Yuanqi Yao
Papers
1
Total Citations
15
H-Index
1
About
Yuanqi Yao is a leading researcher at the intersection of embodied AI, robotics, and spatial reasoning, with a focus on building generalizable visual-language-action (VLA) models. Their most influential work, "SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Models" (2025), introduces a novel framework that re-discretizes pre-learned action grids to capture robot-specific spatial movements across diverse real-world setups. This contribution has rapidly garnered 15 citations, underscoring its immediate impact on the field. Yao’s research is distinguished by its emphasis on bridging the gap between simulation and reality, achieving exceptional in-distribution generalization and out-of-distribution adaptation—a critical step toward deploying robots in unstructured environments. By tackling the challenge of spatial representation in embodied agents, Yao’s work enables robots to transfer learned skills to new hardware and settings without retraining. Their achievements highlight a commitment to advancing scalable, robust robotic systems, making them a rising figure in the quest for truly autonomous, spatially aware machines.
Research Focus
Key Achievements
Top Papers
- 1