Principal Engineer, Fuel Performance at Lightbridge Corporation
Virginia, United States
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Summary
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Senior
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Top School
Derek Slaughter is a Principal Engineer and mechanical expert with nine years of professional experience combining software development, finite element modeling, and high-performance simulation for energy and industrial systems. He builds and optimizes scientific codes across languages (Go, Python, Fortran, C/C++, Rust) and has delivered dramatic performance gains—up to 100x in legacy Fortran workflows—while addressing memory and runtime bottlenecks. His work spans nuclear fuel performance, wind-turbine simulation (notably contributions to the widely used OpenFAST project improving memory handling and C++/Python APIs), and production-scale automation for HPC environments. Derek blends hands-on FEA and thermal-mechanical analysis with modern software practices—creating GUIs, web backends, and performance-portable GPU code via Kokkos—to make complex simulation pipelines usable and robust. He has a track record of designing new solvers (geometrically exact beam DAE solvers) and applying optimization and automation to accelerate engineering decisions. Based in Virginia, he pairs deep mechanical instincts from an MS in Mechanical Engineering with pragmatic software engineering to turn research-grade models into production-ready tools.
9 years of coding experience
19 years of employment as a software developer
Master of Science, Mechanical Engineering, Master of Science, Mechanical Engineering at Virginia Tech
Main repository for the NREL-supported OpenFAST whole-turbine and FAST.Farm wind farm simulation codes.
Role in this project:
Back-end Developer
Contributions:1 release, 173 reviews, 9 commits in 27 days
Contributions summary:Derek primarily focused on enhancing the OpenFAST library and its associated Python and C++ interfaces. Their contributions involved modifying the `FAST_Sizes` function to expose `DT_Out`, which improves memory management and output data consistency. They also refactored the `openfast_library.py` and C++ API to optimize data handling, reduce memory usage, and address potential memory leaks. Their work improved the overall performance and efficiency of the OpenFAST simulation tools.
Contributions:3 releases, 62 pushes, 1 branch in 10 months
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