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.

### Faculty

##### Alex Cloninger

Research Areas

Mathematics of Information, Data, and SignalsMathematical Modeling and Applied Analysis

Statistics

Geometric Data Analysis

Machine Learning

Applied Harmonic Analysis

##### Ioana Dumitriu

Research Areas

Mathematics of Information, Data, and SignalsDiscrete Probability

Stochastic Eigenanalysis

Scientific Computing

Numerical Linear Algebra

Applications in Machine Learning

##### Rayan Saab

Research Areas

Mathematics of Information, Data, and SignalsMathematics of Data

Information Theory

Applied and Computational Harmonic Analysis

Signal Processing