Contributed to highly-performant, high-order and matrix-free solid mechanics code Ratel under the auspices of the Predictive Science Academic Alliance Program (PSAAP).

• Developed GPU-enabled material point method for consolidation simulations of polymer-bonded crystalline materials
• Tuned solvers for AMD and NVIDIA GPU-based supercomputer environments
• Implemented elastic-rigid contact via Nitsche’s method and penalty method

Contributed to Lab-funded open-source projects for the simulation of solid mechanics and contact, with an emphasis on performance.

• Integrated PETSc linear and nonlinear solvers into the Serac solid mechanics code
• Dramatically improved solver performance, with runtime improvements exceeding 40%

Designed assignments aligning with curriculum and taught introductory programming in C++.

• Led two recitation sections weekly consisting of over 70 students
• Facilitated over 30 cumulative hours of interview grading
• Created design documentation and rubrics for final class project, a text-based video game

Researched optimal optimal methods of domain decomposition for eigenvalue problems, particularly spectral Schur complement techniques. Continued research on decentralized optimization in collaboration with LLNL.

• Led development of a moderately-sized software library to facilitate communication between grid devices
• Collaborated with internal and external project contributors and stakeholders
• Augmented existing numerical methods with robustness to communication delays and bad data
• Invented novel asynchronous, distributed linear solver based on Krylov subspace methods

Applied mathematical and computing principles to power system resilience through collaborative autonomy.

• Received Mathematics departmental undergraduate research award
• Presented early results on domain decomposition for eigenvalue problems at 2020 Undergraduate Research Day at the Capitol
• Presented at 2021 SIAM Conference on Computational Science and Engineering over: Using Decentralized Learning to Reduce Communication in Column-Partitioned, Multi-Agent Systems

GPA: 4.0/4.0

Advisor: Jed Brown, PhyPID Group

Coursework centering on numerical methods and high-performance scientific computing.

Research projects:

• Implemented Nitsche’s method for modeling contact between elastic and rigid solid bodies in PSAAP-sponsored Ratel code
• Developed entropy variable implementation of Navier-Stokes fluid dynamics in PSAAP-sponsored libCEED code (now HONEE)
• Contributed arc-length continuation solver to PETSc, a high-performance, scalable library for numerical PDEs
• Developed implicit, updated Lagrangian material point method solver for hyperelastic materials in Ratel
• Created ChordDyn, a Tonnetz-based chord progression generator using chaotic dynamics in Julia

GPA: 4.0/4.0

Major projects:

• Awarded departmental honors for a project on the application of decentralized optimization methods to edge devices
• Received university undergraduate research award for domain decomposition methods for eigenvalue problems

Courses included:

• Advanced Numerical Differential Equations (MATH 882)
• Numerical Analysis I & II (MATH 781 & 782)
• Applied Numerical Linear Algebra (MATH 591)
• Mathematical Analysis I (Math 765)
• Complex Analysis I (MATH 800)

GPA: 4.0/4.0

Comprehensive background in data structures, algorithms, and computing theory. Electives in artificial intelligence and computer graphics, as well as cross-major electives in numerical analysis.

Major projects:

• C and C++ projects including functioning compiler and basic Linux shell
• Reinforcement learning with OpenAI using Python
• Video game and graphics development using Unity, PyGame (Flat-Earth Space Program), and OpenGL (various projects)