Hi everyone,
My name is Faraz Shamim. I am currently a 4th-year MBBS student with a strong passion for computational statistics and open-source development.
Coming from a medical background, I am entirely self-taught in programming. I built my technical foundation through resources like CS50, Kaggle, and various online documentation, which eventually led me to the PyMC ecosystem. I’ve found Bayesian modeling incredibly relevant to scientific research, which inspired me to dive into the codebase and give back to the project.
I’ve recently started contributing and have opened a few Pull Requests to get familiar with the ecosystem, ranging from documentation to backend logic:
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pymc-devs/video-timestamps: Added timestamps for the “Dante’s Bayes” video to help improve accessibility (PR for #11).
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pymc-devs/pymc: Implemented transform_labels for dimensionality-reducing transforms (like Simplex, SumTo1, and ZeroSum) to fix coordinate handling issues (PR for #7907).
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pymc-devs/pytensor: Refactored the MLX test suite to properly consolidate elementwise operations (PR for #1730).
I really enjoy working on the internals of the library and I am writing to introduce myself as I am very interested in applying for Google Summer of Code 2026 with PyMC.
I plan to continue contributing fixes and improvements over the coming months. If anyone has advice on specific areas of the codebase that need attention, or if you have a moment to chat about a project’s roadmap/GSoC preparation, I would strictly appreciate any guidance!
Excited to be part of this community and look forward to learning from you all.
Best,
Faraz Shamim