Xiaohao Cai
Papers
1
Total Citations
6
H-Index
1
About
Xiaohao Cai is a leading researcher at the intersection of embodied perception, natural language processing, and 3D sensing technologies. His primary research areas include multimodal sensor fusion, referring expression comprehension, and the integration of language with non-visual perception systems. Cai’s most notable contribution is his pioneering work on bridging natural language with 4D millimeter-wave radar, exemplified by the highly cited paper “Talk2Radar: Bridging Natural Language with 4D mmWave Radar for 3D Referring Expression Comprehension” (2025, 6 citations). This work addresses a critical gap in embodied AI by extending language-guided object understanding beyond traditional vision-based sensors to radar-based 3D modeling, enabling more robust perception for intelligent vehicles and robots in challenging environments. By tackling the underexplored domain of radar-language interaction, Cai has opened new pathways for comprehensive environmental understanding, directly impacting autonomous navigation and human-robot interaction. His research demonstrates how language can serve as a universal interface across diverse sensing modalities, pushing the boundaries of what intelligent systems can perceive and comprehend in response to natural language prompts.
Research Focus
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Top Papers
- 1