Conrad Sanderson
Research Scientist & Team Leader at Data61 / CSIRO
Queensland, Australia
Summary
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RockstarConrad Sanderson is a Research Scientist and team leader at Data61/CSIRO with a decade of experience building robust, high-performance C++ numerical and machine-learning software. He is an active open-source maintainer on prominent projects such as mlpack and ensmallen, specializing in Armadillo integration, compilation hardening, and numerical stability fixes. Conrad combines hands-on engineering—resolving API changes, deprecation warnings, and edge-case eigensolver issues—with documentation and example work that helps other developers adopt these header-only libraries. Based in Queensland, he brings a researcher’s rigor to production-grade code and a knack for simplifying complex linear-algebra interactions that quietly prevent costly downstream bugs.
9 years of coding experience
Github Skills (17)
algorithm10
c-language10
armadillo10
optimizers10
machine-learning10
deep-learning10
optimisation10
cplus10
cpp10
cprogramming-language10
optimization10
minimize8
deeplearning-ai8
regression8
minification8
Programming languages (16)
Github contributions (5)
mlpack/ensmallen
Nov 2018 - Jun 2022
A header-only C++ library for numerical optimization --
Role in this project:
Back-end Developer
Back-end DeveloperContributions:61 reviews, 48 commits, 89 PRs in 3 years 7 months
Contributions summary:Conrad primarily focused on fixing bugs and improving the robustness of the `ensmallen` library. Their contributions involved addressing potential issues related to the `arma::eig_sym()` function and compiler warnings, indicating a focus on numerical computation and code stability. They also implemented a short example program, expanded the README, and bumped the armadillo version. They demonstrated proficiency in the C++ language and the use of Armadillo library.
optimization-methodsoptimization-algorithmsnumerical-optimizationheader-onlycplusplus
mlpack/mlpack
Apr 2018 - Dec 2022
mlpack: a fast, header-only C++ machine learning library
Role in this project:ML Engineer
ML EngineerContributions:161 reviews, 14 commits, 87 PRs in 4 years 8 months
Contributions summary:Conrad primarily contributed to the mlpack library by addressing compilation issues and deprecation warnings related to Armadillo library updates. Their work involved modifying code to handle new vector types and adapt to changes in the Armadillo API, ensuring continued compatibility. They also made changes to test cases, including those using initializer lists and updating to the latest Catch2 version. Finally, they performed some simplification and code cleanup.
regressionheaderdeep-learningscientific-computingc-plus-plus
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