Haibao Yu

Papers

Total Citations

H-Index

About

Haibao Yu is a rising researcher at the forefront of Embodied AI and multimodal robotics, whose work bridges the gap between high-level language understanding and precise physical robot control. His most notable contribution, "RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis" (2024), tackles the fundamental challenge of translating complex multimodal inputs—including visual scenes and natural language commands—into executable robotic actions. By leveraging code generation as an intermediate representation, Yu’s approach enables robots to synthesize sophisticated behaviors with greater accuracy and adaptability than traditional methods. Though his career is still early-stage, with his flagship paper already garnering 3 citations, the work represents a significant step toward more capable and generalizable embodied AI systems. Yu’s research sits at the critical intersection of large language models, computer vision, and robotics, addressing one of the most pressing problems in the field: how to make robots that can understand and act in the real world. His innovative use of code as a bridge between perception and action marks him as a promising voice in the next generation of robotics researchers.