San Kilkis is a software engineer and aerospace specialist based in Delft with eight years of experience building robust Python tools for engineering and performance analysis. At ParaPy and TU Delft he combined knowledge-based engineering and systems thinking to turn high-level aircraft specifications into parametric 3D models used for CFD and FEM, improving trailing-edge fidelity and drag prediction. A pragmatic backend contributor to notable open-source projects like strawberry-graphql and perfplot, he focuses on performance, correctness, and practical developer ergonomics (e.g., PEP-563 compatibility and automatic plotting scales). He brings strong object-oriented design, rigorous testing and optimization skills from both research labs (DLR) and production engineering, and a demonstrable passion for sustainable aviation. Notably, his work spans from teaching Python to shipping flight-performance tooling, giving him a rare blend of pedagogical clarity and systems-level implementation experience.
8 years of coding experience
1 year of employment as a software developer
Honors High School Diploma, 4.04/4, Honors High School Diploma, 4.04/4 at DoDEA Ankara ES/HS International High School
Bachelor of Science (B.Sc.), Aerospace, Aeronautical and Astronautical Engineering, 7.32/10, Bachelor of Science (B.Sc.), Aerospace, Aeronautical and Astronautical Engineering, 7.32/10 at Delft University of Technology
A GraphQL library for Python that leverages type annotations 🍓
Role in this project:
Back-end Developer
Contributions:47 reviews, 9 commits, 20 PRs in 10 months
Contributions summary:San contributed to the development of the Strawberry GraphQL library for Python. Their work involved implementing features such as compatibility with PEP-563 for private fields, allowing AsyncIterable and AsyncIterator return types for Subscriptions, preventing the creation of TypeDefinitions for private fields, and fixing directive argument issues. Additionally, the user refactored parts of the code, improved performance, and addressed bugs related to generics and interface handling, contributing to the overall stability and functionality of the library.
:chart_with_upwards_trend: Performance analysis for Python snippets
Role in this project:
Performance Engineer
Contributions:17 commits, 1 PR, 6 comments in 5 days
Contributions summary:San focused on enhancing the performance analysis capabilities of the `perfplot` library. They implemented an `automatic_scale` feature, allowing for more readable time-scale plots and updated the plotting functionality to improve readability and user experience. Additionally, they added tests to ensure the correctness of the new `automatic_scale` feature. These contributions demonstrate a focus on optimizing the library for practical performance analysis and usability.
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