#computer science
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.
Fast forward computation of radiation transport for emergency response, environmental protection, and national security
This project will focus on developing a novel fast computational tool for use in Australian emergency response, environmental protection, and national security applications. The expected outcome is for the model to be incorporated into relevant extant situational awareness tools and geographic information systems to enhance utility to support emergency response, environmental protection, and national security operations. First responders, national security and environmental agencies concerned with nuclear and radiological hazards will benefit from enhanced planning and operational information.
AI-empowered visual recognition system for dairy cow identification, health and behaviour monitoring
This project develops an AI-driven system to identify individual cows, and monitor and detect their health and behaviour, through the use of facial recognition, posture analysis, and thermal imaging. The expected outcome is early detection of illness and abnormal activity of cows. This project will support productivity, reduce losses, and improve animal welfare in the dairy industry.
Building responsible AI: Co-designing knowledge transfer solutions using generative AI
This project will bridge the gap between the principles of responsible AI and their measurable practice, by developing AI knowledge tools to empower end-user community groups. The expected outcomes are to build insights and develop AI tools for information dissemination and knowledge transfer. The potential benefit is to produce responsible AI solutions to help disability groups connect, communicate, share and learn.
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.
Quantifying methane emissions from wastewater treatment
This project aims to quantify methane emissions from wastewater treatment plants. The expected outcomes are improved understanding of methane emissions from within the plant, their spatial and temporal variability, and how they contribute to the total emissions. This may reduce emissions of methane.
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.
Enhancing cybersecurity with AI and Large Language Models
This project will explore the integration of artificial intelligence (AI) and large language models (LLMs) to predict organisational cybersecurity risks and mitigate threats in advance. The expected outcomes are an enhanced cybersecurity framework, better threat intelligence techniques and user-centric designs, and an adaptable solution. This may help businesses to identify cyber risks and prevent cyber incidents prior to happening and avoid financial losses and brand damage.