Olivier De Gevigney
Applied Scientist at Amazon
Vancouver, British Columbia, Canada
Summary
👤
Senior🎓
Top SchoolOlivier De Gevigney is a Senior Applied Scientist in Vancouver with 11 years of experience blending deep academic expertise in combinatorial optimization (PhD) with hands-on engineering at Amazon and earlier startups. He builds and leads teams to turn complex algorithmic problems into production-grade services, having architected routing optimization that improved solution quality for half of requests at Routific and later delivering scalable systems at AWS/Amazon. Olivier is comfortable across research and implementation — from disproving conjectures in graph orientation during his PhD to shipping robust SaaS features and infrastructure — and he brings a pragmatic, impact-oriented mindset to fast-paced environments. A reliable collaborator who invites critique, he also contributes to well-known open-source projects such as improving documentation and examples for the Rayon Rust parallelism library, signaling attention to developer experience as well as algorithms.
11 years of coding experience
8 years of employment as a software developer
2010, Optimization, Operations Research, 2010, Optimization, Operations Research at Ecole nationale supérieure de Techniques avancéesDoctor of Philosophy (PhD), Mathematics and Computer Science, Doctor of Philosophy (PhD), Mathematics and Computer Science at Université de GrenobleIngénieur, Applied Mathematics, Ingénieur, Applied Mathematics at Ecole polytechnique
English, French
Github Skills (4)
documentation10
rust10
parallel10
library-design9
Programming languages (15)
Github contributions (5)
rayon-rs/rayon
Jan 2018 - Jan 2018
Rayon: A data parallelism library for Rust
Role in this project:
Technical Writer
Technical WriterContributions:5 commits, 1 PR, 1 comment in 3 days
Contributions summary:Olivier's contributions center around enhancing the documentation of the `rayon-rs/rayon` repository. They added and formatted examples for various methods of the `ParallelIterator` trait, including `map_with`, `reduce_with`, and `fold_with`. These changes involve providing usage examples and improving the clarity and presentation of existing documentation, making it easier for users to understand and utilize the library's functionalities.
rustparallelismrayonparallelism-librarydata-parallelism
oddg/rust
May 2020 - Jun 2020
Empowering everyone to build reliable and efficient software.
Contributions:9 pushes, 3 branches in 1 month
rustreliableempoweringrust-languagerust-lang
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