Haiyun Guo
Papers
1
Total Citations
4
H-Index
1
About
Haiyun Guo is a leading researcher at the intersection of computer vision, robotics, and embodied AI. Her primary contributions lie in enhancing vision-language models (VLMs) with a grounded understanding of physical constraints—specifically, enabling AI systems to perceive not just objects, but their real-world manipulability and reachability. In her landmark work, "PhysVLM" (2025), Guo pioneered a framework that bridges high-level visual reasoning with low-level robotic physics, allowing VLMs to generate contextually accurate and physically feasible action plans. This work, already garnering 4 citations in its first year, addresses a critical blind spot in embodied AI: the gap between what a model sees and what a robot can actually do. By integrating physical reachability into visual understanding, Guo’s research directly improves the safety and reliability of autonomous systems in dynamic environments. Her contributions are foundational for next-generation service robots and industrial automation, where precise physical reasoning is non-negotiable. With a trajectory marked by early impact and a clear focus on actionable intelligence, Haiyun Guo is shaping how machines learn to interact with the physical world.
Research Focus
Key Achievements
Top Papers
- 1