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
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
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
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
The molecular basis for efficacy at G protein coupled receptors. This project aims to investigate the molecular steps underlying the relationship between sensing by signal-transmitting proteins on the cell surface called G protein-coupled receptors and cellular response. The project aims to build on studies that have sought to understand the primary, molecular basis for this cellular volume control. This project seeks to use these novel approaches to fill this knowledge gap, providing a deeper u ....The molecular basis for efficacy at G protein coupled receptors. This project aims to investigate the molecular steps underlying the relationship between sensing by signal-transmitting proteins on the cell surface called G protein-coupled receptors and cellular response. The project aims to build on studies that have sought to understand the primary, molecular basis for this cellular volume control. This project seeks to use these novel approaches to fill this knowledge gap, providing a deeper understanding of how physiology and medicines work. The project expects to expand fundamental understanding of signal transmission at this receptor class. This project will deliver benefits including expanded basic knowledge and a contribution to future improvements in drug development.Read moreRead less
Metabolite regulation of mitochondrial fission. This project aims to understand how the function and health of mitochondria – the energy producing structures in cells - are controlled by fat molecules. The project expects to integrate cutting edge techniques and instrumentation to generate new knowledge of how fat molecules interact with, and influence, enzymes that control how cells maintain their mitochondria in response to nutrient state. An anticipated goal is to define a fingerprint for enz ....Metabolite regulation of mitochondrial fission. This project aims to understand how the function and health of mitochondria – the energy producing structures in cells - are controlled by fat molecules. The project expects to integrate cutting edge techniques and instrumentation to generate new knowledge of how fat molecules interact with, and influence, enzymes that control how cells maintain their mitochondria in response to nutrient state. An anticipated goal is to define a fingerprint for enzymes regulated by fat molecules that will be of great interest to researchers across many branches of life sciences. Expected outcomes and benefits will be deeper understanding of fat molecules as nutrient signalling metabolites, and how they influence cell metabolism, growth and development.Read moreRead less
Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge. This project aims to develop an automatic graph learning system for complex graph data analysis. Machine learning for graph data commonly requires significant human knowledge from both domain professionals as well as algorithm experts, rendering existing systems ineffective and unexplainable. This project expects to design novel graph learning techniques which automatically infer graph relations, learn graph models, adapts ....Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge. This project aims to develop an automatic graph learning system for complex graph data analysis. Machine learning for graph data commonly requires significant human knowledge from both domain professionals as well as algorithm experts, rendering existing systems ineffective and unexplainable. This project expects to design novel graph learning techniques which automatically infer graph relations, learn graph models, adapts existing knowledge to new domains, and provide explanations to the graph learning system. The research results should provide benefit to governments and businesses in many critical applications, such as bioassay activity prediction, credit assessment, and drug discovery and vaccine development in response to the pandemic.Read moreRead less
Uncovering New Mechanisms of Metabolite-Sensing and Signaling. This project aims to understand how cells sense changes in metabolic activity, to ensure energy demands are matched with nutrient supply. Our proposal will fill critical gaps in our understanding of the molecular mechanisms underlying metabolic sensing. This will generate new knowledge with far reaching potential for Australian industries that rely on the propagation and utilization of living organisms, including agriculture, biotech ....Uncovering New Mechanisms of Metabolite-Sensing and Signaling. This project aims to understand how cells sense changes in metabolic activity, to ensure energy demands are matched with nutrient supply. Our proposal will fill critical gaps in our understanding of the molecular mechanisms underlying metabolic sensing. This will generate new knowledge with far reaching potential for Australian industries that rely on the propagation and utilization of living organisms, including agriculture, biotechnology and brewing, as well as knowledge relevant to sporting performance and the metabolic dimensions of ageing. This project will support advanced training of early career researchers and PhD students, which will expand Australian research capabilities and contribute to a producing a highly skilled workforce.Read moreRead less
Managing the risks posed by Artificial General Intelligence. It is widely acknowledged that a failure to implement appropriate controls for the next generation of Artificial Intelligence, Artificial General Intelligence (AGI), could have catastrophic consequences, including in the worst case - the extinction of the human race. This research aims to forecast the risks associated with AGI systems and identify the controls required to ensure that risks and existential threats are minimised. The exp ....Managing the risks posed by Artificial General Intelligence. It is widely acknowledged that a failure to implement appropriate controls for the next generation of Artificial Intelligence, Artificial General Intelligence (AGI), could have catastrophic consequences, including in the worst case - the extinction of the human race. This research aims to forecast the risks associated with AGI systems and identify the controls required to ensure that risks and existential threats are minimised. The expected outputs will provide designers, organisations, regulators and governments with a framework to support the design, implementation, and management of safe and efficient AGI systems. This will ensure that the potential far-reaching benefits of AGI are realised without undue threat to society.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC160100036
Funder
Australian Research Council
Funding Amount
$4,881,754.00
Summary
ARC Training Centre in Alloy Innovation for Mining Efficiency. ARC Training Centre in Alloy Innovation for Mining Efficiency. This centre aims to make Australian manufacturers dominant in the multi-billion dollar mining equipment sector by training innovators to design the world’s best highly customized long-life, wear resistant components. It intends to rapidly develop customized alloys that excel in severe mining conditions, using three-dimensional printing, novel characterisation and its netw ....ARC Training Centre in Alloy Innovation for Mining Efficiency. ARC Training Centre in Alloy Innovation for Mining Efficiency. This centre aims to make Australian manufacturers dominant in the multi-billion dollar mining equipment sector by training innovators to design the world’s best highly customized long-life, wear resistant components. It intends to rapidly develop customized alloys that excel in severe mining conditions, using three-dimensional printing, novel characterisation and its networked training environment. It expects these innovations will enable much needed efficiencies after the end of the mining super-cycle. Anticipated outcomes are the design of products with superior alloy design and material selection; jobs growth and security in the mining component production sector; and increased mining efficiency and cost reduction.Read moreRead less