Discovery Early Career Researcher Award - Grant ID: DE210100256
Funder
Australian Research Council
Funding Amount
$415,283.00
Summary
Extracting the hidden structure of glass from particle vibrations. Predicting the rigid behaviour of glass from its disordered, amorphous atomic structure remains a challenge in materials science. This project aims to define an innovative measure of structure based on how constrained each particle is, which can be quantified by measuring the particles’ vibrations. Using this new measure of structure, this project expects to link the microscopic structure of glass to its macroscopic properties v ....Extracting the hidden structure of glass from particle vibrations. Predicting the rigid behaviour of glass from its disordered, amorphous atomic structure remains a challenge in materials science. This project aims to define an innovative measure of structure based on how constrained each particle is, which can be quantified by measuring the particles’ vibrations. Using this new measure of structure, this project expects to link the microscopic structure of glass to its macroscopic properties via computer simulations. Expected outcomes of this project include a new methodology for characterising amorphous materials and an improved understanding of the nature of glass. This should provide significant benefits, such as an increased ability to rationally design amorphous materials with desired properties.Read moreRead less
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
Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an ....Learning to Pinpoint Emerging Software Vulnerabilities. This project aims to develop learning-based software vulnerability detection techniques to improve the reliability and security of modern software systems. The existing techniques relying on conventional yet rigid software analysis and testing techniques are ineffective and/or inefficient when detecting a wide variety of emerging software vulnerabilities. The outcomes of this project will be a deep-learning-based detection approach and an open-source tool that can capture precision correlations between deep code features and diverse vulnerabilities to pinpoint emerging vulnerabilities without the need for bug specifications. Significant benefits include greatly improved quality, reliability and security for modern software systems.Read moreRead less
Deep ocean thermodynamics and climate change. This project aims to obtain new insights into the thermodynamic and transport properties of mixtures containing water, particularly at high pressures, that impact directly on our understanding of climate change processes. The project will involve the use of a polarisable potential for water which has recently been demonstrated to yield predictions of high accuracy. It will be used to model saline water mixtures containing carbon dioxide, resulting in ....Deep ocean thermodynamics and climate change. This project aims to obtain new insights into the thermodynamic and transport properties of mixtures containing water, particularly at high pressures, that impact directly on our understanding of climate change processes. The project will involve the use of a polarisable potential for water which has recently been demonstrated to yield predictions of high accuracy. It will be used to model saline water mixtures containing carbon dioxide, resulting in valuable data for thermodynamic properties of the world's oceans. These data are of crucial importance for accurate climate change predictions and as such the project will have an important impact on understanding our changing environment.Read moreRead less
Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coord ....Energy big data analytics from a cybersecurity perspective. This project aims to develop a framework on energy big data analytics from security and privacy perspectives. Unlike other big data analytics such as social network big data analytics, energy big data analytics involve research challenges on how to cope with real-time tight cyber-physical couplings, and security/safety of the smart grid system. This project will develop advanced data-driven algorithms that are capable of detecting coordinated cyber-attacks that will potentially lead to catastrophic cascaded failures; and develop new solutions in detecting the false data-injection attacks that are conventionally considered as unobservable. This project will provide the benefit of enhancing our national critical infrastructure's security.Read moreRead less
Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical b ....Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical books. Libraries and legal, social and data science researchers will investigate eBook lending practices and understand their social impacts. The project will identify ways of reforming policy, law, and practice to help libraries fulfil their public interest missions. This project is expected to enable libraries to extract more value from existing public investments.Read moreRead less
Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor ....Privacy-preserving Biometrics based Authentication and Security. Password based authentication systems cannot verify genuine users. Biometric authentication can address this issue. However, the booming IoT applications and cloud computing require that the biometric authentication must be conducted in the privacy-protected setting in order to comply with privacy protection legal regulations. Latest reports show that current biometric authentication systems, under protected setting, exhibit poor authentication performance, which is not commercially applicable. This project aims to investigate innovative solutions to this issue. The intended deliverables will include deep learning based biometric feature extractor, cancellable biometrics and cloud oriented biometrics security protocols. Read moreRead less
Intelligent Reflecting Surface-enabled High-speed 6G Wireless Networks. Intelligent reflecting surface (IRS) is a ground-breaking wireless technology essential for the development of future sixth-generation (6G) wireless communication networks. This project aims to develop fundamental communication theories and practical solutions to characterise and optimise IRS-based communication. The project expects to design novel channel estimation, robust beamforming, resource allocation and analytical fr ....Intelligent Reflecting Surface-enabled High-speed 6G Wireless Networks. Intelligent reflecting surface (IRS) is a ground-breaking wireless technology essential for the development of future sixth-generation (6G) wireless communication networks. This project aims to develop fundamental communication theories and practical solutions to characterise and optimise IRS-based communication. The project expects to design novel channel estimation, robust beamforming, resource allocation and analytical framework to address the significant scientific challenges for the development of IRS for enabling high-speed 6G networks. These outcomes are expected to contribute to a new type of wireless infrastructure which paves the way for building and transforming the Australian information and communications technology industries.Read moreRead less
Expectations and commitments in the Australia-USA alliance. This project aims to investigate the gap between the high expectations of mutual support and the lack of detailed security commitments in the Australia-US Alliance. The project intends to use a focused approach that captures thematic aspects of the alliance through project frames and historical slices across time. Expected outcomes can advance understanding of how alliances operate as security institutions. The outcomes can help to prom ....Expectations and commitments in the Australia-USA alliance. This project aims to investigate the gap between the high expectations of mutual support and the lack of detailed security commitments in the Australia-US Alliance. The project intends to use a focused approach that captures thematic aspects of the alliance through project frames and historical slices across time. Expected outcomes can advance understanding of how alliances operate as security institutions. The outcomes can help to promote a more informed national conversation about the costs and benefits of Australia's security relationship with the United States of America (USA) and contribute to debates over the future of the Australia-USA Alliance during a period of strategic uncertainty.Read moreRead less