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