**Teaching**

__Undergraduate__

1.
**IND E 410 (Linear and Network Programming)**: This is the
first class in a three-class sequence in Operations Research for undergraduate
students in engineering. It covers topics such as the simplex method; linear
programming duality; sensitivity analysis; the dual simplex method; the
transportation simplex method; and minimum cost network flow, maximum flow,
minimum spanning tree, and shortest path problems.

2.
**IND E 411 (Stochastic Models and
Decision Analysis)**: This is the second class in the undergraduate Operations
Research sequence. It covers topics such as probabilistic decision trees;
expected value of perfect information; discrete-time, finite-state Markov
chains; continuous-time Markov chains; and queuing
models.

3.
**IND E 412 (Integer, Dynamic and
Non-linear Programming)**: This third class
in the Operations Research sequence covers topics such as deterministic and
stochastic dynamic programming; Lagrangian duality in
integer programming; branch-and-bound and other methods for integer
programming; gradient search and Newton's method for unconstrained, non-linear
optimization; and Karush-Kuhn-Tucker conditions for
constrained, non-linear optimization. If there is time, I sometimes also cover
two-person zero sum games in this class.

The textbook for the above sequence is "Introduction to
Operations Research" by Hillier and Lieberman.

__Graduate__

1.
****IND E 513 (Linear Optimization in Engineering)**: This class covers convex sets and functions; polyhedral
geometry; equivalence of extreme points and basic feasible solutions; simplex method; duality and Farkas
Lemmas; interior point methods; and minimum cost network flow problems. The
textbook for this class is "Introduction to Linear Optimization" by
Bertsimas and Tsitsiklis.

2.
**IND E 508 (Stochastic Processes
in Engineering)**: This class covers stochastic models
without relying on measure theory. It includes topics such as Poisson
processes; renewal processes; discrete-time and continuous-time Markov chains; and Martingales. The textbook is "Stochastic
Processes" by Ross.