Data Science
Data Science has its foundations in mathematics, statistics, and computer science. The Department of Mathematics, and within it the Center for Approximation and Mathematical Data Analytics (CAMDA), supports a diverse program offering strong training in the mathematical core of Data Science including approximation theory, compressed sensing, learning theory, numerical analysis, optimal recovery, signal/image processing, as well as targeted application areas. Several of its faculty are also affiliates with the Texas A&M Institute of Data Science (TAMIDS). Ongoing research is supported by grants from the National Science Foundation and the Department of Defense.
Regular events 
Faculty

Andrea Bonito
Professor of Mathematics
Adaptive Methods, Geometric PDEs, Non Newtonian Fluid Dynamics, and High Dimensional Approximation Methods.

Ronald DeVore
Koss Professor of Mathematics, Distinguished Professor
Approximation Theory, Numerical Analysis, Data Assimilation, and Deep Learning.

Yalchin Efendiev
Professor of Mathematics, Mobil Chair in Computational Science
Numerical Analysis, Multiscale Finite Element Method, and Flow in Porous Media.

Simon Foucart
Professor of Mathematics
Compressive Sensing, Approximation Theory, Computational Mathematics, and Bioinformatics.

William Johnson
A.G. and M.E. Owen Chair, Distinguished Professor
Geometry of Discrete Metric Spaces and Metric Embeddings.

Peter Kuchment
Distinguished Professor of Mathematics
PDEs, Mathematical Physics, Computerized Tomography, Geometric Analysis, and Imaging Science.

Matthias Maier
Assistant Professor of Mathematics
Multiscale Effects in Optical Metamaterials, Multiscale Methods, Computational Fluid Dynamics, Finite Element Methods and Software.

Francis Narcowich
Professor of Mathematics
Radial Basis Functions, Approximation and Interpolation on Spheres, ScatteredData Surface Fitting, Neural Networks, and Wavelets.

Grigoris Paouris
Professor of Mathematics
Functional Analysis.

Guergana Petrova
Professor of Mathematics
Numerical Methods for PDEs, and Approximation Theory, Wavelets.

Thomas Schlumprecht
Professor of Mathematics
Functional Analysis, Banach spaces, Probability Theory, Convex Geometry, and Mathematics in Finance.

Jonathan Siegel
Assistant Professor
Approximation theory, approximation theory of neural networks, and its application to numerical PDEs.

Peter Stiller
Professor of Mathematics
Functorial Data Clustering Methods, Geometry of Injective Envelopes and Spanning Complexes, Topological Data Analysis.

Edriss Titi
Arthur Owen Professor of Mathematics
Nonlinear PDEs, Atmospheric and Oceanic Dynamics, Data Assimilation, and Control Theory.

Minh Tran
Assitant Professor
Stochastic Control and Machine Learning

Stephan Wojtowytsch
Assitant Professor
Applied analysis, machine learning, partial differential equations and the calculus of variations.