Luís Pereira
Research Engineer at UC Santa Barbara
Santa Barbara, California, United States
Summary
🤩
Rockstar🎓
Top SchoolLuís Pereira is a research engineer and scientific software developer based in Santa Barbara with six years of experience building numerical and geometry-focused tools in Python, Rust, C++ and Matlab. With a Master's in Mechanical Engineering from Universidade do Porto, he blends mechanics intuition with deep interests in linear algebra, numerical analysis and Riemannian geometry. He contributes to the prominent open-source geomstats project, improving core manifold abstractions like VectorSpace and stratified-space support while adding tests and data structures that strengthen mathematical correctness. At UC Santa Barbara he applies this mix of research and engineering to back-end scientific software, favoring rigorous testing and reproducible code. Colleagues describe him as an open-source enthusiast who prefers fixing foundational math issues rather than only adding surface features.
6 years of coding experience
Master's degree, Mechanical Engineering, Master's degree, Mechanical Engineering at Faculdade de Engenharia da Universidade do Porto
French, English, Italian, Portuguese
Github Skills (6)
pytest10
python10
modeling9
data-structure9
mathematical9
data-structures9
Programming languages (4)
Github contributions (5)
geomstats/geomstats
Feb 2022 - Jan 2023
Computations and statistics on manifolds with geometric structures.
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:3 releases, 389 reviews, 669 commits in 11 months
Contributions summary:Luís primarily contributed to the development of the `geomstats/geomstats` repository. Their work focused on enhancing the functionality of the `VectorSpace` class, ensuring consistent basis property, and fixing issues related to stratified spaces and the `Spider` class, indicating a focus on core mathematical and geometric concepts. Furthermore, the user added tests and data structures for stratified spaces and the `Spider` class, indicating a commitment to rigorous testing and code quality. Their contributions suggest an involvement in both back-end development and applying data science methods within the context of the project's focus on manifold-based computations and statistics.
gpu-programmingstatisticslie-groupsdeep-learningneural-networks
luisfpereira/geomfum
Aug 2024 - Mar 2025
Geometry processing with functional maps.
Contributions:5 reviews, 11 PRs, 62 pushes in 6 months
functional-mapsgeometry-processingmeshpoint-cloudshape-matching
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