Mouaad Oujabour
Papers
1
Total Citations
6
H-Index
1
About
Mouaad Oujabour is an emerging researcher at the intersection of affective computing and human-robot interaction, with a focused interest in enabling machines to perceive and respond to human emotional states. His most-cited work, "Multi-Face Emotion Detection for Effective Human-Robot Interaction" (2025), addresses a critical challenge in social robotics: the real-time, accurate recognition of emotions from multiple faces in dynamic environments. By developing robust multi-face detection algorithms, Oujabour’s research enhances the ability of robots to engage naturally with groups of people, moving beyond single-user scenarios. This contribution is foundational for applications in collaborative robotics, assistive technologies, and public-facing service robots. With 6 citations already in a short time, his work signals growing interest in scalable emotional AI. Oujabour’s research promises to make human-robot interaction more intuitive and empathetic, laying groundwork for robots that can read a room—literally. As his citation trajectory suggests, he is a rising voice in the drive to build socially aware autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Multi-Face Emotion Detection for Effective Human-Robot Interaction6 citations · 2025