Teaching
Teaching & Mentoring
As a Teaching Assistant at the Illinois Institute of Technology (since 2021) and TED University, Ankara (2019–2021), I have led recitations and graded for undergraduate mathematics courses ranging from calculus through complex analysis and computational mathematics. Since 2022, I have also mentored undergraduate mathematics students through the Directed Reading Program — Türkiye on nine-week summer reading projects in optimization, machine learning, and applied mathematics. I believe strong teaching and careful mentoring are inseparable from good research.
Teaching Assistant — Illinois Institute of Technology
Recitation and grading for undergraduate and graduate mathematics courses in the Department of Applied Mathematics, Fall 2021 – Spring 2026.
Undergraduate
- Calculus I
- Calculus II
- Multivariate and Vector Calculus
- Linear Algebra
- Differential Equations
- Complex Analysis
- Discrete Mathematics
- Computational Mathematics
Graduate
- Linear Optimization
- Regression
- Statistical Learning
- Time Series
- Mathematical Modeling
- Computational Algebraic Geometry
Teaching Assistant — TED University, Ankara
Recitation and grading for undergraduate mathematics courses in the Department of Mathematics, Fall 2019 – Spring 2021.
- Calculus of One Variable
- Multivariable Calculus
- Linear Algebra
- Differential Equations
Directed Reading Program — Türkiye
DRP Türkiye is an online program that pairs undergraduate mathematics students at universities in and around Türkiye with graduate-student and early-career mentors at institutions around the world. Each summer, mentor and mentee work through selected books or articles over nine intensive weeks: weekly meetings, a written report, and a presentation at a closing symposium.
I have mentored students through DRP since 2022, from a range of universities and backgrounds. I match the topic and difficulty to each student's background, aiming to stretch them on something they can actually finish. Recent projects:
How Robots Walk: An Introduction to Path and Motion Planning.
Fast and Fair? Exploring a Graph-Theoretic Approach to Large-Scale Political Redistricting.
Exceeding Human-Level Expertise: Deep Reinforcement Learning.
Report (in 2024 symposium proceedings, p. 192) · Presentation
Regression and Classification in Statistical Learning.
Beyond Constraints: Integer Programming.
Linear Programming Models and How to Solve Them.