Sean Baxter
Principal Research Scientist at NVIDIA
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolSean Baxter is a Principal Research Scientist at NVIDIA with 14 years of experience designing high-performance, data-parallel algorithms and compilers. He combines a physics-and-mathematics background with hands-on GPU performance engineering, having contributed optimizations and benchmarks to projects like ModernGPU and built his own compiler, Circle. His work spans CUDA kernel development, parallel merge implementations, and debugging edge cases in large-key sorting—demonstrating a focus on measurable performance gains. Sean’s Circle compiler highlights his interest in language design and control-flow features such as pattern matching and typed enums, and he’s open to demos for a deeper look. He has a track record at research-driven organizations including DE Shaw Research and JPL, bringing rigor from scientific programming to production-scale GPU systems. Colleagues can expect a practitioner who marries low-level optimization with thoughtful language and tooling design.
14 years of coding experience
8 years of employment as a software developer
Bachelor of Science (B.S.), Physics, Mathematics, Bachelor of Science (B.S.), Physics, Mathematics at Central Washington University
Github Skills (10)
cuda10
benchmark10
benchmarking10
c-language10
gpgpu10
cprogramming-language10
gpu10
pattern-matching10
accelerated-computing10
compiler-development10
Programming languages (15)
Github contributions (5)
moderngpu/moderngpu
May 2013 - Nov 2021
Patterns and behaviors for GPU computing
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:142 commits, 14 PRs, 83 pushes in 8 years 7 months
Contributions summary:Sean primarily contributed to the `moderngpu` repository by adding and benchmarking a naive parallel merge implementation. Their work included writing CUDA code for parallel merging, creating a benchmark to measure performance, and verifying the results against the STL merge function. Additionally, they addressed a bug related to large keys in the SortedEqualityCount function. The user demonstrates a focus on performance optimization through benchmarking and identifying areas for improvement in GPU computing algorithms.
cudabehaviorsgpu-programminggpu-accelerationgpu
seanbaxter/circle
Feb 2019 - Jan 2023
The compiler is available for download. Get it!
Role in this project:Back-end Developer
Back-end DeveloperContributions:331 commits, 3 PRs, 338 pushes in 4 years
Contributions summary:Sean is primarily working on the `circle` compiler project, adding features related to pattern matching. Their commits include implementing a typed-enums section and adding code that enables for-enum statements, which improve the control flow within the compiler. They also added examples for testing variant feature and related debug layout.
compilerc-plus-plusconstexpr
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