Beyond Speech: Towards better communication for children with hearing loss. Despite the benefits of early newborn hearing screening and early intervention programs for children with hearing loss, most still experience academic and social challenges at school. This is partly due to ongoing listening effort, leading to communicative breakdown. This project aims to identify the locus of the communicative challenges these children face during daily discourse interactions. The outcomes will identify ....Beyond Speech: Towards better communication for children with hearing loss. Despite the benefits of early newborn hearing screening and early intervention programs for children with hearing loss, most still experience academic and social challenges at school. This is partly due to ongoing listening effort, leading to communicative breakdown. This project aims to identify the locus of the communicative challenges these children face during daily discourse interactions. The outcomes will identify which levels of language are most compromised and will inform future interventions to reduce children’s listening effort. This will be undertaken by bringing together researchers in basic science with hearing service providers, parents and industry, providing an innovative model for solving multidisciplinary challenges.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
Nurturing Australia's Little Multilingual Minds. Despite its substantial multilingual capacity of more than 300 languages, Australia has been described as a 'graveyard for languages'. In partnering with community organisations we will facilitate polyglot early learning, commencing with Spanish and Vietnamese. Expected outcomes are a deep understanding of multilingual families’ experiences, a model to support lifespan multilingual education, and openly-accessible database of child language in her ....Nurturing Australia's Little Multilingual Minds. Despite its substantial multilingual capacity of more than 300 languages, Australia has been described as a 'graveyard for languages'. In partnering with community organisations we will facilitate polyglot early learning, commencing with Spanish and Vietnamese. Expected outcomes are a deep understanding of multilingual families’ experiences, a model to support lifespan multilingual education, and openly-accessible database of child language in heritage languages. Benefits include a pivotal contribution to early childhood education with the creation of a tailor-made, principle-based program, which will enhance children’s academic achievement, familial social and mental wellbeing, and cultural and economic opportunities for all Australians. 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
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
The ABC’s of listening and learning: a study in the Northern Territory. Indigenous Australian children experience middle ear disorders earlier in life and for longer periods than their non-Indigenous counterparts. The resulting listening challenges can have implications for academic achievement and future health and well-being, despite normal hearing thresholds. The current project aims to determine the effects of pervasive otitis media and related hearing loss on Indigenous children’s listening ....The ABC’s of listening and learning: a study in the Northern Territory. Indigenous Australian children experience middle ear disorders earlier in life and for longer periods than their non-Indigenous counterparts. The resulting listening challenges can have implications for academic achievement and future health and well-being, despite normal hearing thresholds. The current project aims to determine the effects of pervasive otitis media and related hearing loss on Indigenous children’s listening and pre-literacy skills in the Northern Territory, and how to better identify those at most risk for poor educational outcomes. The findings will lead to policy recommendations to help improve these children’s learning potential.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
Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business t ....Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business tasks and handle fast-changing scenarios in business. The Self-Evolving EIA is a critical step on the path towards the future generation of EIA. Expected outcomes of this project are to develop adaptive EIA for Small and Medium Enterprise to improve their customer service quality.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