Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.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
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.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
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE240100010
Funder
Australian Research Council
Funding Amount
$928,291.00
Summary
Single-molecule Manipulation and Interaction Facility (SMIF). This LIEF project aims to establish Australia's first Single-molecule Manipulation and Interaction Facility (SMIF), providing multidisciplinary researchers with a platform to explore cellular processes and reveal molecular mechanisms at the nanoscale. The SMIF facility incorporates cutting-edge technologies for bio-manipulation, real-time visualisation, and characterisation of single-molecule interactions, overcoming the technical com ....Single-molecule Manipulation and Interaction Facility (SMIF). This LIEF project aims to establish Australia's first Single-molecule Manipulation and Interaction Facility (SMIF), providing multidisciplinary researchers with a platform to explore cellular processes and reveal molecular mechanisms at the nanoscale. The SMIF facility incorporates cutting-edge technologies for bio-manipulation, real-time visualisation, and characterisation of single-molecule interactions, overcoming the technical complexity of traditional tools requiring highly specialised personnel. By offering accessible, easy-to-use advanced systems, this project will significantly boost scientific discovery across physics, chemistry, and biology, fostering collaboration and innovation to better understand life at the molecular level.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
Industrial Transformation Training Centres - Grant ID: IC170100035
Funder
Australian Research Council
Funding Amount
$4,743,710.00
Summary
ARC Training Centre for Innovation in Biomedical Imaging Technology. The ARC Training Centre for Innovation in Biomedical Imaging Technology expects to train 20 industry-ready innovation scientists who will undertake industry-driven research in the development and application of novel diagnostics, therapeutics and theranostics. They will inform changes in regulatory policy that support industry growth. The Centre will build multidisciplinary links between researchers and within industry to devel ....ARC Training Centre for Innovation in Biomedical Imaging Technology. The ARC Training Centre for Innovation in Biomedical Imaging Technology expects to train 20 industry-ready innovation scientists who will undertake industry-driven research in the development and application of novel diagnostics, therapeutics and theranostics. They will inform changes in regulatory policy that support industry growth. The Centre will build multidisciplinary links between researchers and within industry to develop ‘smart’ probes and ‘smart’ scanning, harnessing the digital revolution for better, cost effective diagnostic imaging and improved health outcomes.Read moreRead less