#machine learning
Improving GNSS measurements of Australia’s deformation using machine learning
This Project will improve the accuracy of estimates of Australia’s 3D motion and deformation using machine learning methods. This will apply new methods to hundreds of Global Navigation Satellite System (GNSS) sites to improve understanding of Australia’s vertical land motion and sea level research. This may improve satellite positioning products used by Australian industry, government and researchers.
AI for Early Detection of Neurodegenerative Disorder in Elderly
This Project aims to develop outcome measures for early detection of neurodegenerative disorders using artificial intelligence (AI) and various sensing modalities, offering personalised support to older adults. The expected outcome is the creation of AI algorithms to detect early signs of neurodegenerative disorders in older adults living independently at home. The potential benefit is early detection of neurodegenerative disorders in older adults, improving quality of life and effective disease management.
Applying imaging methods and data analytics to explore the listening brain
This Project aims to understand brain circuits and processes supporting communication in individuals with hearing problems, including those who use devices such as hearing aids and cochlear implants. The potential benefits are that individualised strategies based on real-time brain states estimate algorithms to empower listening and support effective communication. The Project will use brain-imaging techniques‚ including those compatible with listening technologies, including electroencephalogram (EEG), to explore the listening brain. The Project will explore brain changes that arise from hearing loss, how changes in brain function – within and beyond the auditory brain – arise to support listening when hearing is impaired, and how these findings can be used as a part of devices such as cochlear implants that engage the rest of the brain to support an individual's listening.
Clinical lab automation with AI human robot interface
This Project will develop an AI-based robotic programming interface based on large-language model that allows practitioners, regardless of their technical expertise, to efficiently program and control robots. The expected outcomes are to improve efficiency in designing and deploying clinical lab automation and to expand the use of robotics within laboratories. This may lead to improvements with workflow for clinical lab automation, particularly during high-demand situations like pandemic outbreaks.
Improving cropping decisions with AI-enhanced weather forecasts
This project will investigate the use of artificial intelligence (AI) to improve weather forecasts and discover how AI forecasts can advance farming decisions by coupling with crop models and smart farming tools. This is an exciting opportunity to develop or integrate novel AI-enhanced weather forecasts into real world modelling applications, for example in the sugarcane industry. With research being undertaken alongside real farm advisors, your research can help industry to optimise resource use and enhance overall farm productivity while minimising environmental impact.
Communicating in the real world
This project aims to utilise existing sensor technologies to evaluate the impact of hearing loss when communicating in noisy environments. The expected outcome is the discovery of novel analysis methods that utilise multi-sensor fusion techniques. The potential benefit is improved outcomes for individuals with hearing loss.