Papers
2
Total Citations
36
H-Index
2
About
Shih-Chih Chen is a leading researcher at the intersection of human-robot interaction and artificial intelligence, with a particular focus on how consumers perceive and engage with service robots. His work masterfully bridges psychological theory with cutting-edge technology, exploring both the linear and curvilinear effects of robot anthropomorphism on user acceptance. In his highly cited 2023 study, Chen demonstrated that the relationship between a robot’s human-like appearance and consumer usage intention is more complex than previously thought, revealing that perceived risk plays a crucial mediating role—a finding that has garnered 29 citations and reshaped design strategies in service robotics. More recently, Chen has advanced the field of robotic perception by investigating how machine learning techniques, such as Convolutional Neural Networks and Reinforcement Learning, can dramatically improve object recognition and decision-making in autonomous systems. His 2024 work on sensor fusion and robotic cognition highlights his commitment to creating more intuitive and capable machines. Through his rigorous empirical research and theoretical contributions, Chen continues to influence both academic discourse and practical applications in human-centered AI and service automation.
Research Focus
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