Paul Smith is a Software Engineer with eight years of experience, based in England, who combines research-focused rigor with practical backend engineering. As a Senior Research Software Engineer on GitHub, he has contributed performance and memory optimizations to MDAnalysis, a widely used Python library for molecular dynamics analysis, improving core routines like survival probability calculations. His work emphasizes efficient data structures and NumPy-friendly outputs, translating domain knowledge into cleaner, faster code. Trained in languages and cultures at UCL, he brings uncommon strengths in communication and cross-disciplinary collaboration to technical projects.
MDAnalysis is a Python library to analyze molecular dynamics simulations.
Role in this project:
Back-end Developer
Contributions:30 reviews, 20 commits, 7 PRs in 3 years 6 months
Contributions summary:Paul primarily focused on optimizing the `SurvivalProbability` class within the `MDAnalysis` library, specifically in the `waterdynamics.py` file. Their contributions involved optimizing the calculation of survival probability by storing atom selections as sets for faster intersection operations. The user also refactored code by returning survival probability results as NumPy arrays and renaming variables for clarity. They additionally improved memory efficiency by storing atom IDs instead of entire atom groups.
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Paul Smith - Software Engineer at University College London