Neil Lindquist is a Developer Technology Engineer at NVIDIA with nine years of experience bridging high-performance computing research and production GPU optimization. He holds a PhD in Computer Science from the University of Tennessee, where his doctoral work explored how approximate computing can accelerate numerical linear solvers and reduce computational cost. Neil has a strong track record of porting and tuning scientific codes for GPUs—from CFD interpolation routines at Argonne to contributions at MathWorks and the Innovative Computing Laboratory—bringing both theoretical insight and practical implementation skills. He has worked on performance-oriented projects spanning Trilinos, Julia integrations, data-compression strategies for sparse solvers, and ML-driven workflows for XFEL data, highlighting a knack for applying diverse techniques to bottleneck problems. Based in Knoxville, he combines deep numerical linear algebra expertise with hands-on GPU performance engineering to help teams squeeze more throughput from modern hardware.
9 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Mathematics and Computer Science, Bachelor's degree, Mathematics and Computer Science at Saint John's University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Tennessee, Knoxville
Contributions:86 commits, 1 PR, 86 pushes in 2 years 2 months
common-lispremote-execution
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Neil Lindquist - Developer Technology Engineer at NVIDIA