The mathematics of information, data, and signals is a multifaceted field that encompasses the development and application of mathematics for data acquisition, analysis, interpretation, and manipulation. Beyond its theoretical importance, this discipline has significant practical applications. This stems from the fact that data can emerge from a variety of sources such as imagery, acoustics, structured and random networks, and spatial or temporal sensors, or it can be sampled from unknown distributions. To address the resulting theoretical and computational challenges, a range of mathematical tools from various areas are needed. These include probability and statistics, random matrix theory, graph theory, harmonic analysis, signal processing, geometry, linear algebra, and optimization, to name a few.
Research AreasMathematics of Information, Data, and Signals
Numerical Linear Algebra
Applications in Machine Learning