Papers

1

Total Citations

6

H-Index

1

About

Yutao Yue is a leading researcher at the intersection of embodied perception, natural language processing, and 3D sensing technologies. His primary research areas include multimodal AI, 4D millimeter-wave radar perception, and human-robot interaction, with a focus on bridging language and physical environments for intelligent vehicles and autonomous systems. Yue’s most notable contribution is the introduction of Talk2Radar, a pioneering framework that enables natural language-driven 3D referring expression comprehension using 4D mmWave radar data. This work, published in 2025 and already garnering 6 citations, addresses a critical gap in the field: while vision-based perception has advanced rapidly, radar-based 3D modeling for interactive understanding has remained underexplored. By integrating linguistic prompts with radar point clouds, Yue’s research empowers robots and vehicles to interpret complex spatial queries—such as “the car behind the red truck”—with high precision, even in adverse weather conditions where cameras fail. His work has significant implications for autonomous driving, assistive robotics, and smart infrastructure. Yue’s achievements highlight his commitment to pushing the boundaries of multimodal perception, making him a rising figure in AI-driven embodied intelligence.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Talk2Radar: Bridging Natural Language with 4D mmWave Radar for 3D Referring Expression Comprehension
6 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Artificial Intelligence in Medicine (Canada)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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