Reid Atcheson is a research engineer with 12 years of experience specializing in numerical analysis, algorithm development, and high-performance implementation across CPUs, GPUs, and custom silicon. He has moved from academic research in high-order numerical wave propagation to production performance engineering—optimizing ML inference and whole-system latency for autonomous vehicles and developing hardware-agnostic libraries at NAG. Reid combines deep low-level tuning (NUMA, vectorization, cache) with practical porting and modernization work (Fortran→C++, CUDA/HIP), making legacy scientific code run efficiently on modern architectures. Now based in New York, he applies this stack-level mindset at Aquatic Capital Management, bringing monitoring and long-tail latency mitigation practices learned at Cruise. Colleagues can expect a blend of rigorous numerical background (PhD from Rice) and pragmatic, experiment-driven engineering—his public GitHub is a window into quick experiments while curated work lives on his website.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computational and Applied Mathematics, Doctor of Philosophy (Ph.D.) Computational and Applied Mathematics at Rice University
B.S Mathematics, B.S Mathematics at Kennesaw State University
Contributions:35 commits, 27 pushes, 3 branches in 2 months
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Reid Atcheson - Research Engineer at Aquatic Capital Management