Mohamed Dawod

University College London, University of Kassel

Papers

Total Citations

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About

Mohamed Dawod is a researcher at the forefront of construction robotics and digital fabrication, with a primary focus on autonomous assembly and advanced timber construction. His work bridges building information modeling (BIM) and computer vision to enable robots to operate effectively in unstructured construction environments. Dawod’s most cited paper, “BIM-assisted object recognition for the on-site autonomous robotic assembly of discrete structures” (2019, 18 citations), addresses a critical bottleneck in construction automation: the lack of optimized object detection systems for real-world building sites. By integrating BIM data with robotic perception, he developed a method that allows robots to precisely locate and handle building components without tedious manual setups—a key step toward practical, on-site robotic construction. His additional work on “Continuous Timber Fibre Placement” (2019, 9 citations) explores novel fabrication techniques for sustainable timber structures, contributing to the growing field of digital timber construction. Dawod’s research is notable for its direct application to industry challenges, making him a significant figure in the push toward fully autonomous construction systems.