Posts by Michelle Luca

Distributed trust AI for solar energy sustainability in commercial settings

This project develops a scheme and prototype for utilising advanced AI technologies to manage and efficient utilise of solar energy. The expected outcomes is an energy sharing trustworthy framework that enables commercial customers reducing energy bills. The project will lead to a sustainable solution for SMEs and contribute to environment protection.

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.

Dark web analytics for ransomware threat actor profiling

This project investigates active ransomware groups and attempts to identify their key characteristics, attack signatures, victims, and stolen data. The expected outcome is development of a dataset to serve as an essential resource. The project will potentially provide more knowledge on ransomware groups, their tactics, techniques, and procedures for launching attacks.

Fermented plant protein peptides in development of functional elderly milk formulations

This project explores using fermented plant protein peptides in milk formulas for the elderly with potent antioxidant and anti-inflammatory properties. The expected outcome is to ferment plant protein peptides, analyse their bioactive compounds, and assess their in vitro bioactivities. The project aims to develop nutritious, easily digestible, novel dairy formulas, potentially reducing the burden of age-related health concerns on individuals and healthcare systems.

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.

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. 

Catalytic Static Mixers in Organic Synthesis

This Project aims to invent new modes of heterogeneous catalysts (Catalytic Static Mixers - CSMs) to drive new and scalable chemical reactions. The expected outcome is to create catalysis technologies to broaden and sustain Australia’s chemical industries. The potential benefits are the creation of new catalysts, increased technology uptake by industry and the utilisation of critical minerals and rare earth elements in catalysts.

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.