Machine learning; computational design; structural design; digital/robotic fabrication.
Innovation lives at the intersections.
Tao Sun is a PhD student in Building Science, Technology, and Sustainability at the College of Environmental Design, UC Berkeley. His research focuses on machine learning for architectural computation, with an emphasis on structural form-finding, digital and robotic fabrication, and open-source tools for design workflows. Sun earned an MA in Architecture (2024) and a BA in Architecture (2021) from the Technical University of Munich (TUM), and completed an exchange year in software engineering at the University of Queensland (2020). He has worked across practice and research — including the specialist modeling group at Foster + Partners in London, BMW’s design and IT teams, and applied AI R&D in industry — and he has taught computational design and digital fabrication at TUM.
Beyond academia, he serves on the Bavarian Chamber of Architects’ Strategy Group for Digitalization, advancing digital transformation in the built environment, and co-manages social media for the International Association for Shell and Spatial Structures to expand the community’s research visibility and engagement.
T. Sun, P. D’Acunto, and F. Petzold, “Structural embodiment – unified workflow and toolkit for form-finding, solid geometry generation and visualisation via deep learning methods,” in Proc. IASS 2024, 2024.
T. Sun, M. Konstantatou, C. Fivet, and P. D’Acunto, “Geometry-driven stock-constrained truss design via equilibrium-based structural models,” in Lecture Notes in Civil Engineering. Springer, 2024.
T. Sun* and C. Lindner*, “Transformable cladding systems,” Technical University of Munich, 2021.
*denotes equal contribution