Duanshun Li

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About

Duanshun Li is a researcher whose work bridges the gap between classical planning and modern geometric computing, with a focus on automation and 3D perception. His key research areas include construction automation, geometric modeling, and point cloud analysis. Li’s most notable contribution is the development of a classical planning model-based approach to automating construction planning on earthwork projects, a seminal 2018 paper that has garnered 26 citations and laid the groundwork for intelligent, resource-efficient construction workflows. In parallel, he has advanced geometric understanding through his work on primitive fitting using deep boundary-aware geometric segmentation, a method that robustly identifies and fits shapes like planes, spheres, cylinders, and cones from noisy point clouds. This 2018 contribution, with 5 citations, addresses a critical challenge in robotics and reverse engineering by enabling precise multi-model, multi-instance fitting. Together, these works demonstrate Li’s ability to integrate AI-driven perception with practical engineering problems, offering impactful solutions for autonomous systems and construction planning. His research continues to inspire students and professionals seeking to automate complex, real-world tasks.