Papers
52
Total Citations
625
H-Index
14
About
Chu Kiong Loo is a prominent researcher whose work sits at the dynamic intersection of artificial intelligence, robotics, and human-robot interaction. His research spans explainable AI, social robotics, autonomous agents, and assistive technologies, with a particular focus on making intelligent systems more transparent, adaptive, and beneficial to human users. Among his most influential contributions is a comprehensive review of explainable goal-driven agents and robots (2022, 66 citations), addressing the critical challenge of trust in AI systems built on opaque deep learning architectures. His extensive work on social robots for human-robot interaction (2014, 62 citations) has shaped methodological standards in the field, while his research on personalized robotic interventions for autistic children (2020, 52 citations) demonstrates his commitment to socially impactful applications. His development of personality-affected emotional models for robots (2017, 49 citations) further highlights his sophisticated approach to naturalistic human-robot collaboration. Loo's contributions extend into continual learning, SLAM-based navigation, imitation learning, and wearable rehabilitation exoskeletons, reflecting remarkable breadth. His body of work, accumulating hundreds of citations across more than a decade, marks him as a significant and versatile voice in intelligent robotics research.
Research Focus
Key Achievements
Top Papers
- 1Explainable Goal-driven Agents and Robots - A Comprehensive Review66 citations · 2022
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- 6Behavior recognition for humanoid robots using long short-term memory28 citations · 2016
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- 8Imitation learning for daily exercise support with robot partner19 citations · 2015
- 9SLAMM: Visual monocular SLAM with continuous mapping using multiple maps19 citations · 2018
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