David and Goliath - what planets can do to the stars that created them. We used to think that when stars expand during their old age, they would destroy all their close-by planets. Today we know that if a star swallows a Jupiter-like planet it can suffer indigestion. The project will study how star-planet interactions takes place, determine their impact on the lives of stars and glimpse at the future of our own solar system.
Historical frontier violence: drivers, legacy and the role of truth-telling. This project aims to build data to identify the historical factors that incited frontier violence; quantify the legacy on communities today and conduct fieldwork to understand how historical trauma is transmitted across generations. This project expects to develop new knowledge on the circumstances and legacy of settlement and the origins of gaps in life prospects between Indigenous and non-Indigenous Australians. Our e ....Historical frontier violence: drivers, legacy and the role of truth-telling. This project aims to build data to identify the historical factors that incited frontier violence; quantify the legacy on communities today and conduct fieldwork to understand how historical trauma is transmitted across generations. This project expects to develop new knowledge on the circumstances and legacy of settlement and the origins of gaps in life prospects between Indigenous and non-Indigenous Australians. Our expectation is that this will increase public acceptance of the circumstances of settlement and the need to make amends. This project should help increase public support for truth-telling and better relations between Indigenous and non-Indigenous Australians, a vital step towards reconciliation and healing the nation. Read moreRead less
International collaboration in teaching and learning of Einsteinian physics. Following a previous project that showed that it is possible and beneficial to teach the modern Einsteinian paradigm of space, time, matter, light and gravity to students as young as 8 years old, this project aims to test and evaluate a seamless progression of learning modern physics through primary and secondary school. It will sequence, integrate and test research-informed teaching and learning materials, and assessme ....International collaboration in teaching and learning of Einsteinian physics. Following a previous project that showed that it is possible and beneficial to teach the modern Einsteinian paradigm of space, time, matter, light and gravity to students as young as 8 years old, this project aims to test and evaluate a seamless progression of learning modern physics through primary and secondary school. It will sequence, integrate and test research-informed teaching and learning materials, and assessment instruments developed through a 7-nation collaboration. Research across 24 schools will be reviewed by a panel drawn from professional organisations and curriculum authorities, and learning resources will be widely disseminated, with view to worldwide introduction of Einsteinian science at school.Read moreRead less
Processing mathematics tasks: the nature and role of visual and non-visual reasoning in digital and non-digital environments. Within the next four years, it is likely that the National Assessment Plan for Literacy and Numeracy (NAPLAN) will be administered in a digital mode. This project identifies differences between the delivery of mathematics assessment in pencil-and-paper and computer-based modes. Primary students' mathematics reasoning is compared across these modes and to cohorts from Sing ....Processing mathematics tasks: the nature and role of visual and non-visual reasoning in digital and non-digital environments. Within the next four years, it is likely that the National Assessment Plan for Literacy and Numeracy (NAPLAN) will be administered in a digital mode. This project identifies differences between the delivery of mathematics assessment in pencil-and-paper and computer-based modes. Primary students' mathematics reasoning is compared across these modes and to cohorts from Singapore.Read moreRead less
Observe, Reflect, Improve: a tool to enrich Children’s Learning (ORICL). This project aims to address long-standing concerns about the quality of education and care for children during their critical first two years. It will introduce a promising, future-focused digital tool, co-designed with practitioners and providers of early childhood services, to support infant-toddler educators’ planning and practice. Building on ground-breaking pilot work, we will undertake a national implementation and e ....Observe, Reflect, Improve: a tool to enrich Children’s Learning (ORICL). This project aims to address long-standing concerns about the quality of education and care for children during their critical first two years. It will introduce a promising, future-focused digital tool, co-designed with practitioners and providers of early childhood services, to support infant-toddler educators’ planning and practice. Building on ground-breaking pilot work, we will undertake a national implementation and evaluation of the Observe, Reflect and Improve Children’s Learning (ORICL) tool. Expected outcomes include: enhanced pedagogical practices; enriched learning experiences for children birth-two; effective communication with families; and improved resourcing for providers of early childhood education and care services. Read moreRead less
Generative Visual Pre-training on Unlabelled Big Data. This project aims to develop a generative visual pre-training of large-scale deep neural networks on unlabelled big data. Developing pre-trained visual models that are accurate, robust, and efficient for downstream tasks is a keystone of modern computer vision, but it poses challenges and knowledge gaps to existing unsupervised representation learning. Expected outcomes include new theories and algorithms for unsupervised visual pre-training ....Generative Visual Pre-training on Unlabelled Big Data. This project aims to develop a generative visual pre-training of large-scale deep neural networks on unlabelled big data. Developing pre-trained visual models that are accurate, robust, and efficient for downstream tasks is a keystone of modern computer vision, but it poses challenges and knowledge gaps to existing unsupervised representation learning. Expected outcomes include new theories and algorithms for unsupervised visual pre-training, which are anticipated to deepen our understanding of visual representation and make it easier to build and deploy computer vision applications and services. Examples of benefits include modernising machines in manufacturing and farming with visual intelligence. Read moreRead less
Improving novice drivers' speed and hazard management. The aim of the study is to extend the evidence-based approach we have developed for speed management (cognitive integration speed management training) to hazard management, thereby developing cognitive integration hazard management training for young drivers. Hence, this study is specifically designed to curb the alarming trend in young driver fatalities on Australian roads. The results of the research will provide clear direction to road au ....Improving novice drivers' speed and hazard management. The aim of the study is to extend the evidence-based approach we have developed for speed management (cognitive integration speed management training) to hazard management, thereby developing cognitive integration hazard management training for young drivers. Hence, this study is specifically designed to curb the alarming trend in young driver fatalities on Australian roads. The results of the research will provide clear direction to road authorities and driver training providers as to effective training strategies to improve young driver training, and ultimately improve road safety with this vulnerable population.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
Intercultural understanding in primary and secondary schools. What facilitates or impedes intercultural understanding in children, adolescents and schools? How can this be addressed? How can we know what makes a difference? This project answers these questions at the individual, school and national level using a novel cultural systems approach and methodological and technological innovations.
Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less