Quantifying Ethics-related Metrics for Transport Network Systems. This project aims to identify ethics-related metrics for improving the design of transport network services, and augment the social benefits of transport systems to relevant user groups. This project is anticipated to conceive, implement and validate new methodologies to solve challenging optimisation problems aiming at promoting ethics in transport systems via the provision of incentives to transport services providers. The outco ....Quantifying Ethics-related Metrics for Transport Network Systems. This project aims to identify ethics-related metrics for improving the design of transport network services, and augment the social benefits of transport systems to relevant user groups. This project is anticipated to conceive, implement and validate new methodologies to solve challenging optimisation problems aiming at promoting ethics in transport systems via the provision of incentives to transport services providers. The outcomes of this project are expected to support the emergence of ethical transport systems and to address fundamental societal and economical challenges induced by utility-driven transport services. This project will help in positioning Australia as a global leader in the field of ethical transport network systems.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
Stable on-demand optimization for workforce and fleet logistics management. This project aims to conceive, develop and deploy innovative methodologies for stable on-demand workforce management and fleet logistics based on advanced decision-support systems. The outcome of this project will provide a new cloud-based real-time Optimisation Software-as-a-Service (OSaaS) platform that allows businesses to improve their productivity while reducing operating costs and their environmental footprint. Thi ....Stable on-demand optimization for workforce and fleet logistics management. This project aims to conceive, develop and deploy innovative methodologies for stable on-demand workforce management and fleet logistics based on advanced decision-support systems. The outcome of this project will provide a new cloud-based real-time Optimisation Software-as-a-Service (OSaaS) platform that allows businesses to improve their productivity while reducing operating costs and their environmental footprint. This is expected to support the manufacturing, retail, delivery and mobile fleets industries.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
Incentivised strategic traffic assignment: bi-level transport optimisation. This project aims to advance the fundamental knowledge base and methodological modelling capacity related to traffic network assignment representing complex incentive structures such as network pricing, behavioural shift inducement, dynamic speed control and information-provision. Expected outcomes include new equilibrium formulations characterising traveller responses to, and interactions with, incentive structures whil ....Incentivised strategic traffic assignment: bi-level transport optimisation. This project aims to advance the fundamental knowledge base and methodological modelling capacity related to traffic network assignment representing complex incentive structures such as network pricing, behavioural shift inducement, dynamic speed control and information-provision. Expected outcomes include new equilibrium formulations characterising traveller responses to, and interactions with, incentive structures while maintaining complex stochastic adaptive behaviours from previous research, new network routing algorithms, and a novel bi-level optimisation approach for seeking optimal incentive policies. The project will provide a scientific basis for the quantified network evaluation of incentivisation strategies that will support enhanced transport planning thereby improving mobility across society.Read moreRead less
Advancing future primary teachers' engagement in science inquiry learning. Australia's challenges in regard to scientific literacy and growth of student enrolments in science need to be addressed at multiple levels, starting with the preparation of future primary teachers. Promoting children's early interest in inquiry-based science is essential, yet a challenge for many teachers. This project examines the complex and dynamic interplay of cognitive, metacognitive and emotional processes in futur ....Advancing future primary teachers' engagement in science inquiry learning. Australia's challenges in regard to scientific literacy and growth of student enrolments in science need to be addressed at multiple levels, starting with the preparation of future primary teachers. Promoting children's early interest in inquiry-based science is essential, yet a challenge for many teachers. This project examines the complex and dynamic interplay of cognitive, metacognitive and emotional processes in future primary teachers' engagement in collaborative inquiry-based science activities. A comprehensive intervention based on these insights aims to determine how scaffolding productive engagement can improve the quality of primary teachers' preparation for inquiry-based science.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
Discovery Early Career Researcher Award - Grant ID: DE210101881
Funder
Australian Research Council
Funding Amount
$407,390.00
Summary
Building STEM capacity through literacy engagement in spatial reasoning. This project aims to improve boys and girls' spatial reasoning in preschool (when gender differences emerge) by utilizing an activity that both genders equally access: book reading. Spatial reasoning is critical to achievement in science, technology, engineering and mathematics (STEM). This project will address disproportionate outcomes in spatial reasoning and STEM achievement, particularly among females, by identifying ef ....Building STEM capacity through literacy engagement in spatial reasoning. This project aims to improve boys and girls' spatial reasoning in preschool (when gender differences emerge) by utilizing an activity that both genders equally access: book reading. Spatial reasoning is critical to achievement in science, technology, engineering and mathematics (STEM). This project will address disproportionate outcomes in spatial reasoning and STEM achievement, particularly among females, by identifying effective kinds of spatial learning opportunities for the preschool context. Expected outcomes include an innovative approach to improving spatial reasoning through literacy engagement. This provides significant benefits by creating pathways into STEM and informing targeted interventions.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100750
Funder
Australian Research Council
Funding Amount
$370,000.00
Summary
The Effects of Energy Subsidy Reform: The Case of Indonesia. This project plans to analyse and quantify the effects of energy subsidy reductions on environmental, transport, health, socioeconomic and industrial outcomes. Using econometric methods, the project aims to assess recent reductions in subsidies for fuel and electricity in Indonesia. Energy subsidies have been a large drain on many governments’ budgets and are often thought to bring perverse effects. The project may provide a blueprint ....The Effects of Energy Subsidy Reform: The Case of Indonesia. This project plans to analyse and quantify the effects of energy subsidy reductions on environmental, transport, health, socioeconomic and industrial outcomes. Using econometric methods, the project aims to assess recent reductions in subsidies for fuel and electricity in Indonesia. Energy subsidies have been a large drain on many governments’ budgets and are often thought to bring perverse effects. The project may provide a blueprint for the design of future reforms in Indonesia and elsewhere, with the goal of addressing serious issues such as air pollution and traffic congestion while avoiding adverse consequences for the poor. The project also aims to assist budget forecasting and guide economic models on the effects of fiscal settings for energy.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100113
Funder
Australian Research Council
Funding Amount
$390,000.00
Summary
Travel Choice Simulation Laboratory (TRACSLab): a visualisation laboratory to study travel behaviour and drivers’ interactions. Travel Choice Simulation Laboratory (TRACSLab) is a world-first facility to observe collective travel choice in a realistic lab environment. It is unique due to the focus on travel choice, networked interaction and strong teaming. The findings of the lab will support a new generation of transport analysis techniques for emerging issues such as sustainability, reliabili ....Travel Choice Simulation Laboratory (TRACSLab): a visualisation laboratory to study travel behaviour and drivers’ interactions. Travel Choice Simulation Laboratory (TRACSLab) is a world-first facility to observe collective travel choice in a realistic lab environment. It is unique due to the focus on travel choice, networked interaction and strong teaming. The findings of the lab will support a new generation of transport analysis techniques for emerging issues such as sustainability, reliability, and intelligent transport systems (ITS).Read moreRead less