The National Science Foundation has identified the field of analyzing information in high dimensional data sets as an Area of National Need.
Applications of Mathematics

From the era of Newton, fluid dynamics has been the Queen of Applied Mathematics.   While this area is still of central importance, a new era of applications has emerged with high dimensional data and its analysis becoming the center of attention.

M435 Projects in Applied Mathematics

This course deals with the notion of mathematical modeling and the notion of added value.

M532 Mathematical Modeling of Large Data Sets (Spring 2016)

This course is intended for advanced students with solid backgrounds in linear algebra who are interested in the mathematical analysis of large data sets.

M633 Seminar in Industrial and Applied Mathematics

This course is intended for advanced students seeking to explore the power of mathematics applied to real world problems.  Previous editions have included working with SIEMENS on failure prediction, Hewlett Packard on signature recognition in images.

M676 Topological Data Analysis (Special Topics Course)

This course concerns geometry, topology and algebra with a view towards data analysis.
M510-11, M620-621 Optimization and Advanced Optimization

Techniques in optimization are extremely useful for characterizing patterns in data.  The singular value decomposition is an example of an optimization problem where the solution is in closed form.  Linear programming is a useful tool for constructing sparse representations of patterns. Nonlinear programming can reveal relationships in data.  Convex optimization allows one to find low-rank approximations in a general setting.