Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through dee ....Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through deep learning with structural conditions and load-carrying capacities obtained from vibration tests and finite element model analysis for efficient structural damage detection and quantification. The project will lead to effective structural health monitoring and enhance structural safety and reduce maintenance costs. Read moreRead less
Robust Federated Learning for Imperfect Decentralised Data. This project aims to develop a next-generation robust federated learning framework to tackle the challenging scenarios of imperfect decentralised data in real applications, e.g. mobile phones and the Internet of Things (IoT) devices. The outcomes will bring great benefits to a broad range of industry sectors by providing novel large-scale intelligent applications with privacy preservation. The proposed method will advance the developmen ....Robust Federated Learning for Imperfect Decentralised Data. This project aims to develop a next-generation robust federated learning framework to tackle the challenging scenarios of imperfect decentralised data in real applications, e.g. mobile phones and the Internet of Things (IoT) devices. The outcomes will bring great benefits to a broad range of industry sectors by providing novel large-scale intelligent applications with privacy preservation. The proposed method will advance the development of a cutting-edge technique to develop new intelligent applications in a decentralised and privacy-sensitive scenario. This game-changing research will advance current data mining and artificial intelligence research from centralised intelligence to decentralised intelligence with a collaboration network.Read moreRead less
Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make th ....Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make the speech and speaker recognition systems less sensitive to additive background noise and make them more useful in telecommunications and business.Read moreRead less
Atomic scale ion microscopy via laser cooling and correlated imaging. This project will develop next-generation focused ion beam microscopy and nanofabrication using a novel cold ion source based on photoionisation of a laser-cooled atom beam. The low temperature and complex internal state structure of the constituent atoms combine to allow generation of ions with unprecedented brightness and resolution. We will use three unique and innovative ideas: field ionisation of atoms in so-called 'excep ....Atomic scale ion microscopy via laser cooling and correlated imaging. This project will develop next-generation focused ion beam microscopy and nanofabrication using a novel cold ion source based on photoionisation of a laser-cooled atom beam. The low temperature and complex internal state structure of the constituent atoms combine to allow generation of ions with unprecedented brightness and resolution. We will use three unique and innovative ideas: field ionisation of atoms in so-called 'exceptional' states to reduce chromatic aberration; electron-ion correlations to enhance control of the ions at the nanoscale; and atom-atom interactions to isolate and manipulate individual ions. The new technology will enable advances in semiconductor nanofabrication and material characterisation.Read moreRead less
Enhancing the Australian theme park experience by harnessing virtual-physical play. This project will deliver methodologies for designing games enriched by virtual-physical play. The project will contribute to furthering Australia's lead in the production of compelling theme park experiences, computer games and interactive training systems. The entertainment, digital media and information and communications technology industries will all benefit as a result.
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
Atomic scale imaging with high coherence electrons and ions. This project aims to combine a cold atom electron-ion source with a commercial microscope column for atomic-scale imaging in biosciences and materials science. Nanoscale imaging with electron and ion microscopy are tools for investigating the world at the atomic scale, underpinning development in modern technologies from semiconductor devices to medical treatments. This project will use ideas from laser cooling of atoms and atom optics ....Atomic scale imaging with high coherence electrons and ions. This project aims to combine a cold atom electron-ion source with a commercial microscope column for atomic-scale imaging in biosciences and materials science. Nanoscale imaging with electron and ion microscopy are tools for investigating the world at the atomic scale, underpinning development in modern technologies from semiconductor devices to medical treatments. This project will use ideas from laser cooling of atoms and atom optics to achieve new imaging modalities for time-lapse imaging of fundamental processes at the nano-scale. It will allow increasingly small scale resolution of fundamental processes at the nano-scale.Read moreRead less
High resolution ultrafast imaging with cold electrons. This project will develop atomic-scale imaging that is able to bypass the resolution limitations of modern electron microscopes. The project will investigate the physical processes underlying a new imaging source based on extracting cold electrons from laser-cooled atoms. Ultrashort pulses of cold electrons will enable time-lapse imaging of fundamental processes at the nano-scale, with applications in fundamental biosciences and materials sc ....High resolution ultrafast imaging with cold electrons. This project will develop atomic-scale imaging that is able to bypass the resolution limitations of modern electron microscopes. The project will investigate the physical processes underlying a new imaging source based on extracting cold electrons from laser-cooled atoms. Ultrashort pulses of cold electrons will enable time-lapse imaging of fundamental processes at the nano-scale, with applications in fundamental biosciences and materials science.Read moreRead less
Investigating the molecular mechanisms underlying non-visual photoreception and their implications in the treatment of human neurological disease. The ability of organisms to detect light is fundamental for survival and has been a major driver in evolution. The project will investigate the genetic origins of the various visual and non-visual systems and will explore its implications for the bioengineering of therapeutics for the treatment of neurological disease in humans.
Discovery Early Career Researcher Award - Grant ID: DE200100964
Funder
Australian Research Council
Funding Amount
$427,068.00
Summary
Early Prediction in Large-scale Time-variant Information Networks. This project aims to develop an early prediction system to predict possible outbreaks of malicious messages in time-variant information networks. The research will primarily leverage deep representations of time-variant subsequence and substructure patterns in large-scale social networks to signal malicious and malevolent messages before it has a chance to propagate. This project will lay the theoretical foundations of this emerg ....Early Prediction in Large-scale Time-variant Information Networks. This project aims to develop an early prediction system to predict possible outbreaks of malicious messages in time-variant information networks. The research will primarily leverage deep representations of time-variant subsequence and substructure patterns in large-scale social networks to signal malicious and malevolent messages before it has a chance to propagate. This project will lay the theoretical foundations of this emerging field to strengthen Australia’s world leadership role in data science. Practically, the novel theories and data analytics technologies developed will help to safeguard Australian business, industry, and society from cyberfraud, online rumour-mongering, and financial loss.Read moreRead less