CAIML

Knowledge Discovery in Architecture

Coordinator: Milica Vujovic

The proposed SIG focuses on complex design and planning problems in architecture and spatial planning. Emphasis will be placed on multi-domain and multiscale planning and design problems and the role of AI and ML in enabling data-driven knowledge discovery and decision support. An evidence-based approach will support the effectiveness of decision-making in design by creating models and interpreting the built environment using data. The SIG aims to create a framework where decision-making in architectural and spatial design of various scales are supported by AI and ML.

Events

Scientific Committee Members

  • Senior Researcher Dr. Cédric Pruski, LIST Luxembourg Institute of Technology
  • Assoc. Prof. Dr. Defne Sunguroglu Hensel, Southeast University of Nanjing, China
  • Prof. Dr. Arno Schlueter ETHZ, Zurich, Switzerland
  • Prof. Dr. Mathilde Marengo, IAAC Barcelona, Spain
  • Senior Lecturer Dr. Djordje Stojanovic, University of Melbourne, Australia
  • Assoc. Prof. Dr. Mutlu Cukurova, University College London, UK
  • Prof. Dr. Mirko Rakovic, University of Novi Sad, Serbia
  • Prof. Dr. Bojan Tepavcevic, University of Novi Sad, Serbia
  • Prof Dr. Jeffrey Huang, EPFL, Lausanne, Switzerland
  • Dr. Frank Neffke, Complexity Science Hub Vienna, Austria