Teaching

Assistant in Instruction, Princeton University

ORF 523: Convex and Conic Optimization (Course website)
(Spring 2019, Instructor: Amir Ali Ahmadi)
Convex analysis, Duality, Theorems of alternatives and infeasibility certificates, Semidefinite programming, Polynomial optimization, Sum of squares relaxation, Robust optimization, Computational complexity, Convex relaxations in combinatorial optimization.

MAT 375: Introduction to Graph Theory
(Spring 2018, Instructor: Maria Chudnovsky)
Connectivity, Spanning trees, Shortest paths, Euler’s theorem and Hamilton cycles, Bipartite graphs, Menger’s theorem, Digraphs and network flows, Matchings and Tutte’s theorem, Series-Parallel graphs, Planar graphs, Kuratowski’s theorem, Stable sets and cliques, Graph coloring.

ORF 363: Computing and Optimization (Course website)
(Fall 2017, Fall 2018, Fall 2019, Instructor: Amir Ali Ahmadi)
Unconstrained optimization, Convex optimization, Support vector machines, Gradient descent methods, Lyapunov functions in proving convergence, Nonlinear least squares and the Gauss-Newton algorithm, Conjugate direction methods, Leontief economy, Linear programming, Duality, Robust linear programming, Semidefinite programming and its relaxations for nonconvex optimization, Computational complexity theory, Limits of computation.

Teaching Assistant, Bogazici University

IE 598: Advanced Graph Theory
(Spring 2016, Instructor: Tinaz Ekim)
Perfect Graphs, Triangulated Graphs, Comparability Graphs, Permutation Graphs, Interval Graphs, Ramsey Theory for graphs.

IE 587: Optimal Control Theory
(Spring 2016, Instructor: Mustafa Akan)
The basics of dynamic optimization theory with applications in Economics, Calculus of Variations, Optimal Control Theory.

IE 456: Graph Algorithms and Applications
(Fall 2015, Instructor: Tinaz Ekim)
Basic notions in graphs, Eulerian and Hamiltonian graphs, Network Flows, Matching Theory, Coloring problems.

IE 440: Nonlinear Models in Operations Research
(Fall 2015, Instructor: Kuban Altinel)
Convexity, Unconstrained nonlinear optimization, Constrained nonlinear optimization, Neural networks, Supervised learning and back propagation algorithm, Unsupervised learning and self-organizing maps, Machine Learning, Support vector machines.

Student Assistant, Bogazici University

IE 456: Graph Algorithms and Applications
(Fall 2013, Fall 2014, Instructor: Tinaz Ekim)
Basic notions in graphs, Eulerian and Hamiltonian graphs, Network Flows, Matching Theory, Coloring problems.

MAT 162: Discrete Mathematics
(Spring 2013, Instructor: Ozlem Beyarslan)
Recursion, Counting, Discrete Probability, Advanced Counting Techniques, Relations, Graphs, Trees.