Christopher Harris
Founder Latent Systems Advanced Materials & Field-Driven Systems
Allen, Texas, United States
Summary
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Rockstar🎓
Top SchoolChristopher Harris is a founder and systems software engineer with 13 years of experience building high-performance, field-driven systems and GPU-accelerated software. After leading backend work on NVIDIA RAPIDS—contributing performance-focused CUDA and GPU DataFrame improvements—he now runs Latent Systems to prototype advanced ceramics, functional coatings, and field-responsive materials grounded in first-principles experimentation. His engineering career spans consumer-scale products at Netflix and Google to data- and memory-intensive platforms at NVIDIA, where he improved core libraries like rmm, cudf, and cuspatial. Comfortable across low-level C++/CUDA, CI/CD, and system design, he blends hands-on R&D with production-grade software practices. Not obvious at first glance: he pairs deep device-level optimization experience with physical-materials R&D, translating computational performance thinking into experimental materials engineering. Based in Allen, Texas, he’s an active open-source contributor who favors pragmatic refactors that unlock measurable performance and reliability gains.
13 years of coding experience
14 years of employment as a software developer
Bachelors of Science Computer Information Systems, Bachelors of Science Computer Information Systems at East Texas A&M University
Stackoverflow
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318answers
17questions
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reactive-programming
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Github Skills (37)
algorithm10
algorithms10
javascript10
memory-allocation10
c-language10
jquery10
python10
checkbox10
testing10
css10
memory-management10
cudf10
data-structure10
cicd10
html10
Programming languages (12)
Github contributions (5)
rapidsai/cuspatial
Apr 2020 - Jul 2021
CUDA-accelerated GIS and spatiotemporal algorithms
Role in this project:
Back-end Developer
Back-end DeveloperContributions:42 reviews, 190 commits, 49 PRs in 1 year 3 months
Contributions summary:Christopher primarily focused on optimizing and refactoring CUDA-accelerated algorithms within the cuspatial repository. The contributions involve the addition and replacement of CUSPARSE error handling mechanisms. These changes show the user is adept in performance improvements by moving code into separate files and adapting the project's error handling.
cudagpu-programminggpu-accelerationgpuaccelerated
rapidsai/cudf
Jul 2019 - Jul 2022
cuDF - GPU DataFrame Library
Role in this project:Back-end Developer
Back-end DeveloperContributions:502 reviews, 609 commits, 139 PRs in 3 years
Contributions summary:Christopher's commits focus on the development of the cuDF GPU DataFrame Library, specifically addressing merge operations and enhancing the generation of random series. The changes include modifications to merge tests and include new test cases for various merge scenarios, indicating a focus on improving data processing and functionality. Furthermore, the commits demonstrate expertise in database systems by adding and improving test cases, which indicates the user is proficient in integrating database-related features.
cudadataframe-librarydata-analysiscppcudf
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