Privacy-Enhanced ML/AI

Projects & Research Activities

Managing Confidential Data and Transparency Policies in LLM-Empowered Science

The Challenge AI is transforming science. Large Language Models (LLMs) like GPT-4 and Claude are accelerating research by helping scientists […]

Trustworthy AI for Government: Collaboration with the Department of Finance’s GovAI Team

As artificial intelligence continues to reshape industries and public services, governments worldwide are seeking to harness its potential responsibly, ensuring […]

Collaboration with the National AI Centre (NAIC) on the development of the Guidance for AI Adoption

As artificial intelligence (AI) systems become deeply integrated into government, industry, and everyday life, trust is fast emerging as the […]

Privacy-Enhanced Federated Learning

The Challenge Today's mobile intelligent devices boast increasingly powerful hardware, enabling data collection and processing at an unprecedented scale. Concurrently, […]

Privacy and Machine Unlearning

The Challenge In the wake of increased computational resources and data availability, Machine Learning (ML) models have been extensively employed […]

Secure Future Digital Manufacturing – Privacy-preserved IoT services

Challenge Future deployments in Industry 4.0/5.0 manufacturing scenarios will use Internet-of-Things (IoT) platforms as a service. Consequently, IoT platforms can […]

Privacy-preserving Data Encoding and Matching (PriDEMatch)

The Challenge Encoding and matching data is an essential component in any privacy preserving data analytics applications. For example, linking […]

Balancing Privacy and Fairness

The Challenge In today's era of big data, safeguarding user data is crucial, especially when vast amounts of user information […]

Privacy-Preserving Analytics for the EdTech Industry

The Challenge Education, Australia’s largest services export (valued at $30bn pa.), increasingly relies on education technology (EdTech) which is a […]