Teaching Philosophy

I believe students learn best when they can see, build, and experiment with the ideas they are learning. My teaching emphasizes active, hands-on learning—integrating coding exercises, visual explanations, and term-long projects that connect theory to coherent systems. I have taught across the full academic spectrum, from first-generation and working students to advanced learners, using transparent course organization, scaffolded assignments, and equitable support.

Download Teaching Statement (PDF)

Graduate Teaching Assistant

Supporting instruction in algorithmic reasoning, machine learning, and AI courses.

Lecturer (Independent Instruction)

Designed and delivered undergraduate courses in programming, databases, and AI.