Chaudhary Muhammad Aqdus Ilyas

Papers

Total Citations

H-Index

About

Chaudhary Muhammad Aqdus Ilyas is a researcher at the forefront of human-robot interaction (HRI), specializing in affective computing and assistive robotics. His work uniquely bridges deep learning with rehabilitation, particularly for vulnerable populations. Ilyas’s most cited paper (32 citations) introduces a novel model for emotion recognition that fuses upper body movements with facial expressions, addressing a critical gap in HRI by moving beyond face-only analysis. He further advanced the field by teaching the Pepper robot to recognize emotions in Traumatic Brain Injured (TBI) patients using deep neural networks (11 citations), a pioneering application for non-intrusive, robot-assisted therapy. His research on deep transfer learning for cognitive and physical rehabilitation (7 citations) demonstrates how pre-trained models can adapt to patient-specific needs, reducing data requirements while improving robot responsiveness. Ilyas’s contributions are notable for their real-world impact—enhancing robot empathy in clinical settings—and for pushing the boundaries of multimodal emotion sensing. His work is essential reading for students and researchers interested in socially assistive robotics, deep learning in healthcare, and inclusive HRI design.