Georgia Institute of Technology College of Sciences

Elementary combinatorial techniques used in discrete problem solving: counting methods, solving linear recurrences, graph and network models, related algorithms, and combinatorial designs.

The second of a two course sequence of faculty-directed independent research culminating in the writing of a senior thesis and its presentation.

The first of a two course sequence of faculty-directed independent research culminating in the writing of a senior thesis and its presentation.

An introduction to the Ito stochastic calculus and stochastic differential equations through a development of continuous-time martingales and Markov processes. (1st of two courses in sequence)

Case studies, visiting lecturers from financial institutions, student group projects of an advanced nature, and student reports, all centered around quantitative and computational finance. Crosslisted with ISYE and MGT 6785.

Introduction to large scale-system design to support computational finance for options, stocks, or other instruments.

An advanced course in Linear Algebra and applications.

Spectral theory of bounded and unbounded operators, major theorems of functional analysis, additional topics.

Fundamental methods of enumeration and asymptotic analysis, including the use of inclusion/exclusion, generating functions, and recurrence relations. Applications to strings over a finite alphabet and graphs.

Develops the probability basis requisite in modern statistical theories and stochastic processes. Topics of this course include measure and integration foundations of probability, distribution functions, convergence concepts, laws of large numbers and central limit theory. (1st of two courses)