Jianan Liu
Papers
1
Total Citations
6
H-Index
1
About
Jianan Liu is an emerging researcher at the forefront of autonomous systems perception, specializing in multimodal sensor fusion, 4D mmWave radar processing, and natural language-guided scene understanding. His most notable work, *Talk2Radar* (2025), represents a pioneering contribution to the field by bridging natural language processing with 4D mmWave radar technology for 3D referring expression comprehension — a capability critical for intelligent vehicles and robots that must interpret and respond to human prompts in complex environments. This work addresses a significant gap in embodied perception research, which has historically been dominated by vision-based approaches, by demonstrating that radar-based 3D modeling can achieve rich, language-driven object understanding. Already accumulating citations shortly after publication, Liu's research signals growing community interest in radar-centric perception as a robust complement to cameras and LiDAR, particularly in adverse weather conditions where vision fails. His contributions position him as a thoughtful innovator pushing the boundaries of how autonomous systems interpret both their physical surroundings and human intent, with implications spanning robotics, autonomous driving, and human-machine interaction research.
Research Focus
Key Achievements
Top Papers
- 1