Practice-based instruction for undergraduates in data analytics and related majors.
Fall 2023 · Spring 2025 · Fall 2025 · Spring 2026
Led six practice-based lab sections across four semesters. Reinforced foundational data science concepts through R exercises and live coding; graded homework, exams, and team projects; and held office hours. Student teaching evaluations exceeded 4.0 out of 5.0 in every semester.
Selected invited sessions across graduate, undergraduate, and research-training settings.
Understanding Large Language Models: Theory and Practice (IST 700)
Introduced how mechanistic interpretability can explain internal representations of large language models, using sparse autoencoders as a central example.
Understanding Large Language Models: Theory and Practice (IST 700)
Explained how attention represents contextual relationships, connecting conceptual foundations with a hands-on implementation.
Research Experiences for Undergraduates (REU)
Introduced the research process from research questions and data collection through analytical design, interpretation, and broader implications.
Influencers in Network Social Media (IST 400)
Introduced computational text analysis and topic modeling for studying social media discourse, with an applied Twitter data demonstration in R.