TEACHING
This Semester (Spring 2008)

PREVIOUSLY TAUGHT COURSES

Here is a list of courses I have taught so far:

Bilkent University

A general overview of operations research, with selected applications from engineering and management systems, and interdisciplinary areas. The methodology of mathematical modeling and its relation to problems in industrial, commercial, and public systems. Introduction to linear programming: the simplex method, duality, sensitivity analysis, and related topics. Network models and project scheduling.

This course is designed to introduce the engineering students to economic and management concepts. Topics will include economic concepts such as; cash flow, interest rates, rate of return, demand supply relations, product pricing, taxes, inflation, and related subjects; and management analysis such as management layers, network analysis, project management via CPM/PERT networks, optimization concepts, linear programming, and decision analysis. The course also includes use of related software.

Introduction to methods of proof, sets and functions, metric spaces, functions on metric spaces, differential and integral equations, fundamentals of linear algebra.

Theory, algorithms, and computational aspects of linear programming. Formulation of problems as linear programs. Development of simplex algorithm, geometry of simplex method, duality theory, and economic interpretations. Sensitivity analysis. Variants of simplex method.

Local and global optima. Newton-type, quasi-Newton, and conjugate gradient methods for unconstrained optimization. Kuhn-Tucker theory and Lagrangean duality. Algorithms for linearly constrained optimization, including steepest ascent and reduced gradient methods with applications to linear and quadratic programming. Nonlinearly constrained optimization including penalty and barrier function methods, reduced and projected gradient methods, Lagrangean methods. Computer implementation.
Stony Brook University
A course intended to integrate first-semester Stony Brook freshmen into the university community and particularly into the College of Engineering and Applied Sciences. Special emphasis is placed on basic computing skills, internet access, and the programs, laboratories, and library of the college.

An introduction to graph theory and combinatorial analysis. The emphasis is on solving applied problems rather than on theorems and proofs. Techniques used in problem solving include generating functions, recurrence relations, and network flows. This course develops the type of mathematical thinking that is fundamental to computer science and operations research.

Theoretical and computational properties of discrete and nonlinear optimization problems: integer programming, including cutting plane and branch and bound algorithms, necessary and sufficient conditions for optimality of nonlinear programs, and performance of selected nonlinear programming algorithms. This course is offered as both MBA 544 and AMS 544.

The course is designed for second- and third-year graduate students with a strong foundation in linear algebra and analysis who wish to pursue research in applied mathematics. Varying topics from nonlinear programming and optimization to applied graph theory and applied combinatorics may be offered concurrently.

Cornell University
A course for Master of Engineering students that deals with applications and methodologies of dynamic programming, integer programming, and large-scale linear programming.

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