Architecture in the age of data
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|Date:||Monday 22 May 2017|
|Venue:||EN515 Hawthorn Campus|
Our cities are giant Petri dishes where some buildings grow and thrive while others wane and crumble. Architects have theories about why certain buildings succeed, but we're not really sure, we don't really have the evidence.
Today, as we gather ever increasing amounts of data about our buildings, machine learning is set to end this grand experiment, to allow us to identify why some buildings succeed and others fail.
In this public lecture, Dr Daniel Davis will showcase how his team at WeWork are using building information modeling (BIM) and machine learning to predict the success of their buildings.
Relating this work back to earlier studies he completed at RMIT, Daniel will speculate what these techniques might mean for architects now operating in a world full of uncertainty and data.
About the presenter
Dr Daniel Davis is Director of Product Research at WeWork, New York. Daniel leads a team of researchers who are investigating the relationship between people and space. Using a range of computation and machine learning methods, his team are discovering how workplace design can enhance people’s happiness, productivity, and connection to their community.
Daniel studied architect in New Zealand before completing a PhD in computational design at RMIT under the supervision of Jane Burry and Mark Burry. He has previously published articles in Architect Magazine, AD, and ArchDaily, and books including ‘Thought Leaders of BIM’ (2014).