“Education is not the filling of a pail, but the lighting of a fire.”
— W. B. Yeats
I teach bachelor, master, and PhD programmes at Aalborg University, spanning three disciplines: software engineering, artificial intelligence, and research methodology. My approach treats software engineering as much about people and processes as about technology; students grapple with authentic problems and learn to navigate ambiguity alongside technical depth.
Programs
Software Engineering
The full spectrum of software engineering practice, from contemporary agile methodologies and iterative development to large-scale systems architecture.
Human-Centred AI
How AI reshapes software development and organisational practice: responsible AI design, fairness, transparency, and the societal implications of intelligent systems at scale.
Research Methodology
Advanced quantitative and empirical methods for doctoral researchers, from structural equation modelling to research design, the foundations for credible SE scholarship.
PhD Supervision
Supervising doctoral projects at the intersection of AI, software engineering, and human factors, with an emphasis on rigorous, open, and replicable empirical work.
Refreshed each semester. If none of these fit, propose your own.
Adoption of agentic AI coding tools in professional teams
Extends the HACAF framework to agentic workflows, where the unit of work is a delegated task rather than a suggestion. Survey design and PLS-SEM analysis.
New forms of technical and organisational debt in AI-assisted development
A mixed-methods study of where debt accumulates when code is generated faster than it is understood, and who ends up owning it.
Psychological safety in hybrid, AI-mediated software teams
Survey work on how communication and team climate change when part of the team’s output is machine-generated.
Measuring the effectiveness of human oversight of AI systems
Instrument development against EU AI Act obligations, where meaningful human oversight is required but not operationally defined.
Generative AI in software engineering education
Curriculum and assessment redesign under the AAU problem-based learning model, where group work and open-ended projects complicate conventional academic-integrity responses.
Measurement invariance in longitudinal developer surveys
For students with quantitative interests: whether an instrument measures the same construct across waves and populations. SmartPLS and R.
A strong inquiry is short and specific. Tell me your background, which pillar or topic above your interest sits closest to, and one concrete idea of your own, even a rough one. What distinguishes a promising message is not polish but evidence that you have thought about a particular problem rather than about supervision in general.
I read everything that arrives and reply to inquiries that are specific. The topics above are master’s projects. If you are looking for funded doctoral work instead, the Industrial PhD route is often the best-funded path, and the openings page describes it and its usual September deadline.