Posts by Michelle Luca

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.

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. 

Origin of hydrogen and helium occurrences

This Project seeks to understand the geological settings that facilitate the generation and accumulation of natural hydrogen. The expected outcome is to track the critical elements involved in the hydrogen and helium gas resources. This may result in fast-tracking the industrial production of natural hydrogen.

Repurposing & fortification of nutrient-rich waste streams

This project investigates the potential of the combined waste streams from the two industries to develop new ingredients for food applications. The expected outcome is a framework to develop products from reclaimed and fortified nutrient-rich fractions suited to their physico-chemical properties. The potential benefit is improved nutrient upcycling, reduced food waste and carbon footprint. 

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.   

Evaluating Robotic Medical Surgery with Multimodal and Responsible AI

This Project aims to develop multimodal and responsible artificial intelligence (AI) for automated robotic surgery assessment. The expected outcome is to develop multimodal and responsible AI for automated robotic surgery assessment. The potential benefit is enhanced surgical training, improved patient outcomes, reduced training costs, and increased transparency. 

Fingerprinting critical minerals development in continental margins

This project will study how critical minerals develop in the Andean-type plate margins through case studies in eastern Australia. The expected outcomes are results that characterise signature minerals in a polymetallic minerals province in Far North Queensland. This may result in supplying new data-driven mineralisation models for key exploration regions.

Li-ion battery separator material recovery and utilisation

Sodium battery is a promising alternative for energy storage if precious metal prices for making LIB remain high. This Project will mainly focus on the recovery of LIB separator material and explore economic applications of the recovered separator materials, such as turning it into high-value hard carbon for making sodium battery anode material.

Data analytics for enhanced hearing health

This project aims to consolidate hearing health data with other datasets to unlock valuable insights and drive personalised hearing healthcare interventions. The expected outcomes are to streamline access to hearing health data, improve data connectivity, and enhance treatment outcomes. The potential benefit is to facilitate informed decision-making for healthcare providers to enable better patient care.