Pierre De Reuille
Software Engineer at Google
London, England, United Kingdom
Summary
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RockstarPierre De Reuille is a software engineer based in London with 13 years of experience bridging research-grade numerical computing and production software at scale. Currently at Google, he brings a strong academic pedigree including postdoctoral work at the University of Bern and a PhD-focused trajectory across institutions such as INRA and the University of Calgary. His open-source contributions to high-impact scientific projects like PETSc and Statsmodels show a knack for improving numerical robustness and dependency compatibility—e.g., adding domain-error checks to PETSc time-stepping solvers and modernizing pandas/NumPy usage in statsmodels. Comfortable in back-end development for computational libraries, he combines deep numerical insight with practical engineering to harden and future-proof scientific codebases. Colleagues can expect a developer who moves fluidly between research problems and large engineering environments, with an eye for subtle correctness issues that prevent silent failures.
13 years of coding experience
5 years of employment as a software developer
French, English
Github Skills (12)
c1710
petsc10
statistics10
pandas10
c1110
python10
numpy10
data-analysis9
regression-models8
forecasting7
forecast7
fortran5
Programming languages (4)
Github contributions (5)
statsmodels/statsmodels
Oct 2015 - Nov 2015
Statsmodels: statistical modeling and econometrics in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 commits, 5 PRs, 101 comments in 9 days
Contributions summary:Pierre focused on improving the codebase's compatibility and versioning with external dependencies, particularly pandas and NumPy. Their contributions included updating pandas version checks, correcting how numpy arrays were used, and adjusting code to align with changes in library behavior. They also addressed issues related to the correct use of pandas features within the plotting functions and added general file opening functions. This indicates a focus on maintaining code stability and ensuring compatibility with evolving dependencies.
forecastingpythonregression-modelsstatsmodelsstatistics
petsc/petsc
Feb 2015 - Oct 2015
Mirror of https://gitlab.com/petsc/petsc
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 commits in 8 months
Contributions summary:Pierre implemented domain error checks within the PETSc time-stepping library. This involved adding new functions, `TSSetFunctionDomainError` and `TSFunctionDomainError`, and integrating them into existing time-stepping implementations. Additionally, the user added an example demonstrating the use of the pseudo timestep functionality. These changes directly impact the robustness and functionality of the time-stepping solvers within PETSc.
petscgitlab
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