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
Knowledge discovery and recommendation of multimedia data in healthcare. The project aims to develop tools to abstract/streamline the ever-growing information-rich multimedia contents into easily discoverable knowledges. Advanced multimedia knowledge graph will be first time developed to accurately exploit hidden knowledge for health industry, and served to generate right information recommendation for healthcare professionals (HCP) at the right time. The proposed technology will improve HCPs' c ....Knowledge discovery and recommendation of multimedia data in healthcare. The project aims to develop tools to abstract/streamline the ever-growing information-rich multimedia contents into easily discoverable knowledges. Advanced multimedia knowledge graph will be first time developed to accurately exploit hidden knowledge for health industry, and served to generate right information recommendation for healthcare professionals (HCP) at the right time. The proposed technology will improve HCPs' communication, keep them up to date, and enhance their speedy reaction to constantly changing situations/diseases, thus reducing poor patient outcomes and unnecessary hospital costs. It will make significant impact to a range of industries, e.g. healthcare, where personalised professional recommendation is demanded.Read moreRead less
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less
Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective. This project brings together experts in the fields of data mining and cognitive neuroscience. This project aims to develop new data analytics tools, algorithms, and models to combine complex multi-source neuroimage brain data and non-imaging data, to explore the interplays among these different data structures and identify novel functional patterns from complex brain graph structures. The research undertaken in this project ....Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective. This project brings together experts in the fields of data mining and cognitive neuroscience. This project aims to develop new data analytics tools, algorithms, and models to combine complex multi-source neuroimage brain data and non-imaging data, to explore the interplays among these different data structures and identify novel functional patterns from complex brain graph structures. The research undertaken in this project expects to provide practical data analysis approaches and establish the theoretical foundations for data mining with multiple sources of brain data.Read moreRead less
Effective, efficient and scalable processing of the graph of graphs. This project aims to develop novel approaches to realise the value of the graph of graphs (GoG), which has been widely used to capture the relations among the structured entities. Several key challenges will be addressed: better models to capture the similarity and cohesiveness of the structured entities, increased efficiency, and greater scalability of the processing and analytics of the GoG. The novel models and algorithms de ....Effective, efficient and scalable processing of the graph of graphs. This project aims to develop novel approaches to realise the value of the graph of graphs (GoG), which has been widely used to capture the relations among the structured entities. Several key challenges will be addressed: better models to capture the similarity and cohesiveness of the structured entities, increased efficiency, and greater scalability of the processing and analytics of the GoG. The novel models and algorithms developed within this project will be incorporated into a prototype for both evaluation and to demonstrate real-world practical value for business, industry, and academia. Success in this project should see significant benefits for many important applications such as health, cyber-security and e-commerce.Read moreRead less
Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business t ....Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business tasks and handle fast-changing scenarios in business. The Self-Evolving EIA is a critical step on the path towards the future generation of EIA. Expected outcomes of this project are to develop adaptive EIA for Small and Medium Enterprise to improve their customer service quality.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
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
Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over ti ....Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over time and captured by different sensors and identify correlations between historic security incidents and current data attacks. This project will significantly help to secure data on cloud for organisations in Australia and benefit fast-growing security sensitive data hosting and applications on cloud.Read moreRead less
Preventing railway suicide: An open-systems perspective. Preventing railway suicide: An open-systems perspective. This project aims to develop an automated suicide risk detection system to reduce the incidence and impact of railway suicide, which has a devastating effect on victims’ families, station staff, train drivers, emergency workers, and bystanders. This project will use open-systems theory to develop two complementary information systems for more effective detection and reporting of suic ....Preventing railway suicide: An open-systems perspective. Preventing railway suicide: An open-systems perspective. This project aims to develop an automated suicide risk detection system to reduce the incidence and impact of railway suicide, which has a devastating effect on victims’ families, station staff, train drivers, emergency workers, and bystanders. This project will use open-systems theory to develop two complementary information systems for more effective detection and reporting of suicide risk; use these systems to investigate how different situational factors interact with different combinations of service interventions to influence suicide risk; and share the findings to reduce railway suicide in Australia and overseas.Read moreRead less