Manolis Vasileiadis
Papers
5
Total Citations
74
H-Index
4
About
Manolis Vasileiadis is a leading researcher at the intersection of human-robot interaction and assistive robotics, with a primary focus on developing intelligent service robots that can understand and respond to human behavior. His work centers on three key areas: robust human pose tracking, daily activity analysis, and adaptive robot behavior for elderly care. Vasileiadis made significant contributions through his development of robust human pose estimation algorithms for realistic service robot applications, achieving 21 citations for his work on tracking systems that maintain accuracy in uncontrolled, real-world environments. His most impactful paper (34 citations) explores how robotic agents can understand human behavior through daily activity analysis, laying groundwork for context-aware assistance. He has been instrumental in the RAMCIP project, demonstrating a complete framework for personal robotic assistants, and established a living lab infrastructure for monitoring activity needs in service robot applications. Notably, his research on adapting robot behavior based on user mood represents pioneering work in personalized support for patients with Mild Cognitive Impairment (MCI), showing how service robots can dynamically adjust their interactions to provide more empathetic, tailored assistance in home environments.
Research Focus
Key Achievements
Top Papers
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- 2Robust Human Pose Tracking For Realistic Service Robot Applications21 citations · 2017
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