Learning to Reason in Reinforcement Learning. Deep Reinforcement Learning (RL) uses deep neural networks to represent and learn optimal decision-making policies for intelligent agents in complex environments. However, most RL approaches require millions of episodes to converge to good policies, making it difficult for RL to be applied in real-world scenarios taking significant resources. This project aims to equip RL with capabilities such as counterfactual reasoning and outcome anticipation to ....Learning to Reason in Reinforcement Learning. Deep Reinforcement Learning (RL) uses deep neural networks to represent and learn optimal decision-making policies for intelligent agents in complex environments. However, most RL approaches require millions of episodes to converge to good policies, making it difficult for RL to be applied in real-world scenarios taking significant resources. This project aims to equip RL with capabilities such as counterfactual reasoning and outcome anticipation to significantly reduce the number of interactions required, improve generalisation, and provide the agent with the capability to consider the cause-effects. These improvements would narrow the gap between AI and human capabilities and broaden the adoption of RL in real-world applications.Read moreRead less
Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the bui ....Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.Read moreRead less
Build competency aware and assuring machine learning systems. Recent development in machine learning (ML) has seen ML models with extremely high prediction accuracy. However, to support human-machine partnership in decision-making in complex environments, beyond accuracy, it is essential for ML systems to be competency aware and reliable, and at the same time be exploratory. This project aims to develop novel techniques to equip a ML system with the ability to identify own competency, to justify ....Build competency aware and assuring machine learning systems. Recent development in machine learning (ML) has seen ML models with extremely high prediction accuracy. However, to support human-machine partnership in decision-making in complex environments, beyond accuracy, it is essential for ML systems to be competency aware and reliable, and at the same time be exploratory. This project aims to develop novel techniques to equip a ML system with the ability to identify own competency, to justify its competency and decisions, to explore unknown situations and fully utilise existing expertise to deal with unknowns. The expected outcomes of the project will enable ML systems to become truely intelligent and reliable machine partners for human decision makers in a wide range of applications.Read moreRead less
Advancing the visualisation and quantification of nephrons with MRI. . This project aims to characterise key components of nephrons, the glomeruli and tubules, using magnetic resonance imaging without contrast agents, in combination with Deep Learning and super-resolution techniques. Nephrons, the basic functional unit of the kidney, are critical to the maintenance of the body’s homeostasis. Their number and architecture are critical determinants of kidney function. The expected outcomes are inn ....Advancing the visualisation and quantification of nephrons with MRI. . This project aims to characterise key components of nephrons, the glomeruli and tubules, using magnetic resonance imaging without contrast agents, in combination with Deep Learning and super-resolution techniques. Nephrons, the basic functional unit of the kidney, are critical to the maintenance of the body’s homeostasis. Their number and architecture are critical determinants of kidney function. The expected outcomes are innovative semi-automated nephron visualisation and quantitation tools that enable efficient renal phenotyping. Techniques tailored to widely accessible preclinical research scanners are expected to accelerate research into genetic and environmental factors affecting kidney microstructure in embryonic and post-natal life.Read moreRead less
Designed to last: novel gradient coatings for extreme environments. Hard coatings are frequently applied to equipment operating in harsh environments. Often such coatings are highly brittle and so fragile under stress, especially at high temperatures or in corrosive environments. Premature failure can affect safety and lead to negative economic and environmental consequences. The objective of this project is to combine bioinspired microstructural design with an emerging alloying concept to produ ....Designed to last: novel gradient coatings for extreme environments. Hard coatings are frequently applied to equipment operating in harsh environments. Often such coatings are highly brittle and so fragile under stress, especially at high temperatures or in corrosive environments. Premature failure can affect safety and lead to negative economic and environmental consequences. The objective of this project is to combine bioinspired microstructural design with an emerging alloying concept to produce a breakthrough in the development of engineering coatings; for example, overcoming the long standing trade-off between hardness and toughness. Such an innovative coating is expected to be highly durable in extreme conditions, and in so doing will help transform manufacturing, mining and desalination industries.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101773
