Discovery Early Career Researcher Award - Grant ID: DE200100898
Funder
Australian Research Council
Funding Amount
$421,979.00
Summary
Information Embodiment Framework for Education using Immersive Technologies. The project aims to develop a framework to apply mixed reality technologies in education, by fusing the information with human physical, physiological, cognitive and emotional perceptions. The current approach translates existing contents into 3D which does not scale and causes cognitive overload. The project conceptually advances the design and development of mixed reality applications. The expected outcome is a mixed ....Information Embodiment Framework for Education using Immersive Technologies. The project aims to develop a framework to apply mixed reality technologies in education, by fusing the information with human physical, physiological, cognitive and emotional perceptions. The current approach translates existing contents into 3D which does not scale and causes cognitive overload. The project conceptually advances the design and development of mixed reality applications. The expected outcome is a mixed reality integration framework for effective communication, applicable to manufacturing, health, tourism and arts. The benefits are enhanced learning with engaging resources, with positive impact on student learning outcomes and motivation, in both formal and informal education settings such as schools, galleries, and museums.Read moreRead less
Advancing Human–robot Interaction with Augmented Reality. This research aims to advance emerging human-robot interaction (HRI) methods, creating novel and innovative, human-in-the-loop communication, collaboration, and teaching methods. The project expects to support the creation of new applications for the growing wave of assistive robotic platforms emerging in the market and de-risk the integration of collaborative robotics into industrial production. Expected outcomes include methods and tool ....Advancing Human–robot Interaction with Augmented Reality. This research aims to advance emerging human-robot interaction (HRI) methods, creating novel and innovative, human-in-the-loop communication, collaboration, and teaching methods. The project expects to support the creation of new applications for the growing wave of assistive robotic platforms emerging in the market and de-risk the integration of collaborative robotics into industrial production. Expected outcomes include methods and tools developed to allow smart leveraging of the different capacities of humans and robots. This should provide significant benefits allowing manufacturers to capitalize on the high skill level of Australian workers and bring more complex high-value manufactured products to market. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101623
Funder
Australian Research Council
Funding Amount
$456,450.00
Summary
High-Fidelity Motion Simulator using Sickness-Free Motion Cueing Algorithm. This project aims to address the key deficiencies of driving and flight simulators by developing novel human perception-based motion cueing algorithms (MCAs) and leveraging advanced artificial intelligence techniques. Despite widespread applications, existing motion simulators fail to deliver the most accurate human sensation to the user. This failure is mainly attributable to the inefficiency and inflexibility of MCAs u ....High-Fidelity Motion Simulator using Sickness-Free Motion Cueing Algorithm. This project aims to address the key deficiencies of driving and flight simulators by developing novel human perception-based motion cueing algorithms (MCAs) and leveraging advanced artificial intelligence techniques. Despite widespread applications, existing motion simulators fail to deliver the most accurate human sensation to the user. This failure is mainly attributable to the inefficiency and inflexibility of MCAs used by simulators. It is expected that this project will significantly increase simulator motion fidelity and eliminate motion sickness. This will have substantial benefits to Australian research communities and industries, particularly where simulators are used for training, performance evaluation and virtual prototyping.Read moreRead less
Parametric VR: An Interactive Virtual Reality System for Parametric Design. This project aims to create a new and intuitive set of user interactions for Virtual Reality (VR) to support parametric designers in architecture and design. Parametric tools are an emerging design technology dominating contemporary practices, yet their interfaces are on traditional desktop computers while VR is only employed to visualise the geometric models produced by the end design. This project will generate Paramet ....Parametric VR: An Interactive Virtual Reality System for Parametric Design. This project aims to create a new and intuitive set of user interactions for Virtual Reality (VR) to support parametric designers in architecture and design. Parametric tools are an emerging design technology dominating contemporary practices, yet their interfaces are on traditional desktop computers while VR is only employed to visualise the geometric models produced by the end design. This project will generate Parametric VR, a system of VR tools to support parametric design. Key outcomes include software tools and demonstrators to support parametric algorithms and processes in VR. This will have significant benefits for design industries, allowing designers to directly edit parametric design entirely in VR across the project lifecycle.Read moreRead less
Immersive analytics: interactive data analysis using surfaces and spaces. This project aims to explore the potential for new immersive display and interaction technologies to greatly enhance the field of visual data analytics. Humans struggle to understand the masses of complex data they now accumulate. Visual data analytics offers a solution. The project expects to provide practical and theoretical frameworks for immersive data analysis and valuable intellectual property on the first practical ....Immersive analytics: interactive data analysis using surfaces and spaces. This project aims to explore the potential for new immersive display and interaction technologies to greatly enhance the field of visual data analytics. Humans struggle to understand the masses of complex data they now accumulate. Visual data analytics offers a solution. The project expects to provide practical and theoretical frameworks for immersive data analysis and valuable intellectual property on the first practical tools for immersive data analytics. This will provide significant benefits, such as allowing those across government and industry to make more informed decisions from data.Read moreRead less
Personalised public transport. This project aims to address urban congestion by utilising people’s travel plans to coordinate journeys. The project expects to generate new knowledge in scalable optimisation, based on innovative modelling of urban transport, and tested on historical data from Melbourne. The expected outcomes of the project are an active transport database and optimised mode choice and routing system, with predicted reductions in congestion based on simulation of its use. This pro ....Personalised public transport. This project aims to address urban congestion by utilising people’s travel plans to coordinate journeys. The project expects to generate new knowledge in scalable optimisation, based on innovative modelling of urban transport, and tested on historical data from Melbourne. The expected outcomes of the project are an active transport database and optimised mode choice and routing system, with predicted reductions in congestion based on simulation of its use. This project aims to design an urban trip advisory system that could be followed by automated vehicles as well as human drivers, to reduce the financial and environmental cost of current urban congestion.Read moreRead less
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101511
Funder
Australian Research Council
Funding Amount
$424,816.00
Summary
Structural insights into activation, dynamics and bias of GPCRs. The project aims to investigate the mechanisms underlying activation, biased agonism and G protein selectivity of G protein-coupled receptors (GPCRs) by utilising the adenosine A1 receptor as a model system. This project expects to generate knowledge in the area of GPCR biology using an interdisciplinary approach including structural biology, pharmacology, biochemistry and protein engineering. The expected outcomes include (i) unde ....Structural insights into activation, dynamics and bias of GPCRs. The project aims to investigate the mechanisms underlying activation, biased agonism and G protein selectivity of G protein-coupled receptors (GPCRs) by utilising the adenosine A1 receptor as a model system. This project expects to generate knowledge in the area of GPCR biology using an interdisciplinary approach including structural biology, pharmacology, biochemistry and protein engineering. The expected outcomes include (i) understanding the structural mechanisms underlying GPCR activation, (ii) biased agonism and (iii) G protein selectivity. This should provide significant benefits, such as advancement of fundamental knowledge in GPCR biology and pharmacology that could also one day lead to therapeutic development.Read moreRead less