Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
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
New Lead-Free Brass Solutions for Drinking Water Applications. The aim of this Linkage Project is to provide viable material solutions to address the health problem of Lead-contamination in drinking water arising from Leaded-brass plumbing products and the impact Lead-removal from brass will have on the brass industry. In order to achieve this, this project engages leading multidisciplinary researchers along with Australian and international industry partners from across the brass industry suppl ....New Lead-Free Brass Solutions for Drinking Water Applications. The aim of this Linkage Project is to provide viable material solutions to address the health problem of Lead-contamination in drinking water arising from Leaded-brass plumbing products and the impact Lead-removal from brass will have on the brass industry. In order to achieve this, this project engages leading multidisciplinary researchers along with Australian and international industry partners from across the brass industry supply and sales network. This project seeks to identify and harness the key material-product attributes required to develop and implement new, lead-free alloy alternatives that meet health-compliance, production and commercial viability, that offer benefits across the industry network and health benefits to society.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
Indigenous persistence in formal learning. This project will improve knowledge of the learning experiences of Indigenous students transiting from TAFE to university studies. The results will have significant implications for the ways Indigenous students can be supported in their studies in order to achieve better quality learning experiences as well as learning outcomes.
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
Global childhoods: Life-worlds and educational success in Australia and Asia. This project aims to investigate how everyday life-worlds of year four students (nine-ten years of age) in Australia, Hong Kong and Singapore shape children’s orientations to educational success. Situated in the global cities of Melbourne, Sydney, Hong Kong and Singapore, the study explores connections between policy contexts, school experiences and everyday activities of children growing up in the Asian Century. Findi ....Global childhoods: Life-worlds and educational success in Australia and Asia. This project aims to investigate how everyday life-worlds of year four students (nine-ten years of age) in Australia, Hong Kong and Singapore shape children’s orientations to educational success. Situated in the global cities of Melbourne, Sydney, Hong Kong and Singapore, the study explores connections between policy contexts, school experiences and everyday activities of children growing up in the Asian Century. Findings will advance knowledge of factors that contribute to children’s understandings of how their experiences in and out of school prepare them for futures in a global world. This will enable policy-makers, educators and parents to provide improved learning opportunities in children’s lives.Read moreRead less
Realising the Potential of Australia’s High Capacity Students. This project aims to investigate factors that contribute to high capacity students failing to improve in literacy, numeracy and problem solving compared with their lower capacity peers. The project aims to focus on protective factors that might mitigate against this negative association between capacity and achievement. The study and method extends previous research the influence of evidence-based decisions by collaborative teacher t ....Realising the Potential of Australia’s High Capacity Students. This project aims to investigate factors that contribute to high capacity students failing to improve in literacy, numeracy and problem solving compared with their lower capacity peers. The project aims to focus on protective factors that might mitigate against this negative association between capacity and achievement. The study and method extends previous research the influence of evidence-based decisions by collaborative teacher teams on student achievement. In partnership with the Victorian Department of Education and Early Childhood Development, this project seeks to identify ways that will enable systems of education to realise the learning potential of all students.Read moreRead less
Building executive function in imaginary play. This project aims to develop a sustainable, play-based program to increase the executive functions of children in the year prior to school. Executive functions (EF) are cognitive processes that control an individual’s behaviour and cognition and include processes such as working memory, inhibitory control and attention. There is evidence that EF skills are critical to a successful transition to formal learning environments and future academic achiev ....Building executive function in imaginary play. This project aims to develop a sustainable, play-based program to increase the executive functions of children in the year prior to school. Executive functions (EF) are cognitive processes that control an individual’s behaviour and cognition and include processes such as working memory, inhibitory control and attention. There is evidence that EF skills are critical to a successful transition to formal learning environments and future academic achievement, and that they are amenable to early intervention. Improving children’s EF skills in the year prior to school could produce lasting benefits across the school years, particularly for more vulnerable children. This project intends to inform professional development programs in early childhood education.Read moreRead less