Masood Mehmood Khan
Papers
6
Total Citations
145
H-Index
5
About
Masood Mehmood Khan is a pioneering researcher at the intersection of affective computing, robotics, and explainable artificial intelligence. His work centers on enabling machines—particularly sociable robots—to perceive, interpret, and express human emotions with unprecedented realism. Khan’s foundational contribution is the use of infrared thermography for automated facial expression classification and affect interpretation, demonstrating that facial skin temperature variations can reliably indicate emotional states. This work, with 76 citations, addresses critical limitations of vision-based systems, such as varying lighting and occlusion. He further advanced dynamic affect assessment, achieving 32 citations, to support clinical diagnostics and human-robot interaction. Khan’s engineering ingenuity is evident in his design of a single-actuator, multiloop eyeball mechanism for lightweight, agile robotic heads, and in his closed-loop Petri Net models that enable robotic faces to exhibit and maintain human-like expressions. More recently, he has led the development of Accountable and Explainable AI (AXAI) frameworks, integrating transparency into real-time affective state assessment modules. His research not only deepens our understanding of emotion display rules but also sets a benchmark for building trustworthy, emotionally intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 5Design of a Single Cam Single Actuator Multiloop Eyeball Mechanism6 citations · 2018
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