Applied Mathematics and Statistics Research at Mines

Advanced Mathematics and Statistics for the Modern World

The Computational & Statistical Geosciences Group works on all aspects of statistics and modeling atmospheric, oceanic and solid Earth and planetary problems.

The Computational & Statistical Geosciences Group focuses on mathematical and statistical modeling to address a broad spectrum of time-dependent dynamical and static problems related to the Earth and planetary sciences. Our research is often computationally and data-intensive, requiring high-performance computing to interpret atmospheric, oceanic, solid Earth, and planetary processes. 

Our work encompasses the development and application of asymptotic and numerical methods and optimization techniques to investigate the formation and evolution of the Earth and the solar system, as well as environmental, atmospheric, and climate problems. This includes but is not limited to, active and passive-source seismology (e.g., using quakes and ambient noise), 2D/3D numerical wave simulations, tomography, full-waveform inversion as well as utilizing single and array measurements to explore and monitor near-surface and environmental processes, employing both classical (i.e., geophones, broadband sensors) and emerging instruments (i.e., fiber optic cables). We also develop and apply statistical methods to gain deeper insights into atmospheric, oceanic, and solid Earth and planetary phenomena and address oil & gas industrial problems. 

Affiliated Faculty

Ebru Bozdağ

Email: bozdag@mines.edu
Website: https://ebrucsm.wordpress.com/

• Global & Computational Seismology 
• Linearized and non-linear inverse theory 
• 3D (numerical) wave propagation 
• Deep Earth and planetary sciences 
• Seismic hazard 

Samy Wu Fung

Email: swufung@mines.edu
Website: https://swufung.github.io/

• Inverse Problems, Optimization, Deep Learning
• Optimal Control, Mean Field Games

Dorit Hammerling

Email: hammerling@mines.edu
Website: https://ams.mines.edu/hammerling-research-group/

• Spatial statistics for large data
• Environmental statistics
• Computational statistics
• Weather and climate applications
• Oil and gas emissions and local sensing
• Remote sensing data applications

Nathan Lenssen

Email: lenssen@mines.edu

• Statistical prediction of dynamical systems
• Spatial statistics for geoscience applications
• Large-scale atmospheric and oceanic dynamics
• Impacts of climate change on natural and human systems

Eileen Martin

Email: eileenrmartin@mines.edu

• Near-surface, engineering, environmental and urban geophysics
• Analysis of large sensor networks
• Fiber-optic sensing, including distributed acoustic sensing
• Signal processing, imaging, and inverse problems
• Data-intensive high performance computing
• Passive seismic methods