Dylan Copeland is a computational mathematician with seven years of professional experience, currently advancing numerical methods and meshing technologies at Lawrence Livermore National Laboratory. He specializes in finite element methods, adaptive and NURBS meshing, isogeometric analysis, and reduced-order models, and is an active backend developer for the widely used MFEM library where he implemented partial assembly kernels and operator enhancements. Dylan’s background spans industry and academia—from hydraulic fracturing simulation and deep learning at Riventec and GeoNumerical to multigrid and electromagnetics research—giving him a rare blend of applied simulation expertise and algorithmic innovation. Based in Livermore, CA, he consistently turns advanced mathematical ideas into performant, open-source software used for large-scale PDE solvers. An understated strength is his track record of improving low-level operator performance, a detail that materially accelerates production-scale simulations.
7 years of coding experience
7 years of employment as a software developer
Ph.D., Mathematics, Ph.D., Mathematics at Texas A&M University
Lightweight, general, scalable C++ library for finite element methods
Role in this project:
Back-end Developer & Numerical Methods Specialist
Contributions:789 reviews, 495 commits, 47 PRs in 4 years 3 months
Contributions summary:Dylan contributed to the MFEM library, focusing on the development and optimization of numerical methods for solving partial differential equations. Their work included implementing new features for operators, such as adding the MultTranspose method to the IdentityOperator and adding checks in the ProductOperator, TripleProductOperator, and RAPOperator. Furthermore, the user enhanced the library by implementing partial assembly (PA) for various types of bilinear forms, like those using H(curl) and vector spaces, including the development of kernels for the same.
Contributions:3 pushes, 1 comment in 2 years 1 month
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.