Papers
20
Total Citations
312
H-Index
10
About
Konstantinos Tsiakas is a leading researcher at the intersection of socially-assistive robotics, human-robot interaction, and adaptive training systems. His work focuses on developing intelligent frameworks that enable robots to personalize their behavior in real-time, particularly for cognitive and physical rehabilitation. Tsiakas’s most influential paper, “Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive Training” (79 citations), established a novel approach to using user engagement cues—such as facial expressions and body postures—as feedback signals for robot adaptation. He has pioneered the application of Interactive Reinforcement Learning in robot-assisted therapy, allowing robots to learn from human corrections during training sessions. His comprehensive taxonomy of robot-assisted training (21 citations) remains a foundational reference in the field. Tsiakas has also explored multimodal sensing, including EEG-based task performance prediction and nonverbal personality expression in robots. His work on assistive technologies for multiple sclerosis rehabilitation (18 citations) demonstrates his commitment to clinically impactful applications. With over 240 total citations, Tsiakas continues to shape how robots can serve as personalized, adaptive partners in healthcare, education, and vocational training.
Research Focus
Key Achievements
Top Papers
- 1
- 2Adaptive Robot Assisted Therapy Using Interactive Reinforcement Learning27 citations · 2016
- 3A Taxonomy in Robot-Assisted Training: Current Trends, Needs and Challenges21 citations · 2018
- 4Grounding the meaning of words through vision and interactive gameplay19 citations · 2015
- 5
- 6
- 7Towards predicting task performance from EEG signals17 citations · 2017
- 8
- 9Monitoring task engagement using facial expressions and body postures16 citations · 2018
- 10