When AI systems fail, the blame goes to the algorithm. The cause is almost always the specification — what the system was told to do, before a line of code was written. I build the science that closes that gap.
About
My research sits at the intersection of Requirements Engineering and AI — focusing on how organisations specify, constrain, and audit intelligent systems where failure has real consequences: space missions, defence systems, clinical AI, and regulated industries navigating emerging AI law. The work spans 3,500+ citations and $2.5M+ in competitive funding.
I have worked on this problem for over a decade — from NLP automation for requirements in 2013 through to RAG-powered RE for space missions in 2024. The current focus is on LLMs, retrieval-augmented generation, and runtime monitoring for AI systems, across four research themes: AI for RE, Responsible AI, Human-Centred SE, and Software Systems & Applications.
I also serve as Director of Education for Monash's Software Systems & Cybersecurity department, where I focus on redesigning how software engineers are trained for an AI-native world.
Former Systems Engineer at SES Satellites, Luxembourg — one of the world's largest satellite operators. Industry experience in requirements engineering across space, automotive, and regulatory compliance domains underpins all of the research programme.
Member of the International Requirements Engineering Board (IREB) — the global body for RE professional standards — and the IREB AI Special Interest Group. Board Member and Oceania representative for RE professional standards globally.
Leading RE and design for Monash–WHO living evidence ecosystems informing health policy across South-East Asia and the Western Pacific. Invited panellist at AU–EU AI governance dialogues; contributor to the EU Strategic Autonomy book (2026).
Work cited at SIGCSE 2026 in Google's industry session on how generative AI tools are changing how software engineers work — and where requirements skills remain essential.
Research Focus
Using LLMs, RAG, and NLP to automate how requirements are elicited, validated, and translated into verifiable system behaviour — across regulated industries, space, and defence.
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Specifying, monitoring, and governing AI systems so they remain trustworthy over time — covering fairness requirements, runtime monitoring for ML systems, and agentic AI guardrails.
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Placing human needs, cognitive constraints, and social context at the centre of software design — through empirical studies, accessibility engineering, and user-centric requirements processes.
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Applied software engineering research spanning adaptive and connected systems, mobile ecosystems, defect management, IoT, and misinformation mitigation — often in collaboration with industry partners.
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Research Supervision
An active supervision portfolio spanning AI safety, requirements engineering, healthcare AI ethics, and cultural computing — with students at Monash University and collaborating institutions.
Speaking & Consulting
Available for keynotes, industry panels, government briefings, and podcasts on AI governance, trustworthy AI specification, and the future of software engineering.
I help organisations deploying AI systems get the specification right — before the cost of getting it wrong becomes real. Particularly suited to regulated industries and safety-critical contexts.
Get in Touch
Whether you're looking for a keynote speaker, a research collaborator, an advisor on trustworthy AI, or a partner for an industry R&D project — I'd like to hear from you.