Papers
32
Total Citations
802
H-Index
11
About
Maria Kyrarini is a dynamic robotics researcher whose work sits at the intersection of assistive robotics, human-robot interaction, and artificial intelligence. Her most celebrated contribution, "A Survey of Robots in Healthcare" (2021), has garnered an impressive 371 citations, establishing her as a leading authority on the integration of robotic systems in medical and caregiving environments. Kyrarini's research spans both industrial and assistive applications: her 2018 study on robot learning of industrial assembly tasks through human demonstrations (126 citations) demonstrated how robots can adapt to the natural variability of human behavior in collaborative workplaces. A particularly compelling thread in her work is the development of assistive technologies for people with severe motor impairments, including tetraplegics. She has pioneered head gesture-based control interfaces, reinforcement learning approaches to robotic feeding assistance, and autonomous multi-sensory drinking assistants, collectively reflecting a deep commitment to improving quality of life for individuals with disabilities. Her research on cognitive load and fatigue assessment further bridges neuroscience and robotics, enhancing the safety of human-robot collaboration. With a growing citation record and broad interdisciplinary reach, Kyrarini represents an influential voice in the future of socially responsive robotics.
Research Focus
Key Achievements
Top Papers
- 1A Survey of Robots in Healthcare371 citations · 2021
- 2Robot learning of industrial assembly task via human demonstrations126 citations · 2018
- 3
- 4Autonomous Multi-Sensory Robotic Assistant for a Drinking Task34 citations · 2019
- 5Application of Reinforcement Learning to a Robotic Drinking Assistant28 citations · 2019
- 6
- 7A Taxonomy in Robot-Assisted Training: Current Trends, Needs and Challenges21 citations · 2018
- 8Head Gesture-based Control for Assistive Robots20 citations · 2018
- 9
- 10Towards a serious game based human-robot framework for fatigue assessment14 citations · 2020