Interacting with visualisations of extremely large graph structures on large displays. The latest technological progressions have delivered very large data sets that can be modelled as graphs or networks. Examples include: social networks, biological data, and software structures. This project will develop techniques to allow users to visualise the graphs in the entirety and directly interact with data.
Discovery Early Career Researcher Award - Grant ID: DE180101416
Funder
Australian Research Council
Funding Amount
$338,446.00
Summary
Broadening horizons: using curiosity to diversify behaviour. This project aims to explore how interactive systems can encourage their users to try new things. This is made possible by recent developments in artificial intelligence that can estimate what will make users curious. This project expects to generate new knowledge about how interactive technology can encourage diverse behaviour by stimulating curiosity. Expected outcomes include a framework for how to design interactive systems that en ....Broadening horizons: using curiosity to diversify behaviour. This project aims to explore how interactive systems can encourage their users to try new things. This is made possible by recent developments in artificial intelligence that can estimate what will make users curious. This project expects to generate new knowledge about how interactive technology can encourage diverse behaviour by stimulating curiosity. Expected outcomes include a framework for how to design interactive systems that encourage users to try new things, and a greater theoretical understanding of how to diversify user behaviour.Read moreRead less
Affective sensing technology for the detection and monitoring of depression and melancholia. This project will develop reliable and affective sensing technology and evaluate it as an objective measure of depressive disorders; a leading cause of disability worldwide. Outcomes will significantly support and aid clinicians in their diagnosis and treatment, thus providing a major breakthrough with significant research, healthcare and commercial possibilities.
Discovery Early Career Researcher Award - Grant ID: DE200100479
Funder
Australian Research Council
Funding Amount
$427,116.00
Summary
A Unified Framework to Rapidly Fabricate Individualised Activity Sensors. This proposal aims to develop a unified computational framework which enables non-expert users to co-design and fabricate specialised physical activity sensors to address individualised sensing problems in applications such as rehabilitation, age-care and sports. Specifically, we will develop an analytical framework to classify complex sensing problems into fabricable primitive classes, namely i) conditional – limits of ac ....A Unified Framework to Rapidly Fabricate Individualised Activity Sensors. This proposal aims to develop a unified computational framework which enables non-expert users to co-design and fabricate specialised physical activity sensors to address individualised sensing problems in applications such as rehabilitation, age-care and sports. Specifically, we will develop an analytical framework to classify complex sensing problems into fabricable primitive classes, namely i) conditional – limits of activity, ii) differential – frequency of activity and iii) integrational – cumulative activity. And a co-design interface to synthesize them into complex activity sensors to fit individualised needs. Finally, we will evaluate the framework by deploying the created sensors in real-world settings and gathering data.Read moreRead less
Cognitive intelligent information processing and presentation in navigation. This project aims to develop a personalised navigation system to provide effective augmented-reality (AR)-based support information, built on different navigation preference and the momentary cognitive workload of the user. This will immediately encourage users to become aware of their surroundings and continuous use will facilitate the development of navigation skills. It is expected that this research will advance sci ....Cognitive intelligent information processing and presentation in navigation. This project aims to develop a personalised navigation system to provide effective augmented-reality (AR)-based support information, built on different navigation preference and the momentary cognitive workload of the user. This will immediately encourage users to become aware of their surroundings and continuous use will facilitate the development of navigation skills. It is expected that this research will advance scientific knowledge about individual differences in navigation ability. It will significantly enhance spatial learning and alleviate the apparent decline in navigational ability experienced across the life span, benefiting the aged population in Australia by enabling them to live longer independent lives.Read moreRead less
AI-Human Empowered Team Decision-Making. This project aims to introduce machine intelligence into human team decision-making using the brain-to-brain synchrony that arises when people cooperate toward achieving a goal. The expected outcomes are models and indicators of this synchrony, and methods to fuse individual human decisions with autonomous machine agents, into collective decisions. This new knowledge is expected to greatly increase our understanding of cooperative decision-making by human ....AI-Human Empowered Team Decision-Making. This project aims to introduce machine intelligence into human team decision-making using the brain-to-brain synchrony that arises when people cooperate toward achieving a goal. The expected outcomes are models and indicators of this synchrony, and methods to fuse individual human decisions with autonomous machine agents, into collective decisions. This new knowledge is expected to greatly increase our understanding of cooperative decision-making by humans and machine agents. The tools produced are expected to provide a computational basis for human-autonomy teaming, the core of Industry 5.0, that software developers and end-users in various industries could further build upon to optimise complex decision-making to benefit humanity.Read moreRead less
Remote presence for guidance on physical tasks. This project aims to transform remote collaboration on physical tasks. Current systems for remote collaboration on physical tasks are not as effective as working face-to-face. This could be overcome by sharing non-verbal cues, designing systems to account for cultural issues, and using a new model of communication. This project will develop theories and interaction methods for remote guidance based on natural non-verbal communication cues and cultu ....Remote presence for guidance on physical tasks. This project aims to transform remote collaboration on physical tasks. Current systems for remote collaboration on physical tasks are not as effective as working face-to-face. This could be overcome by sharing non-verbal cues, designing systems to account for cultural issues, and using a new model of communication. This project will develop theories and interaction methods for remote guidance based on natural non-verbal communication cues and cultural issues. This project is expected to benefit industries with widely distributed multi-cultural workforces such as mining, defence and medicine.Read moreRead less
Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. Th ....Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. The model and algorithms are intended to be integrated into an innovative brain-robot interface for field testing in a real-world industrial task. Translation of the outcomes to industry is expected to produce substantial economic and societal benefits through improved productivity and safety.Read moreRead less
A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general fra ....A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general framework to facilitate human-machine interaction and enable better collaborative decisions in HMAS. The outcomes will benefit human-centric automation systems in general and next-generation autonomous vehicles in particular, which will contribute to the Australian economy.Read moreRead less