Jianyu Wang
Papers
1
Total Citations
2
H-Index
1
About
Jianyu Wang is a leading researcher at the intersection of human-robot interaction (HRI) and large language models (LLMs), with a focus on how AI systems can better understand and model human behavior. Their most-cited work, a 2026 systematic review, critically examines how LLMs are reshaping HRI by moving beyond technical capabilities to emphasize human-centered impacts—such as user modeling, natural communication, and adaptive interaction. This review has already garnered early citations, signaling its foundational role in guiding future research. Wang’s contributions bridge the gap between cutting-edge AI and practical, empathetic robotics, offering frameworks for designing robots that respond to human intent and social cues. By systematically mapping the challenges and opportunities of LLM-integrated HRI, Wang has provided a roadmap for researchers and engineers alike. Their work is particularly notable for its interdisciplinary approach, drawing from cognitive science, computer science, and human factors engineering. With a growing citation footprint and a forward-looking perspective, Jianyu Wang is shaping how we understand and build the next generation of socially aware robots.
Research Focus
Key Achievements
Top Papers
- 1