Graduate/undergraduate ML support — lectures, review sessions, homework/project design, grading, and office hours.
Teaching assistant for four offerings; led reviews, graded exams/assignments, and mentored students on algorithm design and complexity analysis.
Undergraduate lecturer — classical AI search/logic and introductory neural networks with Python implementations.
Undergraduate lecturer — arrays, linked lists, stacks/queues, trees, heaps, and hashing with focus on implementation and complexity analysis.
Undergraduate lecturer — control flow, functions, modular design, debugging, and style for maintainable C/C++ programs.
