Here is a list of courses I have taught or TA-ed as a PhD student at Cornell. Student evaluations are available upon request.

ORIE 6300 - Mathematical Programming (Fall 2018, Fall 2021)

PhD-level introduction to theory of optimization. Covers fundamentals of convex analysis, linear and conic programming duality, optimality conditions and first-order methods.

Role: TA - Section Size: 40

ORIE 3310 - Optimization II (Spring 2019)

Junior-level optimization modeling class, spanning linear programming for network flows, integer programming and linear programming relaxations, and applications.

Role: TA - Section Size: 40

Math 112 - Contemporary Mathematics (Fall 2019)

Cayuga Prison Educations's intro to mathematics class. Covers logic, sets, basic geometry and trigonometry, discrete probability and intro to statistics using the normal distribution.

Role: Instructor - Class Size: 15

ORIE 4740 - Intro to Statistical Data Mining (Spring 2020)

Senior-level data science class. Covers linear and logistic regression, cross-validation and bootstrapping, model selection and regularization, decision trees, unsupervised learning, dimensionality reduction (PCA) and support vector machines.

Role: Lead TA - Section Size: 75

ORIE 3300 - Intro to Linear Programming (Fall 2020)

Junior-level optimization class. Covers LP modeling, LPs in standard forms, the simplex + revised simplex algorithms, dealing with degeneracy & cycling, elementary convex geometry, duality theory.

Role: Lead TA - Section Size: 35

ORIE 5270/6125 - Big Data Technologies (Spring 2021, Spring 2022)

MEng/PhD level course on computational and mathematical skills useful for data scientists. Topics cover UNIX shell, regular expressions, version control, data structures and algorithms, parallel computing, working with databases, and an overview of machine learning and optimization algorithms.

Role: Instructor - Class size: 50 (in 2021), 120 (in 2022).