Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowled ....Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowledge and an approach to fast-adapt bilevel optimization solutions when required computing resources change. The anticipated outcomes should significantly improve the reliability of ML with benefits for safety learning and computing resource optimisation in ML-based data analytics.Read moreRead less
Causal Knowledge-Empowered Adaptive Federated Learning. Federated learning tools are a promising framework for collaborative machine learning (ML) that also maintain data privacy; however, their ability to model heterogeneous data remains a key challenge. This project aims to develop a new learning scheme for coordinated training of ML models that successfully bridges variable data distributions. The framework proposed will be the first globally that can use causal knowledge to 1) handle data he ....Causal Knowledge-Empowered Adaptive Federated Learning. Federated learning tools are a promising framework for collaborative machine learning (ML) that also maintain data privacy; however, their ability to model heterogeneous data remains a key challenge. This project aims to develop a new learning scheme for coordinated training of ML models that successfully bridges variable data distributions. The framework proposed will be the first globally that can use causal knowledge to 1) handle data heterogeneity across devices and 2) address the real-world challenges when only a subset of devices have labelled data. Expected outcomes and benefits include the theoretical underpinnings and algorithms of causality-based collaborative training of ML models while better preserving the users’ data privacy.Read moreRead less
Transformation Dual Phase Synergy for Unprecedented Superelasticity. This project aims to develop metallic materials of unprecedented mechanical properties based on a novel concept of transformation triggered dual-phase synergy. This is enabled by harnessing the intrinsic strength of interatomic bonds in solids using the nanoscience principle of lattice strain matching between phase transforming bodies. The project will provide significant benefits, such as innovating our metal production techno ....Transformation Dual Phase Synergy for Unprecedented Superelasticity. This project aims to develop metallic materials of unprecedented mechanical properties based on a novel concept of transformation triggered dual-phase synergy. This is enabled by harnessing the intrinsic strength of interatomic bonds in solids using the nanoscience principle of lattice strain matching between phase transforming bodies. The project will provide significant benefits, such as innovating our metal production technology and to value-add the metal processing and manufacturing industries of Australia.Read moreRead less
Modelling twinning transitions in light metals: a new foundation for alloy and process development. Australia's quest to become a world leader in light metals technology is being held back by a lack of quantitative understanding of the metallurgical behaviour of magnesium, which is the lightest engineering metal, and titanium, which is the strongest light metal. In particular, there is poor knowledge of the influence of material parameters on deformation twinning. This knowledge is vital for eff ....Modelling twinning transitions in light metals: a new foundation for alloy and process development. Australia's quest to become a world leader in light metals technology is being held back by a lack of quantitative understanding of the metallurgical behaviour of magnesium, which is the lightest engineering metal, and titanium, which is the strongest light metal. In particular, there is poor knowledge of the influence of material parameters on deformation twinning. This knowledge is vital for efficient production and optimised alloy and part design. This proposal aims to develop a quantitative understanding of transitions in twinning activation for improved performance in fatigue, crash behaviour, structural integrity, forming, forging, extruding, hot rolling and annealing.Read moreRead less
Innovative Zn alloys with essential mechanical and biofunctional properties. This project aims to develop a breakthrough understanding of the impact of alloying additions on the strengthening mechanisms, degradation behaviour, antibacterial properties and biofunctionalities of zinc alloys. The project expects to generate new knowledge in alloying strategies, plastic deformation and surface modification of zinc alloys to achieve mechanical, corrosion and biofunctional properties satisfying the re ....Innovative Zn alloys with essential mechanical and biofunctional properties. This project aims to develop a breakthrough understanding of the impact of alloying additions on the strengthening mechanisms, degradation behaviour, antibacterial properties and biofunctionalities of zinc alloys. The project expects to generate new knowledge in alloying strategies, plastic deformation and surface modification of zinc alloys to achieve mechanical, corrosion and biofunctional properties satisfying the requirements of biodegradable metallic materials. The expected outcomes are the development of novel zinc alloys and practical technologies for industry applications, such as thermomechanical processing and surface coating. The benefits are expected to extend to physical metallurgy and biomaterial manufacturing.Read moreRead less
