The role of electrostatic charge in airway deposition of aerosols. This project aims to unravel the importance of electrostatic charge in controlling deposition of aerosols in the respiratory tract. The expected outcome is a validated mathematical model for accurately predicting deposition behaviour of charged aerosol particles in human airways. Findings may ultimately be used to underpin novel prevention measures to reduce lung deposition of inhaled hazardous airborne particles to significantly ....The role of electrostatic charge in airway deposition of aerosols. This project aims to unravel the importance of electrostatic charge in controlling deposition of aerosols in the respiratory tract. The expected outcome is a validated mathematical model for accurately predicting deposition behaviour of charged aerosol particles in human airways. Findings may ultimately be used to underpin novel prevention measures to reduce lung deposition of inhaled hazardous airborne particles to significantly reduce health risks and costs. They may also be used to enable the development of new inhalation technologies based on electrostatic charge to improve aerosol drug delivery to the lungs of patients with respiratory diseases.Read moreRead less
Smartdrops - Shaping the future of particle technology. The aim of this project is to develop a particle engineering technology, based on microfluidics, that results in micro-droplets with controlled geometry and morphology. These Smartdrops will be used to target respiratory macrophages for the delivery of inflammatory suppressants, since their dimensions can be controlled to optimise lung deposition and macrophage recognition. The project aims to develop an aerosol inhaler and a series of phys ....Smartdrops - Shaping the future of particle technology. The aim of this project is to develop a particle engineering technology, based on microfluidics, that results in micro-droplets with controlled geometry and morphology. These Smartdrops will be used to target respiratory macrophages for the delivery of inflammatory suppressants, since their dimensions can be controlled to optimise lung deposition and macrophage recognition. The project aims to develop an aerosol inhaler and a series of physico-chemical and in vitro characterisation tools that will be used to study Smartdrop formation, aerosol properties and their interactions with cells. The outcome of this project is intended to be the development of a technology for treating chronic lung inflammation which could also be utilised for a number of other commercial applications.Read moreRead less
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
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
Developing novel aerosol inhalers for pulmonary drug delivery from the fundamental understanding of powder dispersion mechanisms. The project seeks to understand how powder aerosol inhalers can be significantly improved. The outcome will provide therapeutic benefits to the Australian community for better treatment of respiratory diseases and facilitate environmentally friendly technology since these inhalers do not require any harmful organic solvents to operate.
Enabling aerosol delivery of phages to defeat antibiotic-resistant bacteria. This project aims to explore the use of bacteriophages towards producing a safe, natural, and highly effective alternative to traditional antibiotics. Respiratory infections caused by multidrug-resistant Gram-negative bacteria are a major health problem worldwide, and cost Australia over $150 million annually. Some 5,000 Australians die each year from antibiotic resistant infections. The project aims to produce efficac ....Enabling aerosol delivery of phages to defeat antibiotic-resistant bacteria. This project aims to explore the use of bacteriophages towards producing a safe, natural, and highly effective alternative to traditional antibiotics. Respiratory infections caused by multidrug-resistant Gram-negative bacteria are a major health problem worldwide, and cost Australia over $150 million annually. Some 5,000 Australians die each year from antibiotic resistant infections. The project aims to produce efficacious and stable formulations of bacteriophages for easy delivery by inhalation as aerosols with a long shelf-life, making them a commercially viable product. The expected research outcome can lead to an economic and efficient technology to produce phage powders for novel treatment strategies of infections by inhalation.Read moreRead less
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