Applied Mathematics & Statistics

Degrees Offered

  • Master of Science (Applied Mathematics and Statistics)
  • Doctor of Philosophy (Applied Mathematics and Statistics)

Program Description

The Department of Applied Mathematics and Statistics (AMS) at Colorado School of Mines prepares the next generation of mathematical and statistical scientists to be leaders in a world driven by increasingly complex technology and challenges. Our department is at the forefront of research in mathematical and statistical methods that are used to address the opportunities and challenges of the future. The AMS department offers two graduate degrees: A Master of Science in Applied Mathematics and Statistics and a Doctor of Philosophy in Applied Mathematics and Statistics. The master's program is designed to prepare candidates for careers in industry or government or for further study at the PhD level. The PhD program is sufficiently flexible to prepare candidates for careers in industry, government and academia. A course of study leading to the PhD degree can be designed either for students who have completed a Master of Science degree or for students with a Bachelor of Science degree.

The AMS department is also involved in the curriculum of three different interdisciplinary master's degree programs: Data Science, Operations Research with Engineering, and Quantitative Biosciences and Engineering. Please view "Interdisciplinary Programs" for more information on these programs.

Research within AMS is conducted in the following areas:

Computational and Applied Mathematics

  • Deep Learning
  • Differential and Integral Equations
  • Dynamical Systems
  • Geophysical and Environmental Applications 
  • High Performance Scientific Computing
  • Mathematical Biology
  • Meshfree Approximation Methods
  • Multi-scale Analysis and Simulation
  • Numerical Methods for PDEs
  • Optimal Control and Transport
  • Wave Phenomena and Inverse Problems


  • Geophysical and Environmental Applications 
  • Methods for Massive Data Sets
  • Spatial and Space-Time Processes
  • Functional Data Analysis 
  • Inverse Problems
  • Uncertainty Quantification

Primary Contact

Department Head

G. Gustave Greivel, Teaching Professor


Greg Fasshauer

Mahadevan Ganesh

Paul A. Martin

Doug Nychka

Associate Professors

Soutir Bandopadhyay

Cecilia Diniz Behn

Dorit Hammerling

Stephen Pankavich

Luis Tenorio

Assistant professors

Samy Wu Fung

Eileen Martin

Teaching Professors

Terry Bridgman

Debra Carney

Holly Eklund

Mike Nicholas

Jennifer Strong

Scott Strong

Rebecca Swanson

Teaching Associate Professors

Mike Mikucki

Ashlyn Munson

Teaching Assistant Professors

John Griesmer

Daisy Philtron

Emeriti Professors

William R. Astle

Bernard Bialecki

Norman Bleistein

Ardel J. Boes

Austin R. Brown

John A. DeSanto

Graeme Fairweather

Raymond R. Gutzman

Frank G. Hagin

Willy Hereman

Donald C.B. Marsh

William Navidi

Steven Pruess

Emeriti Associate Professors

Barbara B. Bath

Ruth Maurer