#engineering
Exploring solar-powered EV charging networks
This project explores strategies for developing a solar-powered EV charging network that ensures comprehensive coverage across urban and remote regions in Australia. The expected outcome is to enhance energy security, mitigate range anxiety, and protect user data, by leveraging AI-driven data analytics and privacy-preserving mechanisms. The project will potentially provide insights into the feasibility and design of a scalable and sustainable EV charging solution in Australia.
AI-driven automatic translation of blueprints into construction instructions
This project develops AI models to address the critical gap in automated interpretation of blueprints in construction domain. The expected outcome is an AI system that translates complex blueprints into plain language actional construction instructions. The project outcome will reduce errors, delays and cost in construction industry, enhancing productivity, safety, and sustainability.
Generalisation of the radiotherapy atlas contouring (TRAC) tool
This project will develop AI tools to both define and check medical image segmentations in radiotherapy clinical trials and clinical practice. The expected outcome is to develop quality assurance tools from artificial intelligence techniques and data from multiple medical imaging modalities. This project will have potential to improve patient outcomes and ensure effective implementation of advanced radiotherapy technologies and clinical trials.
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.
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.
Optimizing NatHERS (Nationwide House Energy Rating Scheme)
This Project aims to improve NatHERS Whole of Home ratings by developing mathematical models for heating and cooling appliances. Expected outcomes are an assessment of various heating and cooling appliances and insights into the most appropriate heating and cooling solutions tailored to specific climate zones. The potential benefit is to enhance the overall energy efficiency and thermal comfort of residential spaces nationwide.
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.