Posts by Michelle Luca
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.
Predictive farming
This Project will investigate artificial intelligence (AI) to improve weather forecasts and use crop models for making better farming decisions. The expected outcome is protocols for integrating AI-enhanced weather forecasts and crop models into farm management and planning tools. This is expected to result in farmers making more informed decisions that optimise resource use, boost crop yields, and enhance overall farm productivity and profitability while minimising environmental impact.
Satellite-based Methane Detection
Methane is a potent greenhouse gas and an important contributor to climate change. This project will develop neural network-based methods to detect anthropogenic methane plumes in satellite imagery and quantify emission rates. The expected outcomes are better detection and monitoring of methane emissions in Australia compared to current methods, with enhanced temporal and spatial coverage. These advancements will enhance Australia’s capability to efficiently identify, quantify and mitigate methane emissions.
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.
Improving infrastructure risks using satellite radar (InSAR) monitoring with GNSS sensor systems
The objective of this project is to develop and test new methods to integrate next generation satellite radar (InSAR) monitoring for ground motion with Global Navigation Satellite Systems (GNSS) positioning devices. This will focus on test sites where the student will investigate the optimal methods for combining multi-satellite InSAR with a network of Kurloo GNSS devices to provide robust 3D ground motion monitoring from space. The potential benefits may include the development of near-real time 3D hazard monitoring for critical infrastructure, extending to pre-collapse alerts, thus reducing the risk of catastrophic events.
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.
Extending the shelf life of UHT plant protein beverages
This Project aims to improve understanding and overcome the negative effects of the secondary lipid oxidation products and Maillard reaction in UHT plant protein beverages. The expected outcome is a methodology to impede the negative impact of malodorous/browning reactions in high protein UHT beverages. This may lead to the extension of shelf life of these products furthering export opportunities.
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.