Close Menu

M.S. in Applied Mathematics with a Specialization in Discrete Computation & Optimization

The Discrete Computation & Optimization specialization is designed to train students in the fundamental mathematical foundations of Graph Theory, Optimization, and Algebra that lead to the latest methodologies and algorithms in discrete models, network optimization, and solutions of polynomial systems. Students who take this specialization will be ready for research in discrete mathematics, statistical models, optimization, and theoretical computer science, or for consultancy-based careers in related industries.

Required to take at least three of the following five courses:

  • Math 535 Optimization I
  • Math 530 Applied and Computational Algebra
  • Math 553 Discrete Math I
  • Math 554 Discrete Math II
  • Math 569 Statistical Learning

Remaining Elective courses to be chosen in consultation with the academic advisor, or from the following list or any unused core/ required courses listed above:

  • Math 430 Applied Algebra
  • Math 454 Graph Theory and Applications (No credit for Math 454 if Math 553 already taken)

Math 542 Stochastic Processes OR Math 481 Intro to Stochastic Processes Math 546 OR Math 446 Introduction to Time Series

  • Math 561 Algebraic and Geometric Methods in Statistics
  • Math 563 Mathematical Statistics OR Math 564 Applied Statistics
  • Math 565 Monte Carlo Methods in Finance
  • Math 567 Advanced Design of Experiments OR Math 483 Design and Analysis of Experiments
  • Math 574 Bayesian Computational Statistics
  • CS 535 Design and Analysis of Algorithms
  • CS 539 Game Theory: Algorithms and Applications
  • CS 579 Online Social Network Analysis
  • CS 583 Probabilistic Graphical Models
  • CS 584 Machine Learning
  • ECE 519 Coding for Reliable Communications
  • ECE 565 Computer Vision and Image Processing

PLANS OF STUDY

Here we present a few plans of study for the various options in the MS program. Note that Math 593, a required course, is not listed below under the plans of study as it is a zero credit course offered every semester.

A Sample Course Sequence for the Specialization in Discrete Computation and Optimization with Project:

Fall - Year 1

Math 577
Elective (Math 540 or Math 475)
Elective (Math 553 or Math 530)



3 credit hours
3 credit hours
3 credit hours

Spring - Year 1

Elective (Math 563 or Math 569)
Elective (Math 535 or Math 554)
Elective (Math, CS, or ECE course from list)



3 credit hours
3 credit hours
3 credit hours

Fall - Year 2

Math 522
Elective (Math 553 or Math 530)
Math 594 Project



3 credit hours
3 credit hours
2 credit hours

Spring - Year 2

Elective (Math 554 or Math 535 or Math 563 or Math 569)
Math 594 Project



3 credit hours
3 credit hours
Total  32 credit hours