Wayne Wu

Papers

Total Citations

H-Index

About

Wayne Wu is an emerging researcher at the intersection of embodied AI, robotics simulation, and urban autonomy. His work addresses one of the most pressing challenges in modern robotics: bridging the gap between simulated training environments and real-world deployment. Wu's most cited contribution, "Vid2Sim" (2025), introduces a novel framework for generating realistic, interactive simulations directly from video footage of urban environments, offering a compelling alternative to traditional domain randomization and system identification approaches for reducing the sim-to-real gap in robot learning. Complementing this, his work on "MetaUrban" (2024) establishes a comprehensive embodied AI simulation platform specifically designed for urban micromobility scenarios — a rapidly growing domain as delivery robots and assistive devices increasingly share public spaces with pedestrians. Together, these contributions position Wu as a pioneer in making urban environments accessible and navigable for autonomous agents. With citations accumulating across both foundational simulation methodology and applied urban robotics, Wu's research speaks directly to students and engineers working on scalable, real-world robot deployment. His focus on socially integrated autonomous systems reflects a forward-looking vision for how AI will coexist with human life in everyday urban spaces.