Design Automation Lab

Patrick Janssen

Associate Professor
Department of Architecture
National University of Singapore

Adjunct Associate Professor
3D Geoinformation
Department of Urbanism
TU Delft


Patrick Janssen is an Associate Professor at the Department of Architecture at the National University of Singapore and is the Director of the Design Automation Laboratory. He is also Adjunct Associate Professor in “Automation in Urban Planning and Design” at GeoInformation group at the Department of Urbanism, Faculty of Architecture and the Built Environment, TU Delft.

He received his PhD from Hong Kong Polytechnic University, his MSc in Cognitive Science and Intelligent Computing from Westminster University, and his AA Diploma from the Architectural Association.

Patrick conducts research into computational methods and tools for design exploration and optimisation at building and urban scales.

Focus areas:

Parametric Design: Development of methods and tools for parametric design at both building and urban scales, focusing in particular on procedural modelling. The research explores approaches that integrate techniques from different fields, including architecture, engineering, animation, and geospatial. These novel approaches are able to incorporate more complex types of constraints as compared to existing approaches.

Parametric Information Modelling: Development of methods and tools that integrate geometric modelling with semantic information. With these approaches, semantic information is directly attached to the topological components of geometric objects, auch as vertices, edges, wires and faces. The research explores the creation of information rich models, supporting a variety of use cases, including interoperability, analysis and simulation.

Building Information Modelling: Development of methods and tools that link parametric modelling to BIM. The link between BIM and other modelling approaches earlier in the design process remains problematic and difficult. The research explores automated mapping processes from lower resolution models (such as CityGML) into higher resolution models (such as IFC).

Design Optimization: Development of methods and tools for design optimization at both building and urban scales, focusing in particular on evolutionary optimization. The research explores the optimisation of building and urban design proposals that optimize designs for various environmental and economic performance criteria, including daylight performance, energy consumption, and construction cost. The research aims to develop methods and tools that are both usable by and useful for architects and designers.

Spatial Computational Thinking: Development of methods and tools for computational thinking for spatial problem solving. This research focuses on pedaggogical approaches for teaching fundamental computational constructs (such as abstraction, automation, and analyses) and applying these to spatial problems.