Economic analysis of child maltreatment and child protection. This project aims to investigate the economic causes and consequences of child maltreatment. It expects to generate new knowledge by applying microeconometric methods to large Australian administrative databases that track children’s health, education and welfare receipt over time. The expected outcomes of this project include an expanded knowledge base on how economic shocks affect maltreatment, the economic consequences of placing c ....Economic analysis of child maltreatment and child protection. This project aims to investigate the economic causes and consequences of child maltreatment. It expects to generate new knowledge by applying microeconometric methods to large Australian administrative databases that track children’s health, education and welfare receipt over time. The expected outcomes of this project include an expanded knowledge base on how economic shocks affect maltreatment, the economic consequences of placing children in out-of-home care, and the value of economic policies for reducing the intergenerational transmission of maltreatment. This should provide significant benefits, such as providing practical evidence to policy makers and service providers that help prevent child maltreatment and reduce its harms.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
Towards knowledge discovery from imperfect and evolving data. Information extraction from data is critical, both to analyse and protect consumer data. However, many learning techniques are developed using perfect, static datasets, quite different to messy, ever-changing real-world data. This project aims to develop data analytics techniques that can extract accurate information in complex structures from imperfect/incomplete data that changes over time. Expected outcomes are a prototype tool, te ....Towards knowledge discovery from imperfect and evolving data. Information extraction from data is critical, both to analyse and protect consumer data. However, many learning techniques are developed using perfect, static datasets, quite different to messy, ever-changing real-world data. This project aims to develop data analytics techniques that can extract accurate information in complex structures from imperfect/incomplete data that changes over time. Expected outcomes are a prototype tool, tested on real datasets, that combines new techniques in data modelling, algorithm development, and system design. Likely benefits are enhanced Australia's competence in data science through student training and new, robust data tools relevant to critical sectors such as cybersecurity, healthcare, and defence.Read moreRead less
The culture of implementing Freedom of Information in Australia. In partnership with three Australian Information Commissioners/Ombudsmen this project aims to map the culture of administering Freedom of Information (FOI) laws across a number of Australian jurisdictions. The study aspires to capture and analyse the attitudes among FOI practitioners, government agency managements and political leaders toward information access implementation. The project aims to provide the partner organisations w ....The culture of implementing Freedom of Information in Australia. In partnership with three Australian Information Commissioners/Ombudsmen this project aims to map the culture of administering Freedom of Information (FOI) laws across a number of Australian jurisdictions. The study aspires to capture and analyse the attitudes among FOI practitioners, government agency managements and political leaders toward information access implementation. The project aims to provide the partner organisations with an increased understanding of the culture of administering FOI to inform training/awareness programs and campaigns in order to increase the functionality of FOI. Well-functioning access to information systems is crucial both for good governance and Australia's participation in the digital economy.
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Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100539
Funder
Australian Research Council
Funding Amount
$408,000.00
Summary
Towards conversational vision-based Artificial Intelligence. This project aims to develop a novel learning framework, Vision-Ask-Answer-Act (V3A). This framework will allow a machine to perform a sequence of actions via a conversation with human users, based on intricate processing of not just visual input, but human-computer verbal exchanges. Artificial intelligence has great potential as a tool for economic productivity and daily tasks. Applications in cars and assistant robots, still in their ....Towards conversational vision-based Artificial Intelligence. This project aims to develop a novel learning framework, Vision-Ask-Answer-Act (V3A). This framework will allow a machine to perform a sequence of actions via a conversation with human users, based on intricate processing of not just visual input, but human-computer verbal exchanges. Artificial intelligence has great potential as a tool for economic productivity and daily tasks. Applications in cars and assistant robots, still in their early days, typically require significant expertise to use effectively. The outcomes of this project will push the boundary of vision-language research to produce a conversational intelligent agent that can be easily used in common situations across industry, transport, the medical sector, and at home.Read moreRead less
Real-time scheduling of trains to control peak electricity demand. This project aims to develop new scheduling and control methods that will enable railways to reduce their demand for electricity during peak demand periods, without undue disruption to the timetable.
These new methods and systems will integrate with—and expand the capabilities of—an Australian train control system that is used by railways around the world. This will enable better management of electricity within a region and be ....Real-time scheduling of trains to control peak electricity demand. This project aims to develop new scheduling and control methods that will enable railways to reduce their demand for electricity during peak demand periods, without undue disruption to the timetable.
These new methods and systems will integrate with—and expand the capabilities of—an Australian train control system that is used by railways around the world. This will enable better management of electricity within a region and better use of renewable energy sources, with significant cost savings for railways and the wider community.Read moreRead less
Fairness aware data mining for discrimination free decision-making. This project aims to develop data mining methods to detect algorithmic discriminations and to build fair decision models. It expects to provide techniques for regulatory organisations to detect discriminations in algorithmic decisions, and for various companies and organisations to build fair decision systems. Expected outcomes are novel and accurate methods for discrimination detection, practical and versatile techniques for fa ....Fairness aware data mining for discrimination free decision-making. This project aims to develop data mining methods to detect algorithmic discriminations and to build fair decision models. It expects to provide techniques for regulatory organisations to detect discriminations in algorithmic decisions, and for various companies and organisations to build fair decision systems. Expected outcomes are novel and accurate methods for discrimination detection, practical and versatile techniques for fair decision model building, and improved understanding of the relationships between privacy preservation and discrimination prevention to enable new techniques to achieve both goals. The developed techniques enable society to tackle ethical challenges in the big data era where many decisions are analytics based. Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100119
Funder
Australian Research Council
Funding Amount
$427,111.00
Summary
Towards Internet of Things Enabled Automated Mushroom Cultivation. This project aims to develop novel Internet-of-Things based learning techniques to inform the design and construction of a portable, automated system for the cultivation of mushrooms. The expected outcomes are a portable smart mushroom cultivation system that provides access to new agriculture techniques and local, fresh supplies in rural and remote areas; learning algorithms that detect mushroom ripeness and set the best environ ....Towards Internet of Things Enabled Automated Mushroom Cultivation. This project aims to develop novel Internet-of-Things based learning techniques to inform the design and construction of a portable, automated system for the cultivation of mushrooms. The expected outcomes are a portable smart mushroom cultivation system that provides access to new agriculture techniques and local, fresh supplies in rural and remote areas; learning algorithms that detect mushroom ripeness and set the best environmental parameters; and a dataset of mushroom cultivation parameters. These products, and associated training opportunities through a strong focus on public and industry engagement, will benefit the industry partners and horticultural producers to improve resource efficiency, waste reduction, and overall yield.Read moreRead less
Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed ....Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly. Read moreRead less