Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Algal direct-air CO2 capture through interfacial enzyme immobilisation . Capturing CO2 directly from the atmosphere is challenging due to inherently slow mass transfer kinetics. This project aims to overcome this using an enzyme that can rapidly solubilise CO2 from air into water, to produce algae. By engineering the enzyme immobilisation at the air-water interface, this project will activate and protect the enzymes, increasing their lifespan and reducing costs. By understanding mass transfer an ....Algal direct-air CO2 capture through interfacial enzyme immobilisation . Capturing CO2 directly from the atmosphere is challenging due to inherently slow mass transfer kinetics. This project aims to overcome this using an enzyme that can rapidly solubilise CO2 from air into water, to produce algae. By engineering the enzyme immobilisation at the air-water interface, this project will activate and protect the enzymes, increasing their lifespan and reducing costs. By understanding mass transfer and enzyme activity in the interfacial immobilisation media, floating enzyme rafts can be developed for deployment over expansive areas, facilitating large-scale conversion of atmospheric CO2 into algae-derived fuels, feeds and chemicals.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101297
Funder
Australian Research Council
Funding Amount
$429,000.00
Summary
A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the e ....A novel, dictionary-free, multi-contrast MRI method for microscopic imaging. This project aims to develop a novel quantitative imaging technique for comprehensive in vitro and in vivo tissue characterisation on the microscopic scale. The technology innovated in the project could revolutionise microscopic imaging techniques by breaking through the sub-millimetre image resolution bottleneck of current magnetic resonance imaging (MRI) methods. This project expects to generate new knowledge in the emerging field of biological imaging and to deliver an integrated imaging platform for mapping various tissue microscopic components at the cellular level. Successful outcomes have the potential for commercialisation and will accelerate a range of fundamental science and engineering studies requiring imaging techniques.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
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
New biocatalysts for selective chemical oxidations under extreme conditions. This project will identify and design new enzyme biocatalysts which function under extreme conditions such as elevated temperature and high concentrations of peroxides. These enzymes will be sourced from microorganisms which are located in extreme biological environments e.g. hot springs (the so-called extremophiles). The expected outcome of this project are the identification of robust enzymes which can catalyse select ....New biocatalysts for selective chemical oxidations under extreme conditions. This project will identify and design new enzyme biocatalysts which function under extreme conditions such as elevated temperature and high concentrations of peroxides. These enzymes will be sourced from microorganisms which are located in extreme biological environments e.g. hot springs (the so-called extremophiles). The expected outcome of this project are the identification of robust enzymes which can catalyse selective oxidation reactions in complex organic molecules, such as steroids. The new biocatalysts developed in this project will have significant benefit in the development of new routes to access bespoke molecules of value in fine chemical synthesis and drug development.
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Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
Nano-reactors: Protein cages as reusable scaffolds for designer enzymes. This project aims to develop robust protein cages derived from the coats of viruses to contain heat-stable P450 enzymes, for use as specialised protein bio-catalysts in chemical industries. A valuable chemical precursor of renewable bio-plastics will be produced from seed oils by enzymes, reducing the use of fossil fuels. This synthetic biology approach combines biotechnology, nanotechnology and protein engineering to estab ....Nano-reactors: Protein cages as reusable scaffolds for designer enzymes. This project aims to develop robust protein cages derived from the coats of viruses to contain heat-stable P450 enzymes, for use as specialised protein bio-catalysts in chemical industries. A valuable chemical precursor of renewable bio-plastics will be produced from seed oils by enzymes, reducing the use of fossil fuels. This synthetic biology approach combines biotechnology, nanotechnology and protein engineering to establish a plant-based platform biotechnology for using enzymes as catalysts to make high-value molecules. The project aims to show how to engineer clean, sustainable chemistry in designer nano-environments. This should make synthetic processes more sustainable and enhance advanced chemical manufacturing in Australia.Read moreRead less
ARC Centre of Excellence in Quantum Biotechnology. ARC Centre of Excellence in Quantum Biotechnology. The ARC Centre of Excellence in Quantum Biotechnology aims to develop paradigm-shifting quantum technologies to observe biological processes and transform our understanding of life. It seeks to create technologies that go far beyond what is possible today, from portable brain imagers to super-fast single protein sensors, and to use them to unravel key problems including how enzymes catalyse reac ....ARC Centre of Excellence in Quantum Biotechnology. ARC Centre of Excellence in Quantum Biotechnology. The ARC Centre of Excellence in Quantum Biotechnology aims to develop paradigm-shifting quantum technologies to observe biological processes and transform our understanding of life. It seeks to create technologies that go far beyond what is possible today, from portable brain imagers to super-fast single protein sensors, and to use them to unravel key problems including how enzymes catalyse reactions and how higher brain function emerges from networks of neurons. By building a diverse, multidisciplinary, and industry-engaged ecosystem, the Centre means to develop our future leaders at the interface of quantum science and biology and drive Australian innovation across manufacturing, energy, agriculture, health, and national security.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less