Optimum Numerics Research Group
Optimum Numerics Research Group


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

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

  • Kyle Henke, PhD
      Project: Analysis & computation of constrained sparse coding on emerging non-von Neumann devices
    • PhD 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

motamed@unm.edu
Last updated: 2024