Papers
6
Total Citations
132
H-Index
4
About
Tim Schork is a pioneering researcher at the intersection of robotic fabrication, computational design, and architectural manufacturing. His work has fundamentally advanced the field of autonomous robotic additive manufacturing, with a particular focus on enabling machines to operate intelligently within complex, real-world construction environments. His most cited work, "Integrating real-time multi-resolution scanning and machine learning for Conformal Robotic 3D Printing in Architecture" (2020, 54 citations), broke new ground by moving robotic 3D printing beyond flat build surfaces, dramatically expanding its potential as a sustainable construction technology. Building on this, his 2022 paper on deep reinforcement learning for autonomous robotic fabrication (50 citations) demonstrated how distributed, model-free AI can guide robots through construction tasks without human intervention — a landmark contribution bridging computational design and robotics communities. Schork has also explored visual feedback systems, topologically optimized cable nets, large-scale multi-colour robotic fabrication, and low-cost inspection robotics for green infrastructure. Collectively accumulating over 130 citations, his body of work positions him as a leading voice in intelligent, adaptive robotic systems for architecture and the built environment.
Research Focus
Key Achievements
Top Papers
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- 3Towards Visual Feedback Loops for Robot-Controlled Additive Manufacturing16 citations · 2018
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- 6The Wallbot: A Low-cost Robot for Green Wall Inspection3 citations · 2020