Discovery Early Career Researcher Award - Grant ID: DE130100292
Funder
Australian Research Council
Funding Amount
$285,000.00
Summary
Towards a stronger proof system for combinatorial optimisation. Combinatorial optimisation problems such as staff rostering, vehicle routing or resource allocation are central to the efficiency of many businesses and industries. This project will improve optimisation technology by using the low-level structure of the problems to find better solutions. This will save time, money and reduce environmental impact.
Accurate analysis of combinatorial problems: from the particular to the general. Combinatorial problems pervade all aspects of our social, environmental and economic life, but finding good solutions to these problems can take too much computer time. This project will develop new analysis tools that are effective at reducing this time, thus allowing for better solutions to be found.
Detecting Supervisory Control and Data Access (SCADA) malicious programs to protect Australian critical infrastructure. The security of SCADA systems has enormous impact to our national security and economy because they control and monitor critical infrastructure, like power, gas and water facilities and nuclear power plants, etc. This project aims to investigate the security issues and provide innovative technological solutions to detect and prevent such problems.
Making the Pilbara blend: agile mine scheduling through contingent planning. Mine scheduling is a challenging problem for Rio Tinto which annually mines more than 200 Million tonnes of iron ore. This project will develop agile scheduling techniques of great economic importance to Australia. Carefully planned scheduling reduces infrastructure and minimises environmental impacts, maximising regeneration after mining.
Designing Distributed Intrusion Detection Systems for Critical Industrial Infrastructures. SCADA systems are computerized systems that control and monitor industrial and critical infrastructures, such as power grid, gas and water facilities and nuclear power plants. Many cyber-attacks on SCADA systems make such systems vulnerable. Also there is an increasing risk that SCADA vulnerabilities could be exploited by terrorist organizations. The security of SCADA systems of critical infrastructures ha ....Designing Distributed Intrusion Detection Systems for Critical Industrial Infrastructures. SCADA systems are computerized systems that control and monitor industrial and critical infrastructures, such as power grid, gas and water facilities and nuclear power plants. Many cyber-attacks on SCADA systems make such systems vulnerable. Also there is an increasing risk that SCADA vulnerabilities could be exploited by terrorist organizations. The security of SCADA systems of critical infrastructures has enormous and direct impact to our national security, economy and social life because of potential disasters that could happen from natural causes as well as malicious attacks. This project aims to investigate the relevant issues and provide efficient and reliable technological solutions to detect and prevent such problems.Read moreRead less
Machine Learning for Fracture Risk Assessment from Simple Radiography. This project aims to develop a novel, reliable, low-cost system to detect poor bone health and assess fracture risk to help to prevent and manage osteoporosis-related fractures. Currently, osteoporosis-related fractures cost our health system millions of dollars annually and costs are increasing with our ageing population. Early detection of poor bone health will improve the effectiveness of preventive measures and ease this ....Machine Learning for Fracture Risk Assessment from Simple Radiography. This project aims to develop a novel, reliable, low-cost system to detect poor bone health and assess fracture risk to help to prevent and manage osteoporosis-related fractures. Currently, osteoporosis-related fractures cost our health system millions of dollars annually and costs are increasing with our ageing population. Early detection of poor bone health will improve the effectiveness of preventive measures and ease this burden. Current methods include unreliable, crude clinical and visual guides that suggest osteoporosis screening. The project plans to develop a novel system by applying machine learning algorithms to radiology data which is commonly captured for diagnosing other conditions.Read moreRead less
Explainable Artificial Creativity. This project aims to develop explainable models for creative AI systems which enable more productive and satisfying interactions between them and their human co-creators. This will boost both human and machine creativity through sustained, ongoing exchanges, leading to high-quality creative outcomes via automated ideation and more advanced human-machine collaborations. The proposed techniques will be validated with creative professionals, ensuring practical ind ....Explainable Artificial Creativity. This project aims to develop explainable models for creative AI systems which enable more productive and satisfying interactions between them and their human co-creators. This will boost both human and machine creativity through sustained, ongoing exchanges, leading to high-quality creative outcomes via automated ideation and more advanced human-machine collaborations. The proposed techniques will be validated with creative professionals, ensuring practical industry relevance. We expect the outcomes to include new methods that automatically generate persuasive explanations, new forms of communication including dialogues between creative AI systems and users, and new understanding of general aspects of explainability for creative AI systems.Read moreRead less
Learned Academies Special Projects - Grant ID: LA170100025
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social med ....Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social media archives or financial records in ways that will shed new light on many complex research questions. This project will map existing capability and infrastructure within and across disciplines, identify common and discipline-specific practices, challenges and opportunities, and assess technology, infrastructure, training and collaboration priorities for Australia.
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Visualisation of large, complex networks through small, beautiful diagrams. Data is increasingly organised as networks. Visualisation is a key way to understand networks. This project plans to develop a new paradigm for this task. Using modern generic constrained optimisation techniques it will produce layouts for small graphs whose quality is similar to that produced by hand, something that is not possible with current approaches. These algorithms will then be used to visualise large graphs. In ....Visualisation of large, complex networks through small, beautiful diagrams. Data is increasingly organised as networks. Visualisation is a key way to understand networks. This project plans to develop a new paradigm for this task. Using modern generic constrained optimisation techniques it will produce layouts for small graphs whose quality is similar to that produced by hand, something that is not possible with current approaches. These algorithms will then be used to visualise large graphs. Instead of simply trying to visualise every node and link in the graph. The project will develop techniques to extract useful subsets or abstractions that are as small possible, yet sufficient to answer targeted queries. The techniques for producing small high-quality diagrams will then be applicable to presenting these focused visualisations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101351
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Playing and Solving General Games. Constructing rational agents for general dynamic decision problems is a long-standing open Artificial Intelligence challenge. An important milestone is to construct artificial agents that can learn and play new games well (universal playing agents). Specialised artificial intelligence systems are increasingly successful in domains such as Chess, Go, and Poker. The project aims to develop the theoretical and practical foundations of universal playing agents thro ....Playing and Solving General Games. Constructing rational agents for general dynamic decision problems is a long-standing open Artificial Intelligence challenge. An important milestone is to construct artificial agents that can learn and play new games well (universal playing agents). Specialised artificial intelligence systems are increasingly successful in domains such as Chess, Go, and Poker. The project aims to develop the theoretical and practical foundations of universal playing agents through a mathematical study of algorithms and heuristics for specific games. This project aims to significantly bridge the gap from efficient specialised players to high performance rational agents.Read moreRead less