Amir Hossain Raj
Papers
5
Total Citations
69
H-Index
3
About
Amir Hossain Raj is an emerging robotics researcher whose work sits at the compelling intersection of social robot navigation, human-robot interaction, and autonomous locomotion. His most recognized contribution, VLM-Social-Nav (2024, 36 citations), introduced a pioneering framework that leverages Vision-Language Models to enable robots to make real-time, socially compliant navigation decisions in human-centered environments — a significant leap forward in bridging perceptual intelligence with ethical motion planning. Building on this, his work "Rethinking Social Robot Navigation" (17 citations) advocates for hybrid approaches that fuse the reliability of classical geometric systems with the adaptability of modern learning-based methods. His Social-LLaVA framework further extends this vision by incorporating human-language reasoning to help robots interpret unwritten social norms, not merely avoid obstacles. Beyond navigation, Raj has demonstrated breadth through his research on dexterous legged locomotion using deep reinforcement learning (12 citations) and the DARC framework for robust human-robot co-transportation under disturbances. Collectively accumulating nearly 70 citations within a single year, Raj's rapidly growing body of work positions him as a promising voice in designing robots that are not only capable, but genuinely people-aware.
Research Focus
Key Achievements
Top Papers
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- 2Rethinking Social Robot Navigation: Leveraging the Best of Two Worlds17 citations · 2024
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