Industrial Transformation Research Hubs - Grant ID: IH230100006
Funder
Australian Research Council
Funding Amount
$4,933,330.00
Summary
ARC Research Hub for Engineering Plants to Replace Fossil Carbon . This Hub aims to develop new plant varieties that enable sustainable production of sugars from crop ‘waste’ (plant biomass) as a base for renewable carbon products. Only now possible through emerging technologies, the Hub expects to translate extensive foundational research and world-leading expertise into cost-effective sustainable aviation fuel. Anticipated outcomes include diversified cropping opportunities for agricultural pr ....ARC Research Hub for Engineering Plants to Replace Fossil Carbon . This Hub aims to develop new plant varieties that enable sustainable production of sugars from crop ‘waste’ (plant biomass) as a base for renewable carbon products. Only now possible through emerging technologies, the Hub expects to translate extensive foundational research and world-leading expertise into cost-effective sustainable aviation fuel. Anticipated outcomes include diversified cropping opportunities for agricultural producers and new industries to convert the biomass to high-volume renewable products. The expected benefits include a decarbonised pathway for Australia’s critical flight, freight and defence connections to world and the substantial economic returns and job creation from new manufacturing capacity in Australia.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC210100023
Funder
Australian Research Council
Funding Amount
$4,943,949.00
Summary
ARC Training Centre in Bioplastics and Biocomposites. There is unprecedented growth in demand for bioderived and biodegradable materials. This Training Centre in Bioplastics and Biocomposites will capitalise on Australia’s abundance of the requisite natural bioresources to drive advances in technology for the development of bioplastic and biocomposite products for the new bioeconomy. The aim is to deliver leading edge research with a holistic focus on technical, social, policy and end of life so ....ARC Training Centre in Bioplastics and Biocomposites. There is unprecedented growth in demand for bioderived and biodegradable materials. This Training Centre in Bioplastics and Biocomposites will capitalise on Australia’s abundance of the requisite natural bioresources to drive advances in technology for the development of bioplastic and biocomposite products for the new bioeconomy. The aim is to deliver leading edge research with a holistic focus on technical, social, policy and end of life solutions, training a cohort of industry ready research specialists to underpin Australia’s transition to a globally significant bioplastics and biocomposites industry, while at the same time laying the foundations for accelerated growth in this space.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
Nanostructured solid acid catalysts for sustainable chemical manufacturing. This project aims to develop next-generation solid acid catalysts for energy- and atom-efficient transformations of waste biomass and carbon dioxide to sustainable chemicals and fuels. Catalysis is a transformative technology, key to both life and lifestyle, contributing to 90% of chemical manufacturing processes and >20% of all industrial products, and will be a key enabler for the emerging Australian bioeconomy. The ex ....Nanostructured solid acid catalysts for sustainable chemical manufacturing. This project aims to develop next-generation solid acid catalysts for energy- and atom-efficient transformations of waste biomass and carbon dioxide to sustainable chemicals and fuels. Catalysis is a transformative technology, key to both life and lifestyle, contributing to 90% of chemical manufacturing processes and >20% of all industrial products, and will be a key enabler for the emerging Australian bioeconomy. The expected development of new high performance catalysts for the production of renewable transportation fuels and sustainable chemical feedstocks will underpin commercially viable low carbon technologies using waste resources, and should provide significant benefits to Australian science, industry, and the environment.
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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
Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global com ....Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global competitiveness. Expected outcomes of this project will help to break the communication barriers between the Deaf and hearing population. This should provide significant benefits to Deaf communities through enhanced communication and improved quality-of-life, leading to a fair, more inclusive and resilient Australian society.Read moreRead less
Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored ....Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored to individual characteristics. The success of this project could significantly advance the fundamental research in image analysis. Expected outcomes include new knowledge and algorithms for image analysis, which could benefit fields like biology and archaeology, where labeled images are hard to attain and scarce.Read moreRead less
Integrated Planning for Uncertainty-Centric Pilot Assistance Systems. This project aims to deliver a novel pilot assistance system to improve the viability, speed and safety of Helicopter Emergency Medical Services (HEMS) and Search and Rescue (SAR) missions. It will advance fundamental algorithms for probabilistic planning in partially observable scenarios to form the core technology of a pilot assistance system that accounts the various types of uncertainty faced by pilots in a typical HEMS/S ....Integrated Planning for Uncertainty-Centric Pilot Assistance Systems. This project aims to deliver a novel pilot assistance system to improve the viability, speed and safety of Helicopter Emergency Medical Services (HEMS) and Search and Rescue (SAR) missions. It will advance fundamental algorithms for probabilistic planning in partially observable scenarios to form the core technology of a pilot assistance system that accounts the various types of uncertainty faced by pilots in a typical HEMS/SAR missions. It will exploit recent advances in Partially Observable Markov Decision Processes (POMDPs) to recommend robust, safe, and pilot-aware mission and manoeuvring strategies to make HEMS/SAR operations safer for helicopter crews, and more effective for those in need of the service.Read moreRead less
Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, ....Uncertainty, Risk and Related Concepts in Machine Learning. Machine learning is the science of making sense of data. It does not and cannot remove all risk and uncertainty. This project proposes to study the foundations of how machine learning uses, represents and communicates risk and uncertainty. It aims to do so by finding new theoretical connections between diverse notions that have arisen in allied disciplines. These include risk, uncertainty, scoring rules and loss functions, divergences, statistics and different ways of aggregating information. By building a more complete theoretical map it is expected that new machine learning methods will be developed, but more importantly that machine learning will be able to be better integrated into larger socio-technical systems.Read moreRead less
DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting th ....DeepHoney: Automatic Honey Data Generation for Active Cyber Defence . This project aims to enhance the security of networks and information systems by empowering them with intelligent deception techniques to achieve proactive attack detection and defence. In recent times, the fictitious environment – honeypot designed by human experience becomes popular to attract attackers and capture their interactions. However, rules-based construction of honeypots fails in preserving the privacy, boosting the attractiveness and evolving the system. The project expects to advance deep learning and yield novel DeepHoney technologies with associated publications and open-source software. This should benefit science, society, and the economy by building the next generation of active cyber defence systems. Read moreRead less