Graduate Students
PhD Students
Jared Andreatta
Chauvenet Hall 271
jared_andreatta@mines.edu
Research:
Geospatial Data Science
Spatiotemporal Analysis
Environmental Modeling
Deep Learning
Michael Basanese
Chauvenet Hall 270
mbasanese@mines.edu
Research:
Applied statistics for emissions monitoring and other environmental problems.
Souvick Bera
Graduate Teaching Fellow
Chauvenet Hall 267
berasouvick@mines.edu
Research:
Nonparametric Inference
Large Sample Theory
Asymptotic Analysis
Probability Theory
Rachel Bertaud
Chauvenet Hall 266
rachel_bertaud@mines.edu
Research:
Computational Fluid Dynamics
Numerical Methods
Teaching and Learning
Clubs and Associations:
Society for Women in Mathematics (SWiM)
Mines Mathematics and Computing Collective (MMCC)
Graduate Student Government (GSG)
Susmit Bhattacharyya
Graduate Teaching Fellow
Chauvenet Hall 267
susmitbhattacharyya@mines.edu
Research:
Spatial Extremes
Dibyajyoti Chakrabarti
Chauvenet Hall 266
dibyajyoti_chakrabarti@mines.edu
Research:
Spatial Statistics
Large Sample Theory
Nonparametric Inference
Statistical Genetics
Isabella Chittumuri
Chauvenet Hall 272
ichittumuri@mines.edu
Research:
Applied Statistics
- Geospatial Risk Analysis
- Machine Learning
- Climate Adaptation in cold regions
Eric Gelphman
Chauvenet Hall 272
eric_gelphman@mines.edu
Research:
- High-Dimensional Continuous Optimization
- Optimal Transport
- Numerical Methods for PDEs
Sam Hall
Chauvenet Hall 268
samantha_hall@mines.edu
Research:
Mathematical modeling and numerical methods to study and understand natural systems.
Dylan Hettinger
Chauvenet Hall 270
dhettinger@mines.edu
Research:
Spatial Statistics
Large Data Statistical Inference
Uncertainty Quantification
Sensitivity Analysis
Andrew Holmberg
Chauvenet Hall 269
andrew_holmberg@mines.edu
Research:
Environmental Modeling
Optimization
Model Development
Methane Detection
Nusrat Islam
Chauvenet Hall 266
kazinusrat_islam@mines.edu
Research:
Applied Mathematics with a focus on Mathematical Modeling, Dynamical Systems, Differential Equations, Epidemiological Modeling and Numerical Analysis.
Olga Khaliukova
Chauvenet Hall 268
okhaliukova@mines.edu
Research:
Applied Statistics
- Spatial Statistics (application: methane emissions satellite data)
- Machine Learning (application: image analysis)
- Neural Network Architecture
Clubs and Associations:
Society for Women in Mathematics (SWiM)
Brandon Knutson
Chauvenet Hall 273
bknutson@mines.edu
Research:
Mathematical Modeling
Numerical Simulation
Visualization to understand Physical Systems
Ziyu Li
Graduate Teaching Fellow Chauvenet Hall 274
ziyu_li@mines.edu
Research:
Spatial and Bayesian Statistics
Computational Statistics
Hydrology
Madison Lytle
Chauvenet Hall 268
madison_lytle@mines.edu
Research:
Modeling wiggling, bending, rolling and flowing at the micron scale
Grace Mattingly
Chauvenet Hall 274
gmattingly@mines.edu
Research:
Computational Mathematics and Analysis
Applied Mathematics and Wave Phenomena
Clubs and Associations:
Society of Women in Mathematics (SWiM)
Women Graduate Students
Brendan McKinley
Chauvenet Hall 268
brendan_mckinley@mines.edu
Research:
Numerical methods for PDEs and applications in soft matter physics
Ryan Peterson
Chauvenet Hall 273
rhpeterson@mines.edu
Research:
Applied Statistics
- Aggregation problems in Spatial Statistics
Andres Pruet
Chauvenet Hall 270
andres_pruet@mines.edu
Research:
Numerical Methods for Differential Equations
Daniel Ramirez
Chauvenet Hall 269 daniel_ramirez@mines.edu
Research:
Mathematical Biology and Biostatistics
Differential Equations and Dynamical Systems
Mathematical Modeling of Metabolic Systems
Hugh Scribner
Chauvenet Hall 266 hugh_scribner@mines.edu
Research:
- Numerical solutions to PDE’s
- Optimization and their applications to problems in sustainability.
Troy Sorensen
Chauvenet Hall 270 trsorensen@mines.edu
Research:
Applied Statistics
- Machine Learning for Detection
- Quantification
- Localization of Methane Emissions
Axel Fraud
Chauvenet Hall 271 axel_fraud@mines.edu
Research:
- Developing statistically grounded methods for inverse problems
- Probabilistic modeling
- Data-driven scientific computing, with applications to the physical sciences.
