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
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
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
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
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
Control and learning for enhancing capabilities of quantum sensors. This project aims to develop new theories and algorithms to enhance capabilities in engineering quantum sensors from the perspective of systems and control. The project is significant because it is anticipated to advance key knowledge and provide systematic methods to enable achievement of high-precision sensing for wide applications, e.g., early disease detection, medical research, discovery of ore deposits and groundwater moni ....Control and learning for enhancing capabilities of quantum sensors. This project aims to develop new theories and algorithms to enhance capabilities in engineering quantum sensors from the perspective of systems and control. The project is significant because it is anticipated to advance key knowledge and provide systematic methods to enable achievement of high-precision sensing for wide applications, e.g., early disease detection, medical research, discovery of ore deposits and groundwater monitoring. The intended outcomes are fundamental theories, effective control and learning algorithms for achieving highly-sensitive sensors. These outcomes should make important contributions to and deliver new knowledge and skills for Australia's sensing industries, which could benefit Australia's economic growth.Read moreRead less
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