Does word similarity across languages help or hinder bilingual speakers? This project aims to understand in more detail how bilinguals can accurately speak in both their languages. Speaking is a complex skill, particularly if you have two languages to choose from, which will be true for over half of Australia’s population by 2025. This project aims to investigate the factors that influence speech production in both monolinguals and bilinguals including those with language impairment, and develop ....Does word similarity across languages help or hinder bilingual speakers? This project aims to understand in more detail how bilinguals can accurately speak in both their languages. Speaking is a complex skill, particularly if you have two languages to choose from, which will be true for over half of Australia’s population by 2025. This project aims to investigate the factors that influence speech production in both monolinguals and bilinguals including those with language impairment, and develop a better bilingual theory. The benefit of this new theory will be to provide a clear basis for diagnosis and treatment for children in bilingual households who have problems learning to speak, and for bilingual people with language problems after a stroke or dementia.Read moreRead less
Using visual science to reduce the dangers of night driving. This project aims to develop novel tests of visual function relevant to the modern night driving environment. Night driving is challenging for all drivers and has been linked to poor visibility under low light conditions. This project will characterise the visual challenges of the modern night driving environment, develop visual tests that incorporate the dynamic light levels typical of night-time roads and assess the association of th ....Using visual science to reduce the dangers of night driving. This project aims to develop novel tests of visual function relevant to the modern night driving environment. Night driving is challenging for all drivers and has been linked to poor visibility under low light conditions. This project will characterise the visual challenges of the modern night driving environment, develop visual tests that incorporate the dynamic light levels typical of night-time roads and assess the association of these tests with night driving performance. The outcomes will contribute new knowledge regarding dynamic visual processing and the ageing visual system and will inform vision testing, potential interventions to improve visual function for night driving and reduce the dangers of night driving.Read moreRead less
Listen and learn - statistical learning and the adapting auditory brain. This project aims to explore the link between rapid neural adaptation - a form of learning referred to as statistical learning - and human listening performance in noisy environments. The project aims to generate a new understanding of mechanisms that contribute to listeners' abilities to understand speech in noise, and to complex communication disorders such as dyslexia. Expected outcomes will include increased capacity to ....Listen and learn - statistical learning and the adapting auditory brain. This project aims to explore the link between rapid neural adaptation - a form of learning referred to as statistical learning - and human listening performance in noisy environments. The project aims to generate a new understanding of mechanisms that contribute to listeners' abilities to understand speech in noise, and to complex communication disorders such as dyslexia. Expected outcomes will include increased capacity to investigate a broad range of cognitive and communication functions. Benefits will include potential technologies and algorithms to assist listening (in devices such as hearing aids), language development and reading.Read moreRead less
Neural plasticity in older adult human vision. This project aims to expand our understanding of age related changes in brain function, specifically plasticity. The project will increase knowledge of the role of an inhibitory neurotransmitter GABA in visual plasticity. Expected outcomes include new knowledge regarding the regulation of brain function in adulthood, enabling future research and planning for societal benefit to older Australia.
Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and e ....Fine-grained Human Action Recognition with Deep Graph Neural Networks. This project aims to develop novel graph neural network based deep learning algorithms for fine-grained human action recognition. This project expects to bring human action analysis to the next level and to significantly advance the analysis of subtle yet complex human actions. Expected outcomes of this project include theoretical advances on graph representation based deep learning algorithms for spatial-temporal data, and enabling techniques for more objective human action analysis in many domains such as sports and health. This should provide significant benefits to any application domain involving big and complex spatial-temporal data for finer analytics and better knowledge discovery.Read moreRead less
Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with thei ....Shape4D: Modelling the Spatiotemporal Deformation Patterns in 3D Shapes. This research will develop new mathematical methods and algorithms that will enable the use of population-level longitudinal studies to model the spatial and temporal deformation patterns in 3D biological objects. Using novel geometric and deep learning techniques, it will create new methods that will allow the characterization of how the 3D shape of objects deforms with ageing, disease progression and interaction with their environment, and the simulation of spatiotemporal deformations in anatomical organs. Benefits include a better understanding of growth processes, predictive models of how degenerative diseases progress and a computational framework that will assist in designing proper mitigation and intervention strategies.Read moreRead less
Tensor and Hypergraph Methods in Fitting Visual Data. This proposal will put an important class of clustering (extracting data that should fit a geometric model) on a more solid theoretical foundation. This will lead to better understanding of how to certify outcomes, efficiency, reliability etc. The type of clustering under consideration is relevant to many problems in machine learning and computer vision, as well as data mining and a wide variety of other settings.
Teaching and testing second language pragmatic skills. This project aims to develop understanding of what it means to be communicatively proficient in English as a second language. Drawing on research in second language acquisition, pragmatics and language testing, the project will develop a set of language tests to assess learners’ ability to use English appropriately in everyday situations. The tests will then be used to evaluate the effectiveness of language instruction in developing this abi ....Teaching and testing second language pragmatic skills. This project aims to develop understanding of what it means to be communicatively proficient in English as a second language. Drawing on research in second language acquisition, pragmatics and language testing, the project will develop a set of language tests to assess learners’ ability to use English appropriately in everyday situations. The tests will then be used to evaluate the effectiveness of language instruction in developing this ability. Outcomes will include a set of novel language tests and valuable information about effective language instruction. The project will inform the extent to which migrants possess the pragmatic skills needed to live and work in Australia and how they can be helped to acquire these skills.Read moreRead less
Passive Positioning and Tracking of Flying Objects Using Satellite Signals. Along with the deployment of low Earth orbit satellite constellations for global satellite Internet services, such as Starlink, Ku/Ka/V band microwave signals from space will be available anywhere on Earth 24/7. Utilising the microwave signals, this project aims to investigate a high-resolution cost-effective solution to position and track un-cooperative flying objects, and expects to generate new knowledge in the area o ....Passive Positioning and Tracking of Flying Objects Using Satellite Signals. Along with the deployment of low Earth orbit satellite constellations for global satellite Internet services, such as Starlink, Ku/Ka/V band microwave signals from space will be available anywhere on Earth 24/7. Utilising the microwave signals, this project aims to investigate a high-resolution cost-effective solution to position and track un-cooperative flying objects, and expects to generate new knowledge in the area of remote sensing and to make Australia the leader in passive flying objects positioning and tracking. This should provide significant benefits, such as enabling new applications for future drone delivery systems or aerial taxi services, and benefiting the air transport industry, the defence industry, and bird conservation.Read moreRead less
Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learni ....Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learning architectures that are inherently robust. The outcomes of this project will increase the security and reliability of computer vision by detecting, reporting and nullifying such attacks and will benefit the general public and industry on many fronts.Read moreRead less