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
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
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
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
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
Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications ....Spatial Cognition—Expressive Representation Formalisms and Effective Reasoning Mechanisms. The project will contribute significantly to the advancement of knowledge in breakthrough science in qualitative spatial reasoning and smart information use in geographic information systems. Expressive spatial languages are important in organising spatial knowledge, defining spatial query languages and guiding spatial data mining. Effective spatial reasoning mechanisms bring theory closer to applications including consistency checking and spatial query pre-processing. The project will help in extracting knowledge from massive spatial databases, meeting the growing needs of naive users for spatial information and establishing Australia as a major player in spatial cognition research and in the development of geo-location services.Read moreRead less