Bahram Salamat Ravandi
Papers
4
Total Citations
19
H-Index
2
About
Bahram Salamat Ravandi is a leading researcher at the intersection of human-robot interaction, cognitive training, and gamification. His work focuses on designing companion social robots that can deliver personalized, engaging interventions—particularly in healthcare and assistive technology. Ravandi’s major contributions include pioneering the use of socially assistive robots (SARs) to facilitate cognitive training, as demonstrated in his highly cited 2023 study on gamified visuospatial memory tasks, where a robot provided real-time feedback to enhance user performance. He has also advanced the field through a comprehensive scoping review on deep learning approaches for detecting user engagement in human-robot interaction (2025, 7 citations), establishing a critical framework for future research. His comparative analysis of feedback types in companion robots (2025) further clarifies how task versus social engagement can be optimized. With a growing citation impact, Ravandi’s work is shaping the next generation of adaptive, socially aware robots capable of supporting mental health and cognitive well-being. His research is essential reading for anyone interested in the future of personalized, gamified human-robot interaction.
Research Focus
Key Achievements
Top Papers
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