Rin-Pin Chang
Papers
2
Total Citations
11
H-Index
2
About
Rin-Pin Chang is a pioneering researcher at the intersection of computational intelligence, AI education, and the Internet of Things (AIoT). Their work centers on developing intelligent robotic assistant agents that enable co-learning between students and machines, particularly through the innovative AI-FML (Artificial Intelligence – Fuzzy Markup Language) framework. This framework integrates fuzzy logic, neural networks, and evolutionary computation to create adaptive, human-centric learning environments. Chang’s most-cited paper, "Robotic Assistant Agent for Student and Machine Co-Learning on AI-FML Practice with AIoT Application" (2021, 9 citations), introduces a Robotic Assistant Agent (RAA) that facilitates hands-on AI practice for pre-university students, bridging theoretical concepts with real-world AIoT applications. A subsequent study (2023) further refines this experiential learning model, demonstrating how computational intelligence can democratize AI education. Chang’s contributions are notable for advancing accessible, interactive AI learning tools that empower young learners to engage with complex technologies. Their work holds significant impact for educators, engineers, and researchers seeking to integrate AI literacy into curricula, with citation growth signaling growing influence in the field of intelligent educational systems.
Research Focus
Key Achievements
Top Papers
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