Building design processes are dynamic and complex. The context of a building project is manifold and depends on the cultural context, climatic conditions and personal design preferences. Many stakeholders may be involved in deciding between a large space of possible designs defined by a set of influential design parameters. Building performance simulation is the state-of-the-art way to provide estimates of the energy and environmental performance of various design alternatives. However, setting up a simulation model can be labour intensive and evaluating it can be computationally costly. As a consequence, building simulations often occur towards the end of the design process instead of being an active component in design processes. This observation and the growing availability of machine learning algorithms as an aid to exploring analytical problems has lead to the development of surrogate models. The idea of surrogate models is to learn from a high-fidelity counterpart, here a building simulation model, by emulating the simulation outputs given the simulation inputs. The key advantage is their computational efficiency. They can produce performance estimates for hundreds of thousands of building designs within seconds. This has great potential to innovate the field. Instead of only being able to assess a few specific designs, entire regions of the design space can be explored, or instantaneous feedback on the sustainability of building can be given to architects during design sessions. I would like to express my thank to my supervisor, Dr. Ralph Evins, for giving me the opportunity to join him and the young Energy and Cities group in beautiful Victoria, for his guidance, and for his support to accommodate any of my plans. A special thanks goes to the rapidly growing team, which always had an open ear for my research ideas and brought in valuable input for my work. Especially I would like to thank Gaby Baasch, David Rulff, Matthias Welzel, David Fritzsche, Kevin Cant, Theo Christiaanse, and Gaëlle Faure. I also owe many thanks to Professor Arno Schlüter and the A/S research group at the Institute for Technology in Architecture, ETH Zurich, for hosting me during my visits in Zurich. Finally, I would like to express great gratitude to limitless support off-campus. Thanks to Chris Wood, Miguel Alvarez, Toby Cotton, Aurélien Liné, Claire Remington, the UVIC Field Hockey team and all the others. Thanks to my sisters and parents. Thank you, Fredi.
