Chih‐Yu Chen

About

Chih-Yu Chen is a researcher at the forefront of educational technology and computational intelligence (CI), with a focus on human-machine co-learning environments. Their work centers on developing intelligent systems that bridge the gap between students and machines, particularly through transformer-based architectures and genetic algorithms. Chen’s most notable contribution is the "Transformer-Based Semantic SBERT Robot with CI Mechanism," a 2024 paper that has already garnered 6 citations. This work introduces a semantic robot designed for collaborative learning among teachers, teaching assistants, and students, leveraging attention ontology to enhance educational outcomes. Additionally, Chen’s 2023 paper on a "Genetic Assessment Agent for High-School Student and Machine Co-Learning Model" (4 citations) demonstrates a practical application of CI in education, involving the IEEE CIS High School Outreach subcommittee to bring computational intelligence experiences to young learners. By integrating advanced AI techniques with pedagogical frameworks, Chen is shaping the future of interactive learning, making complex CI concepts accessible and engaging for students. Their research not only advances technical methodologies but also fosters inclusive, co-learning ecosystems.

Research Focus

Key Achievements

Top Papers

1. 1
   Transformer-Based Semantic SBERT Robot with CI Mechanism for Students and Machine Co-Learning

   6 citations · 2024
2. 2
   Genetic Assessment Agent for High-School Student and Machine Co-Learning Model Construction on Computational Intelligence Experience

   4 citations · 2023

Key Collaborators

Contact & Links