Mohaiad Elbasheer
Papers
1
Total Citations
20
H-Index
1
About
Mohaiad Elbasheer is a forward-thinking researcher at the intersection of digital twin technology and human-robot interaction (HRI). His work explores how digital twins can reshape collaborative systems, particularly in human-robot dyads, where virtual replicas enhance real-time coordination, safety, and adaptability. In his most cited paper, “Shaping the role of the digital twins for human‐robot dyad: Connotations, scenarios, and future perspectives” (2022, 20 citations), Elbasheer provides a comprehensive review of digital twin design and application in HRI, clarifying how these virtual models can bridge the gap between human intent and robotic action. This work has become a foundational reference for researchers seeking to integrate digital twins into collaborative robotics, offering both conceptual clarity and practical scenarios. Elbasheer’s contributions are especially valuable as the field moves toward more intuitive, responsive human-robot teams. By mapping out future directions and critical design considerations, he has helped define a nascent but rapidly growing research area. His work continues to influence scholars and engineers working on smart manufacturing, assistive robotics, and autonomous systems, positioning him as a key voice in the evolution of human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1