Young children in digital society: An Online Tool for service provision . This project aims to identify the practices enacted and shared amongst young children, their families and educators in digital society.The project is significant because in digital society families and educators face new demands ensuring technologies are used in the best interests of young children. Knowledge about practices in digital society informs adult decision-making using technologies with, by and for young children ....Young children in digital society: An Online Tool for service provision . This project aims to identify the practices enacted and shared amongst young children, their families and educators in digital society.The project is significant because in digital society families and educators face new demands ensuring technologies are used in the best interests of young children. Knowledge about practices in digital society informs adult decision-making using technologies with, by and for young children in the early years. The outcome is a new Online Tool for the Partner Organisations to share exemplar practices benefiting Australian children, their families and educators with new resources, materials and programs in areas including: digital media production, cyber-safety education, digital play and digital parenting.
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Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application will not only maintain Australia's leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as cyber security, healthcare, and e-Commerce.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less
Architectural Work Cultures: professional identity, education and wellbeing. This project aims to examine the work and study cultures of architecture in Australia, in relation to professional identity, and in terms of impact on wellbeing, with a whole-of-career scope spanning education to retirement. It will generate the first comprehensive account of work-related wellbeing problems for both architectural practitioners and students, via qualitative and quantitative methods and a vigorous engagem ....Architectural Work Cultures: professional identity, education and wellbeing. This project aims to examine the work and study cultures of architecture in Australia, in relation to professional identity, and in terms of impact on wellbeing, with a whole-of-career scope spanning education to retirement. It will generate the first comprehensive account of work-related wellbeing problems for both architectural practitioners and students, via qualitative and quantitative methods and a vigorous engagement with the profession. Expected outcomes include two toolkits to assist the profession to support cultural change across educational, workplace and institutional settings. This should provide significant benefits for the wellbeing of architects at all career stages, and also support the long-term viability of the sector.Read moreRead less
Socially Responsible Insurance in the Age of Artificial Intelligence. This project aims to discover the social costs and benefits of using Artificial Intelligence in insurance, and to design practical interventions—responsible design workshops, practical guidance, regulatory proposals, new algorithmic tools—that realise the benefits while mitigating the costs. It expects to generate new knowledge drawing on philosophy, law and sociology, working closely with practitioners at the forefront of dep ....Socially Responsible Insurance in the Age of Artificial Intelligence. This project aims to discover the social costs and benefits of using Artificial Intelligence in insurance, and to design practical interventions—responsible design workshops, practical guidance, regulatory proposals, new algorithmic tools—that realise the benefits while mitigating the costs. It expects to generate new knowledge drawing on philosophy, law and sociology, working closely with practitioners at the forefront of deploying AI in insurance. Expected outcomes include novel ethical AI-based approaches to product design, pricing and claims administration. This should benefit insurers and consumers, realising efficiency gains made possible by AI, without unacceptable costs to privacy, fairness, and the unaccountable exercise of power. Read moreRead less
Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, ....Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, statistics and different ways of aggregating information. By building a more complete theoretical map it is expected that new machine learning methods will be developed, but more importantly that machine learning will be able to be better integrated into larger socio-technical systems.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE170100033
Funder
Australian Research Council
Funding Amount
$900,000.00
Summary
Australian Acoustic Observatory: A network to monitor biodiversity. This project aims to create a terrestrial acoustic sensor network comprising 450 listening stations across Australia. Acoustic sensing transforms environmental science by recording vocal species 24/7, providing spatial and temporal data for ecosystem monitoring and research. Australia has leading research expertise in this emerging field, which is relevant to its fragile and mega-diverse environment. This project is expected to ....Australian Acoustic Observatory: A network to monitor biodiversity. This project aims to create a terrestrial acoustic sensor network comprising 450 listening stations across Australia. Acoustic sensing transforms environmental science by recording vocal species 24/7, providing spatial and temporal data for ecosystem monitoring and research. Australia has leading research expertise in this emerging field, which is relevant to its fragile and mega-diverse environment. This project is expected to enable and develop continental scale environmental monitoring, and the data generated will be made freely available to all online, enabling new science in understanding ecosystems, long-term environmental change, data visualisation and acoustic science.Read moreRead less