Teaching

My central goal as an educator is to help students develop intellectual independence: the ability to learn on their own, transfer ideas to unfamiliar situations, and approach difficult problems with curiosity rather than fear.

I begin with problems that make a concept necessary, develop the theory needed to solve them, and then return to the original problem to examine why the solution works and where it may fail. I consider understanding genuine when a student can explain a concept in their own words, create an analogy they were not given, and apply the idea in a setting the course did not cover.

I give students room to revise unsuccessful solutions and gradually remove scaffolding as their confidence grows. Generative AI can support this process, but conceptual decisions, verification, and explanation must remain the student's responsibility. My goal is calibrated trust and a classroom in which students learn to question evidence—including AI output, research papers, and instructors—with curiosity and judgment.

Based on my teaching experience, I am prepared to contribute to courses in introductory programming, algorithms and data structures, databases, web application development, and computer organization. My research background also positions me to develop or support courses in natural language processing, machine learning, and trustworthy AI evaluation.