Min-Yuh Day

National Taipei University, Tamkang University

Papers

Total Citations

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About

Min-Yuh Day is a researcher whose work sits at the intersection of artificial intelligence, natural language processing, and human-computer interaction, with a particular focus on intelligent conversational systems and their real-world applications. His research has made meaningful contributions to the development of AI-powered chatbots and dialogue systems, exploring innovative approaches that combine both generative and retrieval-based models to create more responsive and emotionally intelligent conversational agents. Among his most recognized contributions is his work on AI customer service systems leveraging pre-trained language models for university admissions — a study that has garnered 11 citations and demonstrates the practical value of deploying advanced NLP technologies in institutional settings. Complementing this, his 2019 research on affective conversational robots introduced a hybrid dialogue framework aimed at improving the emotional responsiveness and user engagement of AI systems, reflecting a broader commitment to making AI interactions feel more natural and human-centered. Day's research speaks to a growing need for intelligent, context-aware systems that can serve users across educational and service-oriented domains. His work is particularly relevant for students and researchers interested in applied AI, dialogue systems, and the evolving role of machine learning in transforming how institutions interact with the people they serve.