#programming

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.

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.​

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. 

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.