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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.

Enhanced resilience of irrigated agricultural floodplain landscapes of the Murray-Darling Basin

This project investigates the functional response of floodplain vegetation to environmental drivers at multiple scales in the Murray-Darling Basin. The expected outcome includes a series of tools for prioritising the management of floodplain vegetation communities across the landscape of the Murray-Darling Basin at multiple scales and identifying thresholds for environmental watering. The potential benefits are spatial data and new knowledge that will guide future environmental flow management for the benefit of iconic floodplain vegetation communities and related ecosystem services, especially those important to irrigated agricultural, such as water quality. 

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. 

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. 

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.

Valuing non-crop vegetation in horticultural landscapes of Australia

This project will explore the extent to which areas on farms such as semi-natural vegetation, tree plantings, woodlands, and shelterbelts benefit producers through ecological mechanisms, such as enhancing pollinators or pest predators along with broader aesthetic and Indigenous cultural benefits. The outcome of this project will provide an improved understanding of the scale and relative importance of these benefits in the agricultural production landscape of northern New South Wales. This project will directly support horticulturalists in the region and guide future policy.

Quantum-AI for food security and student wellbeing

This project develops quantum-AI tools to optimise urban hydroponic food systems and evaluate their therapeutic impact on student well-being. The expected outcome is to create quantum-reinforced AI algorithms for resource-efficient hydroponics and evidence-based frameworks for integrating green space exposure for improved student wellbeing. This project will potentially enhance urban food resilience, reduce resource waste, and create scalable mental health interventions, advancing national sustainability and education priorities. 

Real-time quality assurance and machine validation for ultra precision manufacturing

This project is developing a real-time quality assurance system to detect precision assembly errors and validate CNC machine performance using quantitative data. The expected outcome is an intelligent, data-driven quality control method that improves the accuracy and reliability of ultra-precision manufacturing. This technology will potentially result in improved product traceability, reduced defects, and increased compliance with medical and military standard for the advanced manufacturing industry.

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.