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

Photo of Alex Cloninger
Alex Cloninger

Research Areas

Mathematics of Information, Data, and Signals

Mathematical Modeling and Applied Analysis

Statistics

Geometric Data Analysis

Machine Learning

Applied Harmonic Analysis

Photo of Ioana Dumitriu
Ioana Dumitriu

Research Areas

Mathematics of Information, Data, and Signals

Discrete Probability

Stochastic Eigenanalysis

Scientific Computing

Numerical Linear Algebra

Applications in Machine Learning

Photo of Rayan Saab
Rayan Saab

Research Areas

Mathematics of Information, Data, and Signals

Mathematics of Data

Information Theory

Applied and Computational Harmonic Analysis

Signal Processing

Additional Faculty

Photo of Todd Kemp
Todd Kemp

Research Areas

Probability Theory

Functional Analysis / Operator Theory

Mathematical Physics

Mathematics of Information, Data, and Signals