AI in Architecture, Planning, and Environment

AI|APE Research School Artificial Intelligence in Architecture, Planning, and Environment, a programme for doctoral candidates at the Faculty of Architecture and Planning

Since October 2026 the research school has brought together ten doctoral projects in which artificial intelligence carries part of the research. Topics range from AI-aided generation and editing of design content through data analysis and prediction to knowledge discovery and decision support in architecture, planning and environmental transformation. Participants come from architecture, spatial planning, geosciences and environmental engineering.

The programme runs for three years. It brings together doctoral candidates working on related questions so that they challenge and support one another, and gives them a structure that helps them through the scientific expectations of the doctorate. What gets researched is up to the candidates and their supervisors.

Why here: data has become the methodological ground of architecture and planning, as the rapid growth of Architectural Science, City Science and Urban Science shows. AI sits at the centre of these data-driven methods. How it changes the disciplines is still open, and the faculty means to have a hand in it.

The projects treat AI as an applied method, a design instrument, a subject of critical inquiry or a governance question. That includes generative AI and language models in design, machine learning for spatial prediction, land use and planning analytics, computer vision for analysing the built environment, ML-based building and environmental simulation, language processing for planning and policy documents, AI in participatory processes, and data ethics, algorithmic bias and accountability in architecture and planning.

What participants get. Access to the AI|APE Competence Center with its lecture series, expert network and ongoing research; colloquia to present their work to leading international scholars; events with practitioners who work with AI-aided methods; informal exchange with doctoral candidates on related topics; and resources to build formats of their own.

What is expected. Taking part in the lecture series, jour fixes, colloquia and workshops, presenting progress regularly, and co-organising the peer-learning sessions.

Participation is free of charge; travel and accommodation for on-site meetings are partly covered. The school is also the blueprint for a doctoral school, to be worked out by the end of 2027.

Joining. Doctoral candidates enrolled at TU Wien with a fitting dissertation project can apply at any time: a motivation letter stating the current stage of the work (max. 1 page), a CV with topic and supervisor(s) (max. 3 pages), a statement of support from the supervisor (max. 1 page) and an exposé with context, aim, research questions and methodology (max. 3 pages), compiled into one PDF (max. 5 MB) and sent to michael.hensel@tuwien.ac.at and gabriel.wurzer@tuwien.ac.at.

Coordination: AI|APE Competence Center, Faculty of Architecture and Planning, TU Wien.