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
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
Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatm ....Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatments through the linking of relevant biochemical information. By delivering new methods that improve the compilation of knowledge about chemicals and drugs from textual information resources, the project hopes to enable faster drug discovery.Read moreRead less
Deep mining neurological abnormalities from brain signal data. This project aims to develop a reliable, robust and real-time analysis system for automatic and accurate detection of neurological abnormalities, and the prediction of impending neurological problems from brain signal data. The project expects to design novel algorithms for brain signal processing, data compression, and detection and prediction of neurological abnormalities from massive brain signal data. The project will lead to sig ....Deep mining neurological abnormalities from brain signal data. This project aims to develop a reliable, robust and real-time analysis system for automatic and accurate detection of neurological abnormalities, and the prediction of impending neurological problems from brain signal data. The project expects to design novel algorithms for brain signal processing, data compression, and detection and prediction of neurological abnormalities from massive brain signal data. The project will lead to significant improvement of existing methods in health monitoring applications in Australia and worldwide and hence will save lives, money and resources.Read moreRead less
AI for Legal Problem Diagnosis in the Diverse Language of Australians. The number of Australians with unmet legal needs is estimated to be over four million people per year and growing, and free legal assistance is severely under-resourced. A bottleneck for free legal assistance providers is the determination of what (if any) specific legal needs the individual has, to which end this project proposes to develop AI models to semi-automate the process, with particular focus on fairness across user ....AI for Legal Problem Diagnosis in the Diverse Language of Australians. The number of Australians with unmet legal needs is estimated to be over four million people per year and growing, and free legal assistance is severely under-resourced. A bottleneck for free legal assistance providers is the determination of what (if any) specific legal needs the individual has, to which end this project proposes to develop AI models to semi-automate the process, with particular focus on fairness across users of all backgrounds, generalisation from small amounts of curated data, and dynamic interaction with the help-seeker. The project will help deliver legal assistance to some of the most vulnerable members of Australian society, and reinforce Australia's position as a world leader in AI for Law.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
Privacy preservation for personalised smart devices. The goal of this project is to build a privacy preservation framework for personalised smart devices with both immediate and long-term applications in a range of industries. The novel theoretical contributions include a privacy-preservation mechanism that guards against attacks by intelligent tools, a model and metrics that distinguish between object detection and object recognition, and allowing users to specify their desired level of privacy ....Privacy preservation for personalised smart devices. The goal of this project is to build a privacy preservation framework for personalised smart devices with both immediate and long-term applications in a range of industries. The novel theoretical contributions include a privacy-preservation mechanism that guards against attacks by intelligent tools, a model and metrics that distinguish between object detection and object recognition, and allowing users to specify their desired level of privacy guarantee. Practically, these solutions have clear economic and public-safety benefits. The solutions will accelerate AI device development, advance smart technologies based on individual behaviours, and guarantee personal data privacy against both human attackers and adversarial algorithms. Read moreRead less
Field Data based Predictive Maintenance and Enhanced Track Design Procedure. Providing improved railroad design and maintenance solutions with accurate and timely assessment of track performance is vital to reduce the disruption of services, excessive maintenance costs and degradation over time. This project aims to develop a predictive maintenance model based on extensive wayside measurements to monitor and predict the nature of track instability. This will also be supplemented by mathematical ....Field Data based Predictive Maintenance and Enhanced Track Design Procedure. Providing improved railroad design and maintenance solutions with accurate and timely assessment of track performance is vital to reduce the disruption of services, excessive maintenance costs and degradation over time. This project aims to develop a predictive maintenance model based on extensive wayside measurements to monitor and predict the nature of track instability. This will also be supplemented by mathematical modelling to corroborate large-scale laboratory observations with past and real-time field monitoring records. This project will deliver tangible strategies and tools to increase track longevity and assist decision-makers in planning and prioritising corrective maintenance to ensure improved safety and passenger comfort.Read moreRead less
Dynamic Deep Learning for Electricity Demand Forecasting. This project aims at developing a deep learning technology for high resolution electricity demand forecasting and residential demand response modelling. Electricity consumption data are dynamic and highly uncertain. The deep learning technology expects to provide accurate demand forecasting, and thus enabling optimal use of existing
grid assets and guiding future investments. The expected outcome can support data-driven decision-making in ....Dynamic Deep Learning for Electricity Demand Forecasting. This project aims at developing a deep learning technology for high resolution electricity demand forecasting and residential demand response modelling. Electricity consumption data are dynamic and highly uncertain. The deep learning technology expects to provide accurate demand forecasting, and thus enabling optimal use of existing
grid assets and guiding future investments. The expected outcome can support data-driven decision-making in Australia's electricity distribution network planning and operation by considering future challenges such as integrating battery storage and electric vehicles into the grid, and thus providing reliable energy. The project expects to train next generation expert workforce for Australia's future power grid.Read moreRead less
Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges ....Towards full lifecycle privacy protection on cloud. Privacy protection in user data on cloud is now at risk throughout all stages of user information lifecycle facing significant challenges such as stage adaptive protection, across-system protection, privacy invasion tracing and prediction. Current approaches mainly focus on a specific case at certain stage, hence cannot address those challenges properly by considering all stages. This project aims to systematically investigate those challenges and expects to establish innovative research and solutions for enabling full lifecycle privacy protection on cloud. The project outcomes will help to safeguard Australian community in fast-growing online cyber world, and benefit to fast-growing privacy sensitive data hosting and applications on cloud.Read moreRead less