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Ultra-tough coatings via materials engineering . This project aims to develop new generation coatings that combine highly controlled compositions and bio-inspired microstructural characteristics for safety-critical applications. This is made possible through smart materials design, multi-scale modelling and novel fabrication technique. The new coatings are expected to offer exceptionally high toughness underlain by a unique combination of various strengthening modes at multiple length scales. Th ....Ultra-tough coatings via materials engineering . This project aims to develop new generation coatings that combine highly controlled compositions and bio-inspired microstructural characteristics for safety-critical applications. This is made possible through smart materials design, multi-scale modelling and novel fabrication technique. The new coatings are expected to offer exceptionally high toughness underlain by a unique combination of various strengthening modes at multiple length scales. The application of the coatings will enhance the performance and safety of mechanical components in engineering applications, reduce associated costs. In doing so, this project will bring substantial benefits to advanced manufacturing, mining and aerospace sectors. Read moreRead less
Data analytics-based tools and methods to enhance self-regulated learning. This project aims to develop student self-regulated learning skills by harnessing the potential of Big Data analytics. The project expects to generate new knowledge at the intersection of learning analytics, educational technology, learning sciences and teaching practice resulting from novel data collection and analysis tools and methods. The outputs are expected to include insights into metacognitive, motivational, and t ....Data analytics-based tools and methods to enhance self-regulated learning. This project aims to develop student self-regulated learning skills by harnessing the potential of Big Data analytics. The project expects to generate new knowledge at the intersection of learning analytics, educational technology, learning sciences and teaching practice resulting from novel data collection and analysis tools and methods. The outputs are expected to include insights into metacognitive, motivational, and technical issues facing analytics-based personalised feedback. The outcomes are intended to offer benefits for developing pedagogical and the design of educational technology. The outcomes can result in improved student learning outcomes in higher education to ensure graduates are prepared for the digital economy.Read moreRead less
Teaching how to learn: promoting self-regulated learning in STEM classes. This project aims to investigate key factors that influence change in teacher practices and student achievement in Science, Technology, Engineering and Mathematics (STEM). It will involve the development and evaluation of interventions designed to help teachers create learning environments that promote student engagement and the development of the cognitive and metacognitive skills needed for success in STEM. The project w ....Teaching how to learn: promoting self-regulated learning in STEM classes. This project aims to investigate key factors that influence change in teacher practices and student achievement in Science, Technology, Engineering and Mathematics (STEM). It will involve the development and evaluation of interventions designed to help teachers create learning environments that promote student engagement and the development of the cognitive and metacognitive skills needed for success in STEM. The project will advance our understanding of how to increase the quality of teaching and learning in STEM subjects. Improving teacher capacity and student performance in STEM is a national priority with significant social and economic benefits to Australia.Read moreRead less
Literacy Instruction for Children with Autism. There is a social and economic imperative to assist all individuals to reach their full potential with regard to literacy skills. The central goal of the proposed research is to develop and evaluate new ways to support comprehensive literacy instruction for children with autism spectrum disorder (ASD). Following our world-first pilot research, we will investigate the efficacy of the ABRACADABRA literacy instruction program delivered in small groups ....Literacy Instruction for Children with Autism. There is a social and economic imperative to assist all individuals to reach their full potential with regard to literacy skills. The central goal of the proposed research is to develop and evaluate new ways to support comprehensive literacy instruction for children with autism spectrum disorder (ASD). Following our world-first pilot research, we will investigate the efficacy of the ABRACADABRA literacy instruction program delivered in small groups of children with ASD supplemented by a novel parent-child shared book reading program. Immediate outcomes extend beyond advances in the science of reading to upskilling parents and professionals who support children with ASD, and provision of tangible life-long benefits for individuals with ASD.Read moreRead less
Learning how people read: Models, brains, big data and maths. Aims: This project aims to understand how people read. We will use novel mathematical methods, experimentation, brain imaging and computational modelling to adjudicate between model predictions.
Significance: This project expects to develop methods to understand and test important aspects of reading.
Expected outcomes: Expected outcomes are the development of novel methods for understanding complex models and the collection of data t ....Learning how people read: Models, brains, big data and maths. Aims: This project aims to understand how people read. We will use novel mathematical methods, experimentation, brain imaging and computational modelling to adjudicate between model predictions.
Significance: This project expects to develop methods to understand and test important aspects of reading.
Expected outcomes: Expected outcomes are the development of novel methods for understanding complex models and the collection of data that can extend and falsify current models of reading.
Benefits: These developments will significantly increase our understanding of how people read and what causes dyslexia. This work will also provide new ways to evaluate complex computational psychological models.Read moreRead less