Xuemei Xie
Papers
2
Total Citations
10
H-Index
1
About
Xuemei Xie is a rising researcher at the intersection of embodied AI and robotic perception, whose work bridges tactile sensing and visual-language reasoning. Her most impactful contribution, "Improving Robotic Tactile Localization Super-resolution via Spatiotemporal Continuity Learning and Overlapping Air Chambers" (2023, 9 citations), draws inspiration from the human hand’s innate ability to refine touch through practice. She introduces a novel method that learns spatiotemporal continuity of contact positions, enabling robots to achieve super-resolution in force and location sensing—a critical advance for dexterous manipulation. More recently, Xie tackles the challenging Embodied Complex-Question Answering task (2025, 1 citation), where robots must parse intricate, abstract human queries and generate plans grounded in visual environments. Her work on visual environment-interactive planning addresses a core bottleneck in embodied AI: bridging high-level language understanding with low-level sensorimotor control. By integrating tactile super-resolution with interactive planning, Xie is pioneering systems that perceive and act with human-like nuance. Her research, though early in citation impact, signals a promising trajectory toward robots that learn from both touch and context—a dual focus that positions her as a key voice in next-generation embodied intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2