Matthias Standfest

Matthias Standfest

Matthias Standfest is an architect with main interests directed towards understanding the geometric impact on architecture performance models using machine learning methods. As a researcher at ETH Zurich with Dr. Gerhard Schmitt and as a guest at FCL Singapore with Dr. Ludger Hovestadt, he has balanced method development for mesh based deep learning techniques with the application of these tools to predict urban simulation results in real time. His future research plans are aimed at extending these methods in order to use data streams of anthropocentric urban sensing setups to correlate human biofeedback with architectural design patterns. His aim is to establish a data driven workflow for predicting the holistic effects of formal architectural and urban design decisions in various scales.