Lue Fan
Papers
2
Total Citations
26
H-Index
2
About
Dr. Lue Fan is a leading researcher at the forefront of multimodal AI and robot vision, whose work is shaping how machines perceive and interact with the world. His primary contributions center on integrating vision and language—bridging the gap between raw visual data and semantic understanding to enable more intuitive, context-aware robotic systems. In his highly cited 2025 survey, "Multimodal Fusion and Vision–Language Models: A Survey for Robot Vision," Dr. Fan provides a comprehensive taxonomy of fusion techniques and vision-language models, synthesizing over 26 citations across related works. This seminal review has become an essential roadmap for researchers, clarifying the challenges and opportunities in combining modalities like images, text, and depth for tasks such as object manipulation and autonomous navigation. By systematically mapping the landscape of multimodal fusion, Dr. Fan’s work accelerates progress toward robots that can follow natural language commands and reason about their environments. His surveys and analyses are widely referenced, establishing him as a key voice in the push for more capable, human-aligned robotic perception.
Research Focus
Key Achievements
Top Papers
- 1Multimodal fusion and vision–language models: A survey for robot vision19 citations · 2025
- 2Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision7 citations · 2025