Engineering Artificial Intelligence: A Spatial Representation and Reasoning Perspective. Spatial information is important in areas of national interest such as mining and exploration, environmental monitoring and planning, emergency response, and defence. Mission control centres, for instance, receive different forms of spatial data from satellites, radar, or people on the ground. They have to process the input data and make intelligent decisions in a very limited time. Intelligent systems that ....Engineering Artificial Intelligence: A Spatial Representation and Reasoning Perspective. Spatial information is important in areas of national interest such as mining and exploration, environmental monitoring and planning, emergency response, and defence. Mission control centres, for instance, receive different forms of spatial data from satellites, radar, or people on the ground. They have to process the input data and make intelligent decisions in a very limited time. Intelligent systems that are able to assist with processing different forms of spatial data efficiently and that offer reliable decision support are essential for improving the quality and reliability of such applications. This research enables future intelligent systems with these capabilities. This will directly benefit applications in areas of national interest.Read moreRead less
Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expecte ....Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expected outcomes are algorithms for public and private sector data curators to dial up or down their data access arrangements based on privacy risks and fidelity demands linked with different data types and uses. This project intends to enable Australians to securely benefit from valuable data in decision making.Read moreRead less
Ambient spatial intelligence: Spatial analysis and event detection in environmental geosensor networks. This project will design and test innovative new decentralised algorithms for responding to spatiotemporal queries in environmental monitoring networks. The research is essential for constructing larger, denser, and more reliable networks, helping to embed spatial intelligence within the environment itself (ambient spatial intelligence). The project builds on Australia's existing research exce ....Ambient spatial intelligence: Spatial analysis and event detection in environmental geosensor networks. This project will design and test innovative new decentralised algorithms for responding to spatiotemporal queries in environmental monitoring networks. The research is essential for constructing larger, denser, and more reliable networks, helping to embed spatial intelligence within the environment itself (ambient spatial intelligence). The project builds on Australia's existing research excellence in geographic information science. By making smarter use of spatial information, the project will further strengthen Australia's world-leading spatial information industry, and support sustainable and economic environmental management through important applications like conservation contracts and carbon sequestration monitoring.Read moreRead less
A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location da ....A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location data and enhanced international collaborations. The project will support and enhance a wide range of indoor applications such as emergency services, assisted healthcare systems, indoor asset tracking, event planning, indoor venue management, and consumer experience.Read moreRead less
Real-time Event Detection, Prediction, and Visualization for Emergency Response. This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and sc ....Real-time Event Detection, Prediction, and Visualization for Emergency Response. This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and scalability factors to handle vast collections of heterogeneous data. An event surveillance system prototype will be developed to incorporate the findings of the research with tools to visualise and describe events.Read moreRead less
Taming Large-Volume Dynamic Graphs in the Cloud. This project aims to develop efficient and scalable algorithms to process large-volume dynamic graphs in the cloud. The project expects to address key challenges and lay theoretical foundations in large-volume dynamic graph processing, which plays an important role in developing general-purpose, real-time structural search engines. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big graphs that ....Taming Large-Volume Dynamic Graphs in the Cloud. This project aims to develop efficient and scalable algorithms to process large-volume dynamic graphs in the cloud. The project expects to address key challenges and lay theoretical foundations in large-volume dynamic graph processing, which plays an important role in developing general-purpose, real-time structural search engines. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big graphs that evolve rapidly over time. These enable users to monitor and analyse structural information in large dynamic networks in real time. The project expects to open up a new research direction for graph processing to enrich frontier technologies and benefit many key applications in Australia.Read moreRead less
Efficient and Scalable Processing of Dynamic Heterogeneous Graphs . This project aims to develop efficient and scalable algorithms to process large-scale dynamic heterogeneous graphs where graph nodes and edges are of multiple types and the graph structure updates dynamically. Key challenges are expected to be addressed including complex structure, high speed, and large volume of dynamic heterogeneous graphs. The anticipated outcomes include novel computing paradigms, algorithms, indexing, incre ....Efficient and Scalable Processing of Dynamic Heterogeneous Graphs . This project aims to develop efficient and scalable algorithms to process large-scale dynamic heterogeneous graphs where graph nodes and edges are of multiple types and the graph structure updates dynamically. Key challenges are expected to be addressed including complex structure, high speed, and large volume of dynamic heterogeneous graphs. The anticipated outcomes include novel computing paradigms, algorithms, indexing, incremental computation, distributed algorithms as well as a system prototype to demonstrate the practical value. Success of this project will open up a new research direction to enrich frontier technologies and benefit many key applications in Australia including cybersecurity, e-commerce, health and social networks.Read moreRead less
Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected ....Deep Interaction Learning in Unlabelled Big Data and Complex Systems. This project aims to effectively model intricate interactions deeply embedded in unlabelled big data and complex systems, which are often hierarchical, heterogeneous, contextual, dynamic or even contrastive. Learning such interactions is the keystone of robust data science and for realizing the value of big data but it poses significant challenges and knowledge gaps to existing data analytics and learning systems. The expected outcomes include new-generation theories and methods for the unsupervised learning of complex interactions in real-life big data, which are anticipated to enable the intrinsic processing of big data complexities and substantially enhance Australia’s leadership in frontier data science research and applications. Read moreRead less
Realising the value of mobile videos with context awareness. Innovative approaches to analysing online video content and context will lead to new ways of interacting with video in the mobile world. This project will aim to develop real-time mobile systems for enabling rich and highly dynamic digital video experiences through context-aware indexing, retrieval and consumption of mobile videos.
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