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
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
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
Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-vi ....Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-visual services that are of great interest to international standards bodies and industry, while facilitating free interaction and augmented reality. This project will provide significant benefits to broadcast, entertainment, surveillance and health industries and position Australia as a world leader in this field.Read moreRead less
A Midas touch for electrophiles in new reaction development. This project aims to address the lack of knowledge about how high-value organic molecules are formed in gold-catalysed reactions by advancing a novel mode of catalysis. This project expects to generate new knowledge about these gold-catalysed reactions using an innovative, interdisciplinary approach incorporating computational and synthetic techniques. Expected outcomes of this project include the optimisation and development of import ....A Midas touch for electrophiles in new reaction development. This project aims to address the lack of knowledge about how high-value organic molecules are formed in gold-catalysed reactions by advancing a novel mode of catalysis. This project expects to generate new knowledge about these gold-catalysed reactions using an innovative, interdisciplinary approach incorporating computational and synthetic techniques. Expected outcomes of this project include the optimisation and development of important organic reactions and enhancing collaboration nationally and internationally between computational and synthetic chemists. This should provide significant benefits in the form of improved chemical reactions for chemists to prepare new pharmaceuticals, agrochemicals and materials.Read moreRead less
Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through th ....An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through the utilisation of pioneering natural language processing components and novel custom-made machine-readable knowledge bases. The outcome of this research will broaden access to high-quality models by non-expert workforce and alleviate the shortage of expert mathematicians, bringing significant social and economic benefits.Read moreRead less
Wicked defaults: how to overcome the dark side of choice architecture. This project aims to investigate how defaults and product complexity might be used to exploit consumers in environments like private insurance where consumers are prone to making systematic errors. Defaults are used to nudge individuals into socially beneficial actions such as increasing their retirement savings and joining organ donor lists. However, in the hands of firms, defaults can also be used to exploit consumers by en ....Wicked defaults: how to overcome the dark side of choice architecture. This project aims to investigate how defaults and product complexity might be used to exploit consumers in environments like private insurance where consumers are prone to making systematic errors. Defaults are used to nudge individuals into socially beneficial actions such as increasing their retirement savings and joining organ donor lists. However, in the hands of firms, defaults can also be used to exploit consumers by encouraging choices that help the firm but disadvantage consumers. The project intends to study experimentally whether exploitation can be reduced via competition and reputation building systems based on consumer feedback.Read moreRead less
Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored ....Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored to individual characteristics. The success of this project could significantly advance the fundamental research in image analysis. Expected outcomes include new knowledge and algorithms for image analysis, which could benefit fields like biology and archaeology, where labeled images are hard to attain and scarce.Read moreRead less