#programming
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.
Multimodal sensing intelligence for aerial robots in bushfire mitigation and pest management
This project develops advanced multimodal sensing techniques for next-generation aerial robots to improve bushfire mitigation and pest management. The expected outcome is a robotic sensing prototype for real-time monitoring. This technology will deliver customer, national, industry, and public benefits through enhanced safety, sustainability, cost-efficiency, and support for Indigenous manufacturing.
Smartphone for triage to detect stroke
This project will focus on AI based voice analysis to assess patients in the emergency departments to assist in early detection of stroke conditions. The expected outcome is to develop interactive software and AI modelling focusing on responsible AI, overcoming gender, ethnicity and age-related biases. The potential benefit of this project is to reduce misdiagnosis that takes place in hospitals due to differences in gender, age and ethnicity.
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.
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.
Ecological drivers of disease spread in horticultural tree crops
This project investigates ecological interactions that influence disease spread in tree crop horticultural systems. The expected outcomes are improved understanding of ecological drivers of the dynamics of diseases and ecological intervention/restoration strategies for disease management. The potential benefit is chemically limited sustainable disease management in horticulture, benefiting industry and the environment.
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.
Cyber security risk mitigation for sensor data integrity
This Project will investigate cyber security risk mitigation approaches to secure the integrity of sensor information feeding into critical infrastructure operational systems and digital twins. The expected outcome is the development of guidelines for implementing robust cyber security measures. This may enhance resilience against cyber threats and ensure the integrity of decision-making processes.