Md Khurram Monir Rabby
Papers
3
Total Citations
32
H-Index
3
About
Md Khurram Monir Rabby is a researcher at the forefront of human–robot collaboration (HRC), focusing on how robots can intelligently adapt to and earn the trust of human partners. His work addresses two critical challenges in HRC: adjustable autonomy and trust modeling. In his most-cited paper (14 citations), he proposed a learning-based framework where a robot uses reinforcement learning guided by human rewards to dynamically adjust its autonomy level in unknown workspaces—a key step toward fluid, safe teamwork. His second major contribution (13 citations) introduced a time-driven, performance-aware mathematical model of trust that accounts for both human and robot performance, providing a foundation for more reliable human-robot interaction. Most recently, he extended this trust model to multi-robot settings (5 citations), incorporating physical and cognitive human constraints. Together, these works form a cohesive research program that bridges machine learning, human factors, and control theory, earning Rabby recognition as a rising voice in the design of adaptive, trustworthy robotic teammates.
Research Focus
Key Achievements
Top Papers
- 1A Learning-Based Adjustable Autonomy Framework for Human–Robot Collaboration14 citations · 2022
- 2Modeling of Trust Within a Human-Robot Collaboration Framework13 citations · 2020
- 3