MICROFORMING: effects of microstructural scale on metal formability. Microforming is a rapidly growing industry, and already enjoys considerable activity in Germany, Japan, the US, and Korea, all of which are major trading partners of Australia. This project couples fundamental insight into the effects of microstructural and geometric scale with the frontier technology of microforming. Thus, the project will place Australian researchers at the frontier of microforming research, with the capacity ....MICROFORMING: effects of microstructural scale on metal formability. Microforming is a rapidly growing industry, and already enjoys considerable activity in Germany, Japan, the US, and Korea, all of which are major trading partners of Australia. This project couples fundamental insight into the effects of microstructural and geometric scale with the frontier technology of microforming. Thus, the project will place Australian researchers at the frontier of microforming research, with the capacity to be involved in shaping the industry. In the course of this work, new process routes will be developed, new materials may be created, and new opportunities will certainly emerge.Read moreRead less
Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capabili ....Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capability and competitiveness in AI, and deliver robust and trustworthy learning technology. The project should provide significant benefits not only in advancing scientific and translational knowledge but also in accelerating AI innovations, safeguarding cyberspace, and reducing the burden on defence expenses in Australia.Read moreRead less
A Novel Approach to Grain Refinement of Cast Metals. This proposal combines fundamental scientific studies with applied engineering research. The outcomes will offer materials scientists and engineers with a totally new way to understand the grain refinement of cast metals. The new scientific knowledge generated will put Australia at the absolute forefront of the field and maintain our internationally leading position. The new grain refiners and the relevant master alloys to be developed will ....A Novel Approach to Grain Refinement of Cast Metals. This proposal combines fundamental scientific studies with applied engineering research. The outcomes will offer materials scientists and engineers with a totally new way to understand the grain refinement of cast metals. The new scientific knowledge generated will put Australia at the absolute forefront of the field and maintain our internationally leading position. The new grain refiners and the relevant master alloys to be developed will have strong potential to be commercialized to produce cast metals with much improved properties and performance. This will not only increase Australian competitive ability in the international market, but will also make considerable economic benefits.Read moreRead less
Modelling complex learning spaces. The growing use of digital tools and resources means that students' learning activities are no longer tied to unique physical places. Their work is distributed across increasingly complex mixtures of physical and digital spaces, which both shape and are shaped by students' activity. This project aims to identify productive ways of modelling the characteristics and uses of complex learning spaces in higher education. Evidence and models generated by the project ....Modelling complex learning spaces. The growing use of digital tools and resources means that students' learning activities are no longer tied to unique physical places. Their work is distributed across increasingly complex mixtures of physical and digital spaces, which both shape and are shaped by students' activity. This project aims to identify productive ways of modelling the characteristics and uses of complex learning spaces in higher education. Evidence and models generated by the project aim to strengthen the logic connecting the use, management and design of learning spaces. A better understanding of the relations between pedagogy, activity and space will improve the work of architects and other designers, campus managers, university teachers and students themselves.Read moreRead less
Does a teacher-led mindfulness intervention improve student outcomes? This project aims to determine if improving teacher knowledge and practice of mindfulness in the classroom, can lead to better child attention and school functioning outcomes during the early primary school years. Mindfulness is an approach that aims to improve attention, self-regulation, mental health, and cognitive functioning. Expected outcomes include new knowledge as to whether mindfulness can be integrated into classroom ....Does a teacher-led mindfulness intervention improve student outcomes? This project aims to determine if improving teacher knowledge and practice of mindfulness in the classroom, can lead to better child attention and school functioning outcomes during the early primary school years. Mindfulness is an approach that aims to improve attention, self-regulation, mental health, and cognitive functioning. Expected outcomes include new knowledge as to whether mindfulness can be integrated into classroom practice, how to best implement it, student benefits and cost-effectiveness. Findings will inform schools as to whether this approach can support students in making a positive transition to primary school that can place them on positive academic and well-being pathways and lead to benefits in their adulthood.Read moreRead less