Siamak Layeghy

Prospective Students

I welcome applications from motivated MPhil and PhD candidates interested in working at the intersection of AI/ML, cybersecurity, and networking. Research in my group is hands-on and experimentally rigorous, with a strong emphasis on producing work that is deployable, reproducible, and publishable. Current projects span four broad directions: applied ML for security and networked systems; large language and foundation models for security analytics and automation; adversarially robust and continual learning for resilient detection in dynamic environments; and AI-driven analytics for energy systems and consumer behaviour. Students are expected to contribute to open research artefacts as well as refereed publications. Strong candidates will have solid programming skills (e.g., Python or C++), a background in either ML or networking, and an appetite for tackling applied research problems with methodological care. I particularly encourage enquiries from graduates in Computer Science, Software Engineering, or Network Engineering.

About me

I am a Lecturer and researcher at The University of Queensland working on practical AI/ML for cybersecurity, networked systems, and energy analytics. My research focuses on robust and scalable methods for detecting, understanding, and responding to complex behaviour in dynamic environments, spanning modern networks, computing systems, and energy infrastructure. Current themes include large language and foundation models for security analytics and automation, adversarially robust and continual learning, explainable ML, and data-driven methods that support trustworthy operational and decision-making outcomes in real-world settings.