Tzong-Xiang Huang
Tokyo Metropolitan University, National University of Tainan
Papers
6
Total Citations
31
H-Index
4
About
Tzong-Xiang Huang is a researcher specializing in artificial intelligence, fuzzy logic systems, and human-robot interaction, with a particular focus on intelligent educational technologies. His work centers on the development of AI-FML (Artificial Intelligence-Fuzzy Markup Language) frameworks that integrate fuzzy logic, neural networks, and evolutionary computation to create adaptive learning environments where students and machines learn collaboratively. Huang's most notable contribution is the Robotic Assistant Agent (RAA) system, which leverages AIoT applications to support personalized student learning — his 2021 paper on this topic has garnered 9 citations and represents the culmination of years of foundational work. Earlier research explored ontology-based robotic agents for subjects ranging from mathematics to English language skills, demonstrating the versatility of his AI-FML approach across educational domains. His 2018 and 2019 studies, each attracting 6 and 5 citations respectively, established key groundwork in machine-human co-learning models, including a creative application to the strategic game of Go using genetic fuzzy markup language (GFML). Beyond education, Huang has extended his frameworks into brain-computer interfaces for emotional recognition in music applications and investigated how robot expressions influence student stress during assessments, showcasing a broad and humanistic vision for intelligent robotic systems.
Research Focus
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Top Papers
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