Papers
14
Total Citations
231
H-Index
7
About
Sado Fatai is a researcher whose work sits at the intersection of robotics, artificial intelligence, and rehabilitation engineering. His research focuses on three core areas: explainable AI for autonomous agents and robots, robotic-assisted rehabilitation, and human-robot interaction. Fatai's most influential contribution, a comprehensive review of explainable goal-driven agents and robots (2022, 66 citations), addresses critical trust and transparency challenges in AI systems, particularly those relying on deep learning architectures—a timely and widely recognized contribution to the field. His work on assist-as-needed (AAN) rehabilitation strategies has been equally impactful, with multiple papers exploring adaptive control frameworks that personalize robotic assistance based on a patient's real-time functional ability, fostering motor recovery in neurologically impaired individuals (2019, 53 citations). His research on exoskeleton control for workplace injury prevention further demonstrates a commitment to practical human welfare applications. Across his body of work, Fatai consistently bridges theoretical AI design with real-world assistive technology, making his research valuable for engineers, clinicians, and AI practitioners alike. His growing citation record underscores his emerging influence in responsible robotics and intelligent rehabilitation systems.
Research Focus
Key Achievements
Top Papers
- 1Explainable Goal-driven Agents and Robots - A Comprehensive Review66 citations · 2022
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- 4Emotion detection from thermal facial imprint based on GLCM features13 citations · 2016
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- 9Explainable Goal-Driven Agents and Robots -- A Comprehensive Review6 citations · 2020
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