I study and build human-centered learning technologies, with a focus on large language
models, teacher-facing tools, and classroom experiences that balance rigor with usability.
I am a researcher and designer specializing in AI-driven educational technologies. My work focuses on developing large language model (LLM) applications that foster personalized learning environments and reimagine the role of teachers in AI-enhanced classrooms. I combine a background in industrial design with hands-on experience in user research, qualitative/quantitative analysis, and human-centered design.
I have contributed to projects that integrate LLMs into Computer Science Education, English as a Foreign Language (EFL) education, including designing student support systems, designing learning analytics dashboards, evaluating student–AI interactions, and developing teacher-support tools. My research has been published at HCI and NLP venues such as VL/HCC, UIST, L@S, LAK, NeurIPS, EMNLP, and LREC-COLING etc.
Current areas of work
AI-supported learning systems
Teacher dashboards and learning analytics for LLM-mediated classrooms
Human-centered evaluation of student and teacher interaction with AI
Proceedings of the 39th Annual ACM Symposium on User Interface Software and Technology (UIST '26), Detroit, MI, USA, 2026
AI programming tutors provide scalable support, yet lack the behavioral context human tutors rely on to adapt support to learners’ needs. We present TutorTrace, a dataset and behavioral abstraction...