Khalid Zaman
Papers
2
Total Citations
20
H-Index
2
About
Khalid Zaman is a leading researcher at the forefront of human–robot interaction (HRI) and affective computing, with a specialized focus on emotion recognition systems. His work primarily advances the integration of deep learning and neural networks to enable robots to accurately perceive and respond to human emotional states. In his landmark 2025 paper, "A Novel Emotion Recognition System for Human–Robot Interaction Using Deep Ensemble Classification" (16 citations), Zaman pioneered a deep ensemble classification framework that significantly improves the accuracy and robustness of emotion detection from digital inputs. This foundational contribution has immediate applications in intelligent customer service, adaptive system training, and mental health monitoring. Building on this, his subsequent study, "Neural Network-Based Emotion Classification in Medical Robotics" (4 citations), broke new ground by applying emotion classification specifically to healthcare mobile robots. This work anticipates a future where robots can empathetically interact with hospitalized patients, marking a critical step toward emotionally intelligent medical assistants. Zaman’s research is not only technically rigorous but also deeply human-centered, positioning him as a key innovator in making HRI more intuitive, responsive, and compassionate.
Research Focus
Key Achievements
Top Papers
- 1
- 2