Gergely Magyar
Papers
7
Total Citations
193
H-Index
6
About
Gergely Magyar is a leading researcher in social robotics, with a primary focus on emotion modelling and human-robot interaction (HRI). His most influential work, the 2018 review "Emotion Modelling for Social Robotics Applications" (135 citations), provides a foundational framework for integrating affective computing into robotic systems, enabling more natural and empathetic machine behaviour. Magyar has pioneered the concept of the "Affective Loop" (13 citations), an autonomous and adaptive tool for emotional HRI, and has advanced the Wizard of Oz methodology through cloud-based platforms, allowing robots to learn from human experimenters in real time. His applied research includes a socially-assistive robot that learns during interaction to prevent low back pain in children (12 citations), addressing a global health crisis that causes more disability than any other condition. Magyar also contributed to cloud-based robotic assistants for education, leveraging platforms like Google App Engine and Microsoft Azure. With over 190 total citations, his work bridges theoretical emotion modelling with practical, cloud-enabled HRI systems, making significant strides toward autonomous, socially-aware robots capable of adaptive, therapeutic, and educational support.
Research Focus
Key Achievements
Top Papers
- 1Emotion Modelling for Social Robotics Applications: A Review135 citations · 2018
- 2Comparison Study of Robotic Middleware for Robotic Applications18 citations · 2014
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- 7Cloud-based Wizard of Oz as a service2 citations · 2015