RESEARCH TOPICS

• Uncertainty quantification, verification, and validation

• Bayesian optimal experimental design (batch and sequential)

• Deep learning and computation

• Quantum computing: quantum computation-characterization-control

• Analysis and computation of parametric partial differential equations

• Numerical optimization and optimal transport

• Multi-scale and multi-fidelity modeling and computation

MEMBERS

• Mohammad Motamed

• Owen Davis, PhD student
  Project: Multi-fidelity deep learning with application to parameteric ODE/PDE problems
Defense: Scheduled Apr. 11, 2024


• Kyle Henke, PhD student
  Project: Analysis & computation of constrained sparse coding on emerging non-von Neumann devices
Defense: Completed Nov. 6, 2023


• Serafina Middleton, PhD student
  Project: Information-theoretic graphs and system dynamics
Defense: Expected 2025-2026


• Chase Hodges-Heilmann, PhD student
  Project: Quantum optimal control
Defense: Expected 2025-2026


• Jose Agudelo, PhD student
  Project: Stochastic computations with application to accelerator physics
Defense: Expected 2026-2027

CURRENT COLLABORATORS

• Sandia National Laboratories

• Los Alamos National Laboratory

• Lawrence Livermore National Laboratory

• Virginia Tech, Computational Modeling and Data Analysis (CMDA)

• RWTH Aachen University, Mathematics for Uncertainty Quantification

motamed@unm.edu
Last updated: 2023