Mike Smirnov
Software Development Engineer at Intel Corporation
Nizhny Novgorod, Nizhny Novgorod Oblast, Russia
Summary
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RockstarMike Smirnov is a seasoned Software Development Engineer with 11 years of experience based in Nizhny Novgorod, currently building high-performance data analytics and ML infrastructure at Intel. He contributes to prominent open-source projects such as oneDAL and scikit-learn-intelex, focusing on DPC++/DPCTL support, performance optimizations, and robust test automation. His work spans backend algorithm implementation (e.g., logistic regression enhancements and second-class probability computation) to CI/test fixes that keep libraries production-ready across heterogeneous compute backends. Known for bridging data science algorithms with low-level performance engineering, he brings a pragmatic blend of QA rigor and systems-level coding. Colleagues rely on him to make compute-heavy workflows both faster and more reliable across accelerator-enabled environments.
11 years of coding experience
Github Skills (24)
algorithm10
unit-testing10
c-language10
python10
scikit10
testing10
machine-learning-algorithms10
oneapi10
scikit-learn10
test-integration10
logistic-regression10
cprogramming-language10
test-unit10
unit-test10
integration-testing10
Programming languages (3)
Github contributions (5)
uxlfoundation/scikit-learn-intelex
Apr 2020 - Sep 2021
Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Role in this project:
Backend Developer & QA Engineer / Test Automation Engineer
Backend Developer & QA Engineer / Test Automation EngineerContributions:92 reviews, 29 commits, 38 PRs in 1 year 5 months
Contributions summary:Mike's commits primarily focus on testing and ensuring the correctness of the `scikit-learn-intelex` library. The contributions involve fixing tests, adding copyright notices to files, and changing paths for CI environments. Furthermore, the user modified several examples and examples used for testing to work properly with DPCTL and USM.
pythonswrepoai-machine-learningdata-scienceintel
uxlfoundation/oneDAL
Nov 2019 - Jul 2021
oneAPI Data Analytics Library (oneDAL)
Role in this project:Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:387 reviews, 40 commits, 86 PRs in 1 year 7 months
Contributions summary:Mike primarily contributed to the development of the oneAPI Data Analytics Library (oneDAL), focusing on the implementation of logistic regression algorithms. They added functionality for second class probability calculation in binary logistic regression, and also added ComputeCpp 1.1.6 support. Furthermore, the user improved the table metadata concept and added DPC++ support for the array and data management aspects of the library. These changes demonstrate a strong focus on improving the data analysis capabilities and performance within the oneDAL framework.
swrepodata-analyticsanalyticscppdata-analysis
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