Conor Hoekstra
Research Scientist at NVIDIA
Old Toronto, Ontario, Canada
Summary
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RockstarConor Hoekstra is a Research Scientist with eight years of hands-on experience building high-performance GPU software and production CI/CD systems, currently at NVIDIA after roles at Amazon and Moody’s Analytics. He specializes in CUDA-enabled data and graph libraries—contributing deep fixes and performance work to RAPIDS projects like cuDF, cuGraph and cuSpatial—while also improving developer velocity through CI, code-style automation, and DevOps tooling. Conor pairs low-level numeric engineering (fixed-point arithmetic implementations and edge-case testing) with pragmatic build and integration skills, ensuring both correctness and reproducible performance. Outside production code he pursues language-play and algorithmic puzzles in APL, BQN and J, reflecting a taste for concise, expressive problem solving that informs his approach to algorithm design.
8 years of coding experience
Github Skills (24)
algorithms10
programming-language10
c-language10
compilation10
bash10
clang-format10
cicd10
cuda10
cprogramming-language10
devops10
code-formatting10
unit-testing9
graph-analysis9
graph-algorithms9
python9
Programming languages (23)
Github contributions (5)
rapidsai/cudf
Oct 2019 - Feb 2022
cuDF - GPU DataFrame Library
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:585 reviews, 761 commits, 163 PRs in 2 years 3 months
Contributions summary:Conor focused on implementing core components for fixed-point arithmetic functionality within the cuDF GPU DataFrame Library. They implemented mathematical operators such as addition, subtraction, multiplication, division, and comparison on fixed-point datatypes, along with functions for rescale and truncation. Furthermore, the user also implemented a suite of unit tests to ensure the correctness, and performance of the implemented fixed-point operations, with focus on identifying edge cases and testing various scaling scenarios.
cudadataframe-librarydata-analysiscppcudf
rapidsai/rmm
Apr 2020 - Apr 2022
RAPIDS Memory Manager
Role in this project:DevOps Engineer
DevOps EngineerContributions:47 reviews, 29 commits, 6 PRs in 2 years
Contributions summary:Conor primarily focused on improving the continuous integration setup for the repository. They added and updated scripts to check code style using `clang-format`, `isort`, and `flake8`. The user also made several modifications to the `ci/checks/style.sh` file and fixed Python formatting issues to ensure the CI/CD pipeline functions correctly. These changes indicate a focus on automating code quality checks within the build process.
cudamemory-managementmemorycpppython
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