A computer science graduate from the University of Adelaide, working across artificial intelligence, machine learning, software engineering, and software validation.
My work spans both research and applied engineering. I have worked on projects involving computer vision, biomedical image analysis, retrieval-augmented generation (RAG), AI-powered customer support systems, telecommunications technology, and medical device software validation.
Professionally, I work as an AI Solutions Engineer and Software Validation Engineer. My work ranges from designing AI-assisted workflows and building knowledge-driven conversational systems to defining software requirements, developing verification strategies, creating test cases, analysing defects, and producing traceable engineering documentation.
What interests me most is not only whether a system works, but why it works, where it fails, and how we can make it more reliable.
This website is my technical notebook and project archive. I use it to document the thinking behind the systems and research projects I work on, including architecture decisions, experiments, failed approaches, debugging processes, validation strategies, and lessons learned during implementation.
Rather than showing only polished final results, I want to keep a record of the reasoning and engineering process behind them.
My current interests sit at the intersection of AI research, intelligent systems, computer vision, and reliable software engineering, and I am particularly interested in problems where machine learning systems need to operate robustly in real-world environments.