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
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
Building on rural knowledges to unlock the potential of rural students. This project aims to advance understanding of the distinctive knowledges that rural students bring to school and develop teaching practices that build on these rural knowledges to unlock the potential of this significant student population. The project involves collaborating with rural primary schools, teachers, students and communities to identify rural knowledges, study classroom practices in detail, and develop sustainabl ....Building on rural knowledges to unlock the potential of rural students. This project aims to advance understanding of the distinctive knowledges that rural students bring to school and develop teaching practices that build on these rural knowledges to unlock the potential of this significant student population. The project involves collaborating with rural primary schools, teachers, students and communities to identify rural knowledges, study classroom practices in detail, and develop sustainable teaching practices that help students connect rural knowledges and school knowledge. Expected outcomes include a framework of place-based teaching practices and resources that will benefit rural schooling, teacher education, and the education of communities crucial to the nation’s future wealth and welfare.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
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
Structural safety guidelines for accidental hydrogen explosion hazards . This project aims to develop structural safety guidelines to mitigate hydrogen explosion hazards which can be identified as a major safety concern due to the higher demand worldwide for sustainable energy sources with no carbon emission. The world’s growing demand for hydrogen and Australia’s National Hydrogen Strategy to develop the industry will make Australia a core player in hydrogen production creating a massive econom ....Structural safety guidelines for accidental hydrogen explosion hazards . This project aims to develop structural safety guidelines to mitigate hydrogen explosion hazards which can be identified as a major safety concern due to the higher demand worldwide for sustainable energy sources with no carbon emission. The world’s growing demand for hydrogen and Australia’s National Hydrogen Strategy to develop the industry will make Australia a core player in hydrogen production creating a massive economic opportunity. However, the high flammability and low ignition energy of hydrogen makes it vulnerable to accidental explosions. Hence, this project will address the lack of safety protocols in Australian Standards related to the handling of hydrogen by producing essential design recommendations.Read moreRead less
Hydrogen generation by subsurface iron mineral transformations. Aim
The aim of this project is to elucidate key factors responsible for natural hydrogen generation in Australian subsurface environments.
Significance
Large amounts of this valuable resource are produced naturally with estimates of production rates of this “gold” hydrogen at least 100 times the annual demand for this critical resource.
Expected Outcomes
Based on improved understanding of the source of natural hydrogen, predictive ....Hydrogen generation by subsurface iron mineral transformations. Aim
The aim of this project is to elucidate key factors responsible for natural hydrogen generation in Australian subsurface environments.
Significance
Large amounts of this valuable resource are produced naturally with estimates of production rates of this “gold” hydrogen at least 100 times the annual demand for this critical resource.
Expected Outcomes
Based on improved understanding of the source of natural hydrogen, predictive tools will be developed that will assist in assessing the viability in Australia of hydrogen exploration and engineered retrieval.
Benefits
Ready access to naturally produced hydrogen could enable Australia to replace hydrogen that is currently generated via the use of unabated hydrocarbons.Read moreRead less
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
Tracking flood waters over Australia using space gravity data. This project aims to assess the utility of near-real-time data from the currently operating space gravity satellite mission to quantify and track flood waters in Australia. Through analysis of the satellite data and fusion of observed signals with rainfall, river flows and conventional hydrological modelling, it expects to create new knowledge of soil moisture and movement of flood waters. Expected outcomes include a capability to im ....Tracking flood waters over Australia using space gravity data. This project aims to assess the utility of near-real-time data from the currently operating space gravity satellite mission to quantify and track flood waters in Australia. Through analysis of the satellite data and fusion of observed signals with rainfall, river flows and conventional hydrological modelling, it expects to create new knowledge of soil moisture and movement of flood waters. Expected outcomes include a capability to improve hydrological models by including the information of water signals obtained from the near-real-time observations. This should provide significant benefits such as more accurate land saturation maps and better predictions of runoff and flood risk.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100031
Funder
Australian Research Council
Funding Amount
$3,973,202.00
Summary
ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand ....ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.Read moreRead less