Discovery Early Career Researcher Award - Grant ID: DE240100623
Funder
Australian Research Council
Funding Amount
$412,037.00
Summary
New electrodes for green electrochemical carbon dioxide capture. This project aims to develop new electrochemical carbon capture technology. By designing and fabricating new functional electrodes and high-performance electrochemical devices based on water and driven by renewable electricity, this project will enhance the ability to capture CO2, the primary greenhouse gas that causes global climate change. Expected outcomes include new multi-dimension electrodes with unique chemistry and state-of ....New electrodes for green electrochemical carbon dioxide capture. This project aims to develop new electrochemical carbon capture technology. By designing and fabricating new functional electrodes and high-performance electrochemical devices based on water and driven by renewable electricity, this project will enhance the ability to capture CO2, the primary greenhouse gas that causes global climate change. Expected outcomes include new multi-dimension electrodes with unique chemistry and state-of-the-art CO2 capture devices plus in-depth knowledge of electrochemical CO2 capture mechanisms for optimised device design and control. Benefits include the development of circular carbon economies with capabilities to effectively capture CO2, supporting Australian industries to achieve net zero emissions by 2050.Read moreRead less
ARC Centre of Excellence for Carbon Science and Innovation. ARC Centre of Excellence for Carbon Science and Innovation. This Centre aims to develop carbon-based catalysts for clean energy, CO2 capture, and green chemistry to reduce emissions. The Centre expects to use pioneering data-guided atomic-precision synthesis and multiscale analysis to transform fundamental science of carbon materials. Expected outcomes of this Centre will benefit new technologies for energy, environmental, and green che ....ARC Centre of Excellence for Carbon Science and Innovation. ARC Centre of Excellence for Carbon Science and Innovation. This Centre aims to develop carbon-based catalysts for clean energy, CO2 capture, and green chemistry to reduce emissions. The Centre expects to use pioneering data-guided atomic-precision synthesis and multiscale analysis to transform fundamental science of carbon materials. Expected outcomes of this Centre will benefit new technologies for energy, environmental, and green chemical industries by utilising abundant sunlight, seawater, and waste feedstocks. This should provide significant benefits, through industry collaborations, our new world-leading capacity will train a next generation of game changers to empower emerging carbon industries to solve grand socio-economic challenges, ultimately meeting zero-carbon emissions targets.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
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
Physico-chemical effects on long-time fluid transport for CO2 geostorage. This project aims to develop an efficient multi-scale laboratory-based modelling framework for the analysis of nonequilibrium transport and reaction processes occurring in CO2 storage scenarios. In a significant technological advance two non-destructive analysis techniques, Xray computed tomography and nuclear magnetic resonance, are combined with pore-scale simulations to address uncertainties in dynamic wettability alter ....Physico-chemical effects on long-time fluid transport for CO2 geostorage. This project aims to develop an efficient multi-scale laboratory-based modelling framework for the analysis of nonequilibrium transport and reaction processes occurring in CO2 storage scenarios. In a significant technological advance two non-destructive analysis techniques, Xray computed tomography and nuclear magnetic resonance, are combined with pore-scale simulations to address uncertainties in dynamic wettability alteration occurring during gravity driven convection. Expected outcomes are the in-situ characterisation of solid-surface interactions and predictions of multi-phase fluid flow. The project benefits the Australian resources sector by improving injectivity, storage efficiency and security of supercritical CO2 storage projects.Read moreRead less
Multiscale geomechanical modelling of basin-scale CO2 storage. This project aims to develop innovative geomechanical models that will provide rapid assessments of the potential for reservoir deformation, including induced seismicity, during geological storage of CO2. The main expected outcome is a multiscale modelling approach that will help to identify storage locations at low risk for deformation and CO2 leakage in regions of little existing geomechanical data. The project will elucidate the .... Multiscale geomechanical modelling of basin-scale CO2 storage. This project aims to develop innovative geomechanical models that will provide rapid assessments of the potential for reservoir deformation, including induced seismicity, during geological storage of CO2. The main expected outcome is a multiscale modelling approach that will help to identify storage locations at low risk for deformation and CO2 leakage in regions of little existing geomechanical data. The project will elucidate the technical and commercial viability of CO2 storage in Australia’s Cooper-Eromanga basins and provide broad economic and environmental benefits by reducing the geomechanical uncertainties that provide a barrier to the global need to upscale carbon capture and storage.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
Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelli ....Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.Read moreRead less