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About

Qiaojun Yu is an emerging robotics and embodied AI researcher whose work sits at the intersection of autonomous manipulation, code generation, and intelligent simulation. His research addresses some of the field's most pressing challenges: enabling robots to perform complex, real-world tasks through sophisticated reasoning and generative technologies. Yu's most impactful contribution, "RoboTwin" (2025), has already garnered 16 citations within its first year, introducing a dual-arm robot benchmark powered by generative digital twins that tackles the critical shortage of high-quality training data and realistic evaluation environments for autonomous systems. Complementing this, his "RoboScript" and "RoboCodeX" projects advance the frontier of multimodal code generation, allowing robots to synthesize physical behaviors from complex inputs and execute free-form manipulation tasks across both real and simulated environments. Together, these works represent a coherent and ambitious research vision: bridging the gap between high-level AI reasoning and precise robotic action. Yu's early publication record signals a researcher rapidly establishing himself as a meaningful contributor to next-generation embodied intelligence and human-robot collaboration systems.