Switching Dynamics Approach for Distributed Global Optimisation . This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in industrial big-data environments where timely decision making is required. It will result in a practical technology for industry optimisation problems such as economic energy dispatch in smart g ....Switching Dynamics Approach for Distributed Global Optimisation . This project aims to create a breakthrough switching dynamics approach and new technology to speed up finding optimal solutions. It will develop a distributed switching dynamics based optimisation scheme for global optimisation problems in industrial big-data environments where timely decision making is required. It will result in a practical technology for industry optimisation problems such as economic energy dispatch in smart grids and optimal charging and discharging tasks in a large network of electric vehicles, helping Australian power industry improve efficiency and security, as well as training the next generation scientists and engineers for Australia in this emerging field.Read moreRead less
Broadening Choice and Increasing Diversity in Public Schools. Currently, most families are limited to the public school in their catchment area, meaning the area in which they can afford to live. This leads to socio-economically and ethnically homogenous schools and entrenches disadvantage, as well as denying students the crucial life lessons that flow from being part of a diverse student body. This project aims to investigate a model for allocating public school places that integrates catchment ....Broadening Choice and Increasing Diversity in Public Schools. Currently, most families are limited to the public school in their catchment area, meaning the area in which they can afford to live. This leads to socio-economically and ethnically homogenous schools and entrenches disadvantage, as well as denying students the crucial life lessons that flow from being part of a diverse student body. This project aims to investigate a model for allocating public school places that integrates catchment areas. The expected outcome would be a system that gives families a wider choice, enabling them to enrol in out-of-area schools, while ensuring that allocations remain fair, equitable and balanced, and also delivering benefits such as achieving a desired level of diversity in student populations within schoolsRead moreRead less
Testing strategy-proofness in matching markets: an experimental study. This project seeks to test and improve matching algorithms by investigating the effect of advice on strategy-proofness. Matching algorithms are used to solve allocation problems in designed markets (eg school or house allocation problems). Many of the algorithms employed are strategy-proof: participants never gain from strategising, that is, from lying about their preferences. Strategy-proofness had been seemingly validated b ....Testing strategy-proofness in matching markets: an experimental study. This project seeks to test and improve matching algorithms by investigating the effect of advice on strategy-proofness. Matching algorithms are used to solve allocation problems in designed markets (eg school or house allocation problems). Many of the algorithms employed are strategy-proof: participants never gain from strategising, that is, from lying about their preferences. Strategy-proofness had been seemingly validated by experimental research, but new evidence suggests that participants could be prone to follow wrong advice and therefore lie. In order to improve the performance of designed markets, the project proposes to further test strategy-proofness by investigating how advice can affect truth-telling in strategy-proof algorithms and whether learning can counteract or complement the effect of advice.Read moreRead less
Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the ext ....Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the extent of such biases, and develop models that are both more socially equitable, as well as less prone to expose private data in the learned representations. In doing so, it will make NLP more accessible to new populations of users, and remove socio-technological barriers to NLP uptake.Read moreRead less
Advanced Materials from Automated Synthesis of Sequence-Defined Polymers. The project aims to develop industrially scalable and environmentally friendly methods for synthesis of sequence-defined multiblock copolymers (polymer chains containing segments of different polymer types) using automated synthesis methods. The materials to be explored will be largely based on renewable biomass-derived monomeric building blocks. Such polymers are able to undergo microphase separation into spatially period ....Advanced Materials from Automated Synthesis of Sequence-Defined Polymers. The project aims to develop industrially scalable and environmentally friendly methods for synthesis of sequence-defined multiblock copolymers (polymer chains containing segments of different polymer types) using automated synthesis methods. The materials to be explored will be largely based on renewable biomass-derived monomeric building blocks. Such polymers are able to undergo microphase separation into spatially periodic compositional patterns, thereby providing access to a vast range of nano-engineered materials. This would enable design and synthesis of new advanced materials, making use of renewable resources and supporting the circular economy, with diverse potential applications ranging from nanomedicine to materials science.Read moreRead less
Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applicatio ....Leveraging 3D computer vision for camera-based precise geo-localisation. This project aims to develop advanced 3D computer vision and image processing technology that can turn regular cameras into high-precision location-sensing devices. Spatial Location is a fundamental type of information of our physical world. Determining the precise location of people, vehicle, and mobile devices is essential for many critical applications. Outcomes of the project will enable a wide range of novel applications of significant social, environmental and economic value, such as Location-Aware Service, Environment Monitoring, Augmented Reality, Autonomous Vehicle, and Rapid Emergency Response. The project will enhance Australia's international competitive advantage in forefront of ICT research and technology innovation.Read moreRead less
Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less
Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approa ....Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.Read moreRead less
Decentralised assets trading, centralised clearing and systemic risk. This project aims to study the effect of regulating over-the-counter (OTC) financial markets on economic performance. The lack of transparency of OTC financial markets may have exacerbated the severity of the 2007-09 financial crisis. In response, regulators around the world decided to mandate centralised clearing of derivatives traded OTC, believing this would reduce system-wide risk. This project will study the regulatory ch ....Decentralised assets trading, centralised clearing and systemic risk. This project aims to study the effect of regulating over-the-counter (OTC) financial markets on economic performance. The lack of transparency of OTC financial markets may have exacerbated the severity of the 2007-09 financial crisis. In response, regulators around the world decided to mandate centralised clearing of derivatives traded OTC, believing this would reduce system-wide risk. This project will study the regulatory change’s effects on market participation, volumes of trade and prices, and the behavioural effect of shifting risk from market participants to clearinghouses. It expects to suggest remedial policies clearinghouses could implement to control market participants’ risk appetite. These can help enhance future productivity and reduce unemployment in Australia.Read moreRead less
Deep analytics of non-occurring but important behaviours. This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. Thi ....Deep analytics of non-occurring but important behaviours. This project aims to build a systematic theory for the deep analytics of complex and important occurring and non-occurring behaviours. Behaviours that should occur but do not take place, called non-occurring behaviours (NOB), are widely evident but easily overlooked, such as missed important medical treatments. While often occurring behaviours are focused, such NOB may be associated with significant effects such as a threat to health. This project expects to fill the knowledge gaps in representing, analysing and evaluating NOB complexities and impact, with significant benefits for the evidence-based detection, prediction and risk management of covert NOB applications and their important effects.Read moreRead less