Teaching

My teaching philosophy centers on making AI and data science accessible to all, especially minorities and marginalized populations. I help bridge technical rigor with ethical responsibility through hands-on projects that tackles real-world problems. I create inclusive learning environments where diverse perspectives meet and strengthen our collective understanding of technology's impact on society. Through mentorship and critical thinking, I help students become not just skilled practitioners who know "how to", but thoughtful leaders who ask "should we?", and recognize that ethical AI development requires both technical excellence and social responsibility.

2026

Instructor | Python Vibe Coding Tutorial: AI Bias in Text-to-Image Generative AI

UBC Extended Learning Course: Programming in Python for Data Science

Spring2026 | Delivered a lecture about responsible genAI use, demonstrated by building a bias evaluation tool for text-to-image models in Cursor, demonstrating Python best practices and the power of system prompts.

2025

Lecturer | DSCI 522: Reproducible and Trustworthy Data Science Workflows

University of British Columbia Master of Data Science Program (UBC MDS)

Fall 2025 | Teaching reproducible and trustworthy data science workflows, focusing on reproducibility, project management, version control, Docker containers, and automated workflows.

Lecturer | DSCI 571: Supervised Machine Learning

University of British Columbia Master of Data Science Program (UBC MDS)

Fall 2025 | Teaching supervised machine learning, including topics likemulti-class classification, logistic regression, decision trees, random forests, and SVM.

Tutorial Instructor | AI Tools Playground: Responsible Use of Generative AI

University of British Columbia

Fall 2025 | Designed and taught a comprehensive AI literacy workshop for graduate students, covering UBC-approved AI platforms, advanced coding assistance (GitHub Copilot, Cursor IDE), LLM evaluation, text-to-image generation, and prompt engineering. Emphasized "AI as copilot, not autopilot" philosophy, teaching critical evaluation of AI outputs, and responsible AI usage including privacy, bias detection, and ethical considerations.

Instructor | Data Science for Kids Summer Camp

Vancouver Independent School of Science and Technology (VISST)

Summer 2025 | Designed and taught an introduction to data science workshop for kids, making AI (Anthropic Claude) and data science accessible and fun for young learners. Topics included Claude AI–assisted programming; introduction to programming (if–else conditions, for loops); statistical inference (sampling, bootstrapping); data visualization and analysis; k-nearest neighbors; and AI ethics.

Mentor | Data Science for Girls Summer Camp

University of British Columbia

Summer 2025 | Mentored participants in a summer camp focused on introducing girls to data science, fostering diversity and inclusion in STEM fields through hands-on learning experiences.

Guest Lecturer

Vancouver Independent School of Science and Technology (VISST)

Spring 2025 | Taught a lecture about AI bias and animal welfare focusing on "How AI Sees Farm Animals: Whose Stories Are Lost?" Engaged high school students in discussions about technology ethics and representation bias in AI systems.

Tutorial Instructor | Linux Command Using Amazon Web Services (AWS) EC2

University of British Columbia Master of Data Science Program (UBC MDS)

Spring 2025 | 40 students | Designed and taught a hands-on AWS EC2 tutorial where participants learned to set up EC2 instances, use SSH with key-based authentication, and master Linux commands through a creative rescue mission. Students helped free "Ollie the Otter" from a digital dungeon using Linux commands, turning technical concepts into a memorable adventure.

Teaching Assistant | DSCI 525: Web and Cloud Computing