Curriculum Vitae

Education

Ph.D in Applied Mathematics University of Arizona, 2026 (expected)
- Minor in Aerospace Engineering
M.S. in Applied Mathematics, University of Arizona, 2023
B.S. in Applied and Computational Mathematics, Brigham Young University, 2021
- Concentration in Physics

December 2023 – Present: Graduate Research Assistant
- University of Arizona (Tucson, AZ) – Computational Hypersonics and Nonequilibrium Lab
  - Implements new thermodynamic mechanism in open-source library to model vibrational energy states
  - Simulates energy transfer and atomic state transitions through computational fluid dynamics
August 2021 – December 2022: Graduate Teaching Assistant
- University of Arizona (Tucson, AZ)
  - Taught introductory class about understanding data and data exploration
May 2020 – August 2020: High Energy Density Physics Student Intern
- Lawrence Livermore National Laboratory (Livermore, CA)
  - Utilized hydrodynamics code to create an accurate neural network model for artificial viscosity
  - Implemented neural network that resulted in similar accuracy as high-order operator
September 2019 April 2020: Research Assistant
- Brigham Young University (Provo, UT)
  - Analyzed previously published literature on fractional derivatives
  - Applied the finite difference method to numerically solve PDEs with fractional derivatives
May 2019 – August 2019: High Energy Density Physics Student Intern
- Lawrence Livermore National Laboratory (Livermore, CA)
  - Generated and analyzed simulations to determine accuracy and convergence

Mathematics
- Algorithms, Approximation, Optimization
- Linear Algebra
- Mathematical Programming
Physics
- Aerothermodynamics
- Compressible Fluid Dynamics
- Computational Physics
Software
- Languages: Python, C++, Bash
- Experience with Git
- Machine Learning and Deep Learning: TensorFlow, PyTorch
- Unix/batch-computing environment

August 2016 – August 2018: Full-Time Volunteer Representative
- The Church of Jesus Christ of Latter-day Saints (Quito, Ecuador)
  - Supervised and motivated groups of 8 volunteers to help them work better and more efficiently
  - Analyzed team results to determine weekly training topics, resulting in achieving group improvement goals
  - Daily, specialized training provided to new volunteers on a one-on-one basis for first 12 weeks