Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision m ....Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision making. The project will revolutionise the design of information services where computers deal with humans and location in time-critical or stressful situations, including emergency calls, disaster response and local search queries. The uptake of this design by industry will lead to economic benefits as well as a safer society living in a smarter environment.Read moreRead less
Modelling graph-of-graphs for solving document categorisation problems. Documents in the World Wide Web, such as scientific documents, exhibit a referencing structure as well as being structured objects themselves. This project addresses some inherent limitations of existing modelling techniques in order to improve on the quality of results, and to allow the addressing of some unsolved problems involving documents.
Learning Deep Semantics for Automatic Translation between Human Languages. This project seeks to integrate deep linguistics and deep learning to improve translation quality. The modern world relies increasingly on automatic translation of human languages to deal with billions of documents. Current translation systems struggle with complex texts and often produce misleading or incoherent outputs. Furthermore, they translate sentences independently and ignore their overall document-wide context. T ....Learning Deep Semantics for Automatic Translation between Human Languages. This project seeks to integrate deep linguistics and deep learning to improve translation quality. The modern world relies increasingly on automatic translation of human languages to deal with billions of documents. Current translation systems struggle with complex texts and often produce misleading or incoherent outputs. Furthermore, they translate sentences independently and ignore their overall document-wide context. This project seeks to address these issues by developing a new approach using semantics – the underlying meaning of the text – to drive translation, both as discrete structures and continuous representations learned via deep learning. This may improve translation quality, thereby improving automatic translation for end-users.Read moreRead less
The cellular basis of branching morphogenesis during kidney development. This project aims to study the process of branching morphogenesis which drives the development of the kidney. Previous studies group have demonstrated, in general terms, how branching progresses during gestation. However, little is known about the fundamental cellular events which trigger or characterise this basic developmental process. This project expects to provide deep insights into the cellular basis of tissue and org ....The cellular basis of branching morphogenesis during kidney development. This project aims to study the process of branching morphogenesis which drives the development of the kidney. Previous studies group have demonstrated, in general terms, how branching progresses during gestation. However, little is known about the fundamental cellular events which trigger or characterise this basic developmental process. This project expects to provide deep insights into the cellular basis of tissue and organ development. In studying this process the project should provide critical insights into how cells act, individually and collectively, to build tissues.Read moreRead less
Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, i ....Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, integer models usually assume the data is known with certainty, which is often not the case in the real world. This project will develop new theory and algorithms to enhance the analysis of integer models, including those that incorporating uncertainty, while also enabling the use of parallel computing paradigms. Read moreRead less
“Beacons in the Night” unveiling how galaxies light up dark matter. How dark matter influences the formation and evolution of galaxies is to this day an outstanding question in astrophysics. To answer it, world-class facilities and a unique combination of observations and theory are required. This DP team, a world-class team of observers and theorists, will tackle this question by leveraging on two multi-million dollar projects: the MAGPI galaxy survey and the hydrodynamical simulations suite EA ....“Beacons in the Night” unveiling how galaxies light up dark matter. How dark matter influences the formation and evolution of galaxies is to this day an outstanding question in astrophysics. To answer it, world-class facilities and a unique combination of observations and theory are required. This DP team, a world-class team of observers and theorists, will tackle this question by leveraging on two multi-million dollar projects: the MAGPI galaxy survey and the hydrodynamical simulations suite EAGLE-XL. MAGPI will deliver exquisite kinematics for hundreds of galaxies in the middle ages of the Universe, providing a view to the effect of dark matter on galaxies at this critical time, while EAGLE-XL represents the technological frontier in simulations and provides the best interpretative framework for MAGPI.Read moreRead less
Dynamics of Causal Knowledge. We operate in complex dynamic environments including highly sensitive and safety-critical situations such as medical emergencies, disaster management and air-traffic control systems. Our knowledge of what causes what plays a pivotal role in making correct decisions in such situations. To ensure robustness and sound behaviour of the underlying causal knowledge systems, their designs and implementations must be formally well grounded. This is an important but difficul ....Dynamics of Causal Knowledge. We operate in complex dynamic environments including highly sensitive and safety-critical situations such as medical emergencies, disaster management and air-traffic control systems. Our knowledge of what causes what plays a pivotal role in making correct decisions in such situations. To ensure robustness and sound behaviour of the underlying causal knowledge systems, their designs and implementations must be formally well grounded. This is an important but difficult challenge. This project aims to systematically develop a logic-based framework to adequately capture and reason about evolving causal knowledge. This research is expected to form the basis for smart decision making, and be evaluated on practical applications.Read moreRead less
Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire ....Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire risk and spread, trained and validated on a two-decade satellite fire record. The predictive ability of the model will be tested on the 2019/20 fire season to determine if novel drivers of fire can be identified, and the model itself will be operationalised into a novel short-to-mid term fire risk prediction tool. Read moreRead less
Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge compu ....Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge computing. The expected outcome of the project is a set of solutions to the myriad of services relying on mobile edge computing including e-Health, autonomous vehicles, and Internet of Things. This project will develop key fundamental technologies to improve Australia’s standing in the international research community.
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Risk-aware business process management. Risk-aware business process management will revolutionise the identification and treatment of risks in business processes by integrating the latest technologies for risk management and process management. It will provide organisations with a range of new tools and techniques for designing, deploying and monitoring risk-aware business processes.