High-value functional ingredients from bean processing waste. Legumes are considered highly nutritious and sustainable food. Accordingly, there is a steady growth in the consumption of legumes worldwide, including in Australia. Due to lengthy soaking and cooking times, consumers prefer ready-to-eat canned legumes. The current processing technologies are energy and water-intensive and generate considerable waste. This project investigates the application of non-thermal technologies to reduce pro ....High-value functional ingredients from bean processing waste. Legumes are considered highly nutritious and sustainable food. Accordingly, there is a steady growth in the consumption of legumes worldwide, including in Australia. Due to lengthy soaking and cooking times, consumers prefer ready-to-eat canned legumes. The current processing technologies are energy and water-intensive and generate considerable waste. This project investigates the application of non-thermal technologies to reduce processing time, water and energy use and enable the recovery of valuable polyphenols and soluble dietary fibres normally lost in the wastewater. This knowledge will lead to sustainable beans processing, delivering improved productivity to Australian manufacturers and quality food to Australian consumers.Read moreRead less
Incorporation of legume protein in liquid breakfast for a healthy Australia. This project aims to understand and control the properties and interactions of legume protein with other ingredients (e.g. whey protein and dietary fibre) to formulate healthy liquid foods with superior techno-functionality. This research should significantly broaden our understanding of the behaviour of legume protein-phospholipid complexes and their contribution to malodorous flavour development. The expected outcomes ....Incorporation of legume protein in liquid breakfast for a healthy Australia. This project aims to understand and control the properties and interactions of legume protein with other ingredients (e.g. whey protein and dietary fibre) to formulate healthy liquid foods with superior techno-functionality. This research should significantly broaden our understanding of the behaviour of legume protein-phospholipid complexes and their contribution to malodorous flavour development. The expected outcomes are protocols to prevent undesirable sensory characteristics in liquid foods. This should benefit the food industry by improving the sensory attributes of beverages enriched with legume protein, leading to the creation of novel, highly nutritious products with superior sensory attributes and long shelf-life.Read moreRead less
Intelligent bioprocessing for next-generation nutritional yeast extracts. This project aims to provide new, science-based levers for optimising the industrial production of tailormade yeast extracts for food applications. Advanced biochemical and engineering methods will be used to develop new knowledge of the links between yeast growth conditions, cell biochemistry, processing and the flavour and texture profiles of yeast hydrolysates. This understanding will allow the properties of yeast hydro ....Intelligent bioprocessing for next-generation nutritional yeast extracts. This project aims to provide new, science-based levers for optimising the industrial production of tailormade yeast extracts for food applications. Advanced biochemical and engineering methods will be used to develop new knowledge of the links between yeast growth conditions, cell biochemistry, processing and the flavour and texture profiles of yeast hydrolysates. This understanding will allow the properties of yeast hydrolysates to be accurately tuned during yeast production and processing. The resulting process improvements and innovations will increase the efficiency and quality of current yeast extract products and allow the development of new food products.Read moreRead less
Chemicals in compostable food contact paper packaging materials. The aim of this project is to understand the presence of persistent chemicals in recyclable and compostable food contact materials (FCMs). These types of products are destined for recycling or biowaste streams that bridge the gap from take-make-dispose and into a circular economy. Currently, the knowledge of the chemicals in these products is limited but we need to ensure that they are safe and do not unnecessarily contaminate reso ....Chemicals in compostable food contact paper packaging materials. The aim of this project is to understand the presence of persistent chemicals in recyclable and compostable food contact materials (FCMs). These types of products are destined for recycling or biowaste streams that bridge the gap from take-make-dispose and into a circular economy. Currently, the knowledge of the chemicals in these products is limited but we need to ensure that they are safe and do not unnecessarily contaminate resource recovery streams. It is expected that this project will develop a framework that could be used by industry and government to prevent chemicals of concern persisting in a circular economy, providing environmental and economic benefits through reduced risk of chemical exposure and unnecessary remediation costs.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Flavour enhancing functional feeds for farmed Barramundi. This project aims to improve the flavour quality of Australian farmed barramundi through developing novel functional feeds. The project expects to expand our fundamental knowledge of flavour enhancement, whilst providing practical benefits with respect to final product quality. The project will enable industry to achieve higher product quality benchmarks, towards the ultimate goal of improving the marketability of barramundi both locally ....Flavour enhancing functional feeds for farmed Barramundi. This project aims to improve the flavour quality of Australian farmed barramundi through developing novel functional feeds. The project expects to expand our fundamental knowledge of flavour enhancement, whilst providing practical benefits with respect to final product quality. The project will enable industry to achieve higher product quality benchmarks, towards the ultimate goal of improving the marketability of barramundi both locally and overseas. This project will provide significant benefits to the Australian barramundi industry by increasing product values, thereby facilitating an economically sustainable growth of this important regional industry.Read moreRead less
Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatm ....Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatments through the linking of relevant biochemical information. By delivering new methods that improve the compilation of knowledge about chemicals and drugs from textual information resources, the project hopes to enable faster drug discovery.Read moreRead less
Deep mining neurological abnormalities from brain signal data. This project aims to develop a reliable, robust and real-time analysis system for automatic and accurate detection of neurological abnormalities, and the prediction of impending neurological problems from brain signal data. The project expects to design novel algorithms for brain signal processing, data compression, and detection and prediction of neurological abnormalities from massive brain signal data. The project will lead to sig ....Deep mining neurological abnormalities from brain signal data. This project aims to develop a reliable, robust and real-time analysis system for automatic and accurate detection of neurological abnormalities, and the prediction of impending neurological problems from brain signal data. The project expects to design novel algorithms for brain signal processing, data compression, and detection and prediction of neurological abnormalities from massive brain signal data. The project will lead to significant improvement of existing methods in health monitoring applications in Australia and worldwide and hence will save lives, money and resources.Read moreRead less
AI for Legal Problem Diagnosis in the Diverse Language of Australians. The number of Australians with unmet legal needs is estimated to be over four million people per year and growing, and free legal assistance is severely under-resourced. A bottleneck for free legal assistance providers is the determination of what (if any) specific legal needs the individual has, to which end this project proposes to develop AI models to semi-automate the process, with particular focus on fairness across user ....AI for Legal Problem Diagnosis in the Diverse Language of Australians. The number of Australians with unmet legal needs is estimated to be over four million people per year and growing, and free legal assistance is severely under-resourced. A bottleneck for free legal assistance providers is the determination of what (if any) specific legal needs the individual has, to which end this project proposes to develop AI models to semi-automate the process, with particular focus on fairness across users of all backgrounds, generalisation from small amounts of curated data, and dynamic interaction with the help-seeker. The project will help deliver legal assistance to some of the most vulnerable members of Australian society, and reinforce Australia's position as a world leader in AI for Law.Read moreRead less