#44 Generative Architectural Design Engine

Advancements in machine learning (ML) and artificial intelligence (AI) models that produce graphics have dominated the discussion around computational creativity for the past 5 years.

Generative neural networks, like DALLE-2 and Midjourney, can render remarkably detailed, intricate and convincing images, to the point where they can be perceived as ‘creative work’. This project aims to leverage these advancements to support creative processes in a more complex field: architectural design.

Using a combination of qualitative methods and advanced ML and AI models, our goal is to develop and implement prototypical digital tools, capable of ‘proposing’ multiple viable architectural design drafts, based on design value and performance. They will be used as a starting point for designers to build upon.

Researchers include: Dr Camilo Cruz Gambardella, Prof Jianfei Cai, Prof Shane Murray, Prof Dinh Phung, Prof Jon McCormack, Prof Mel Dodd & Dr Duncan Maxwell.