Sheehan Olver
Reader at Imperial College London
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolSheehan Olver is a Reader in applied mathematics at Imperial College London with 14 years of research and academic experience spanning senior roles at the University of Sydney and Oxford. He combines deep numerical and linear-algebra expertise—evident from core contributions to the Julia language’s array stride handling and BLAS/LAPACK integration—with practical visualization work adding GLVisualize support to JuliaPlots. His background (PhD from Cambridge, BSc from Minnesota) underpins a rare blend of theoretical rigor and low-level performance engineering that improves scientific computing stacks used by a global community. Comfortable operating at the intersection of research and production code, he focuses on extending numerical libraries to be both faster and more expressive for users.
14 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (PhD), Applied Mathematics, Doctor of Philosophy (PhD), Applied Mathematics at University of CambridgeUniversity of Minnesota Twin Cities
Github Skills (18)
visualization10
blas10
plot10
lapack10
visualizations10
linear-algebra10
julia10
typed-array9
multidimensional-arrays9
back-end-development9
arrayobject9
dynamic-array9
numerical-methods9
parallel-arrays9
language-design8
Programming languages (13)
Github contributions (5)
JuliaLang/julia
Dec 2017 - Mar 2022
The Julia Programming Language
Role in this project:
Back-end Developer
Back-end DeveloperContributions:17 reviews, 45 commits, 37 PRs in 4 years 3 months
Contributions summary:Sheehan's primary contributions involve modifying and improving the core functionality of the Julia programming language. They focused on implementing or adapting strided array interfaces within the codebase, and made several modifications to the linear algebra (LinAlg) sub-package, specifically related to BLAS and LAPACK. This included incorporating improvements to the calculation of strides, and the support of mathematical operator overloading. These changes suggest a focus on improving performance and extending the capabilities of the underlying numerical libraries.
sciencejulia-languagemachine-learningjulialangpetsc
JuliaPlots/Plots.jl
Nov 2015 - May 2017
Powerful convenience for Julia visualizations and data analysis
Role in this project:Back-end Developer
Back-end DeveloperContributions:8 commits, 6 PRs, 93 comments in 1 year 6 months
Contributions summary:Sheehan contributed to the JuliaPlots project by implementing and integrating the GLVisualize backend for plotting. They added support for GLVisualize by modifying `src/plotter.jl`, creating the `src/backends/glvisualize.jl` file with necessary functions, and updating `src/backends/supported.jl`. Their changes involved adding and modifying plotting functionality to support the rendering of plots using the GLVisualize library.
data-analysisjulia-languageconveniencevisualizationsdata-visualization
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