AI Lab - Knowledge Representation for Buildings

This course introduces students to semantic modeling and knowledge representation for the built environment. Students will learn how to structure building information using ontologies and knowledge graphs, integrate geometric and semantic data, and apply reasoning techniques to support interdisciplinary workflows in architecture, engineering, and construction. Through hands-on exercises and a collaborative project, participants will develop skills in querying, visualization, and inference, enabling AI-driven applications such as compliance checking, digital fabrication, and intelligent building analysis. No prior knowledge is required, though familiarity with computational design or programming is considered a plus.

The course is held in person. Participants must be enrolled in either Faculty 1 (Architecture) or Faculty 5 (Computer Science). The seminar includes weekly group assignments as well as a final group project.