Discovery Early Career Researcher Award - Grant ID: DE180100688
Funder
Australian Research Council
Funding Amount
$336,446.00
Summary
Nanosensors in artificial cochlea for natural hearing. This project aims to develop a miniaturised and implantable cochlear that closely mimics the human auditory system by utilising advanced microfabrication techniques. This project expects to generate new knowledge in engineering hearing and vestibular hair cells and also on tonotopic organisation of cochlear. Expected outcomes include study of auditory hair cells and development of implantable ear-on-a-chip devices. This project is expected t ....Nanosensors in artificial cochlea for natural hearing. This project aims to develop a miniaturised and implantable cochlear that closely mimics the human auditory system by utilising advanced microfabrication techniques. This project expects to generate new knowledge in engineering hearing and vestibular hair cells and also on tonotopic organisation of cochlear. Expected outcomes include study of auditory hair cells and development of implantable ear-on-a-chip devices. This project is expected to enable low-cost production of highly engineered implant cochlear with great potential for commercialisation.Read moreRead less
A coupled finite volume method for viscoelastic flow problems on highly-skewed unstructured meshes: a computational rheology revolution. Commercial tools are unavailable for 21st century industry to analyse complex flow processes involving viscoelastic materials. Using fabrication of microstructured polymer optical fibre as a key case study, a coupled finite volume methodology holds the key for the next generation of computational rheology simulators.
Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful ....Faithful Visual Analytics: models, metrics and algorithms. This project aims to deliver new models, metrics and algorithms for Faithful Visual Analytics of complex data. For a purported visual representation of some data, "faithfulness" measures how accurately the visual representation describes the data. This project will develop new models for Faithful Visual Analytics, design new faithfulness metrics for faithful visual analytics of complex networks, design new algorithms to compute faithful visualisations, and evaluate using real world social network and biological network data sets. The new models, metrics and algorithms produced by this project will be used in the next generation Visual Analytic tools to enable analysts develop accurate insights and new knowledge of complex data.Read moreRead less
Modelling human perceptual-motor interaction for human-machine applications. This project aims to develop a new modelling framework for identifying the perceptual-motor processes that underlie cooperative and competitive human interaction. The project will also determine whether this modelling framework can be combined with modern machine-learning methods to develop artificial agents capable of human level performance. Expected outcomes will include a practical methodology for rapidly generating ....Modelling human perceptual-motor interaction for human-machine applications. This project aims to develop a new modelling framework for identifying the perceptual-motor processes that underlie cooperative and competitive human interaction. The project will also determine whether this modelling framework can be combined with modern machine-learning methods to develop artificial agents capable of human level performance. Expected outcomes will include a practical methodology for rapidly generating models of effective human interaction that can be easily implemented in human-machine systems. This will provide a richer understanding of the fundamental perceptual-motor processes that support robust human interaction and enhanced the effectiveness of human-machine collaboration and training technologies.Read moreRead less
Digital technologies and the private rental sector in Australia. This project aims to show how digital technologies are transforming the private rental sector in Australia. This project expects to generate new knowledge about the growing global reach of digital technologies aimed at private renters, landlords and property managers. The expected outcomes of this project include the production of social scientific knowledge about the potential of digital technologies to be both socially pernicious ....Digital technologies and the private rental sector in Australia. This project aims to show how digital technologies are transforming the private rental sector in Australia. This project expects to generate new knowledge about the growing global reach of digital technologies aimed at private renters, landlords and property managers. The expected outcomes of this project include the production of social scientific knowledge about the potential of digital technologies to be both socially pernicious and socially progressive. This project should provide significant benefits for Australian renters and our tenant advocacy partners who represent them, and to show how digital technologies can be used to create a better housing system.Read moreRead less
Modelling network innovation performance capability: a multidisciplinary approach. Innovation is created in complex network interactions.
By combining agent-based and fuzzy logic modelling, this project will identify combinations of resources to generate new ideas/technologies. This will enable managers and policy makers to understand the mechanisms behind innovation and implement policies aimed at enhancing innovation processes.
Sublinear algorithms for visual analytics of extreme-scale networks. This project aims to design new sublinear algorithms for the visual analytics of extreme-scale networks, involving billions of nodes. Based on algorithmics for graph drawing, integrating sublinear algorithms and distributed algorithms, the project will introduce new quality metrics for good visualisation of extreme-scale networks, design new sublinear-time algorithms to compute good visualisation, implement them in a distribute ....Sublinear algorithms for visual analytics of extreme-scale networks. This project aims to design new sublinear algorithms for the visual analytics of extreme-scale networks, involving billions of nodes. Based on algorithmics for graph drawing, integrating sublinear algorithms and distributed algorithms, the project will introduce new quality metrics for good visualisation of extreme-scale networks, design new sublinear-time algorithms to compute good visualisation, implement them in a distributed computing environment, and evaluate with a real world social network and biological network data sets. The new algorithms produced by this project will be used in the next generation visual analytic tools for extreme-scale data to enable analysts develop new insights and new knowledge of extreme-scale data.Read moreRead less
Beyond Planarity: Algorithms for Visualisation of Sparse Non-Planar Graphs. This project aims to develop new efficient algorithms to enable analysts to visually understand complex data and detect anomalies or patterns. It aims to develop visualisation algorithms for sparse non-planar graphs arising from real-world networks. Specifically, the project plans to investigate structural properties of sparse non-planar topological graphs such as k-planar graphs, k-skew graphs, and k-quasi-planar graphs ....Beyond Planarity: Algorithms for Visualisation of Sparse Non-Planar Graphs. This project aims to develop new efficient algorithms to enable analysts to visually understand complex data and detect anomalies or patterns. It aims to develop visualisation algorithms for sparse non-planar graphs arising from real-world networks. Specifically, the project plans to investigate structural properties of sparse non-planar topological graphs such as k-planar graphs, k-skew graphs, and k-quasi-planar graphs, and design efficient testing algorithms, embedding algorithms, and drawing algorithms. These algorithms will be evaluated with real-world social networks and biological networks. New insights into the mathematical interplay between combinatorial and geometric structures would provide a theoretical foundation for a new generation of complex network visualisation methods with potential applications in social networks, systems biology, health informatics, finance and security.Read moreRead less