Rundong Luo

Papers

Total Citations

H-Index

About

Rundong Luo is a researcher focused on advancing 3D generative modeling, with a particular emphasis on creating physically plausible and interactable objects for applications in robotics, simulation, and 3D printing. His major contribution is the development of **PhysPart**, a novel framework for physically plausible part completion of interactable objects. This work addresses a critical gap in existing 3D generative models, which often produce static or physically inconsistent shapes, by ensuring that generated object parts not only look realistic but also function correctly under physical interactions. Luo’s approach enables automated modeling of everyday objects, such as tools and furniture, making them suitable for use in robot simulation environments and interactive virtual worlds. Although early in his career, his work has already garnered attention, with his most-cited paper accumulating 2 citations within its first year of publication. By bridging the gap between geometric generation and physical plausibility, Luo is helping to lay the groundwork for more practical and deployable 3D content creation, with potential impacts on embodied AI, digital twins, and automated design.