The mathematics of information, data, and signals is a multifaceted field that includes data analysis, interpretation, and manipulation. Data can emerge from a variety of sources, such as imagery, acoustics, structured or random networks, and spatial or temporal sensors. To suitably process the data, a range of mathematical tools from various areas are needed. These include probability and statistics, random matrix theory, graph theory, harmonic analysis, signal processing theory, geometry, linear algebra, and optimization. Beyond its theoretical importance, this discipline also has significant practical applications.

### 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

### Additional Faculty

##### Todd Kemp

Research Areas

Probability TheoryFunctional Analysis / Operator Theory

Mathematical Physics

Mathematics of Information, Data, and Signals