brain functions in a highly dynamic wor ....The neural dynamics of real-time processing in the brain. The aim of this project is to investigate a new model for predictive coding of sensory processing in the brain in which the brain compensates for the time delays in neural transmission by maintaining a real-time temporal alignment of the neural activity. This results in a representation of sensory information that is aligned in time across the cortex, offering a new fundamental principle for how the brain functions in a highly dynamic world whose outcomes would provide a deeper understanding of brain function. It could also have profound significance for artificial intelligence and brain-inspired technologies, as well as benefit neural sensory prostheses and brain-machine interfaces.Read moreRead less
A novel and efficient approach for optimisation involving iterative solvers. Computationally expensive simulations involving iterative solvers are increasingly being used in industry to assess performance of products and processes. Repeated use of such simulations is necessary to identify optimum solutions. Even with today's computing power, many such tasks remain computationally prohibitive. This project presents a novel approach to solve optimisation problems involving iterative solvers with l ....A novel and efficient approach for optimisation involving iterative solvers. Computationally expensive simulations involving iterative solvers are increasingly being used in industry to assess performance of products and processes. Repeated use of such simulations is necessary to identify optimum solutions. Even with today's computing power, many such tasks remain computationally prohibitive. This project presents a novel approach to solve optimisation problems involving iterative solvers with limited computing budget. A wide range of industries involved in product and process design would gain a significant competitive advantage from this unique technical innovation. In addition, this technology will be invaluable to uncover and understand complex natural phenomena.Read moreRead less