Artem Smirnov
Independant SW & HW Developer at Freelance developer
Nizhny Novgorod, Nizhny Novgorod Oblast, Russia
Summary
🤩
Rockstar🎓
Top SchoolArtem Smirnov is an independent software and hardware developer with over a decade of experience building embedded systems, Linux kernel drivers, and automotive software aligned with ISO standards and AUTOSAR. He combines low-level expertise in AVR/ARM/x86 assembly and C/C++ with higher-level scripting in Python and Shell, and has worked across real-time OSes like ThreadX and VxWorks as well as mainstream GNU/Linux and Windows. Artem has contributed performance-focused optimizations to high-profile open-source ML libraries (notably XGBoost) and improved CPU implementations in oneDAL, showing a rare blend of embedded systems craftsmanship and data‑processing performance engineering. Based in Nizhny Novgorod, he leverages his Master’s in Radiophysics & Electronics to solve tough signal and protocol problems across GSM, IEEE802.11x, Bluetooth, CAN and TCP/IP stacks. Colleagues know him for digging into SIMD/prefetching optimizations and pragmatic refactoring that yields measurable speedups in production-grade code.
10 years of coding experience
10 years of employment as a software developer
Master’s Degree, Radiophysics & Electronics, Statistical radiophysics chair, Master’s Degree, Radiophysics & Electronics, Statistical radiophysics chair at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Github Skills (20)
algorithm10
algorithms10
xgboost10
c-language10
machine-learning10
data-structure10
oneapi10
performance-optimization10
dbscan10
data-structures10
cprogramming-language10
knn10
gbm9
machine-learning-algorithms9
datastructures-algorithms9
Programming languages (6)
Github contributions (5)
uxlfoundation/oneDAL
Sep 2019 - Feb 2021
oneAPI Data Analytics Library (oneDAL)
Role in this project:
ML Engineer
ML EngineerContributions:100 reviews, 23 commits, 76 PRs in 1 year 5 months
Contributions summary:Artem focused on optimizing and improving the performance of the oneDAL library, specifically targeting k-NN prediction and DBSCAN algorithms. Contributions included code modifications for CPU optimizations, and enhancements to handle large K values in the k-NN brute force implementation. The user also addressed platform-specific issues, fixing DBSCAN functionality on Windows.
swrepodata-analyticsanalyticscppdata-analysis
dmlc/xgboost
Jan 2019 - Feb 2020
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Role in this project:Performance Engineer
Performance EngineerContributions:17 reviews, 7 commits, 22 PRs in 1 year 1 month
Contributions summary:Artem focused on performance optimization within the XGBoost library, particularly for Intel CPUs. Their commits include significant code changes involving prefetching, SIMD instructions, and other low-level optimizations to improve execution speed. The user's contributions involved refactoring and cleaning up existing code, with specific modifications to the histogram building and splitting logic. Additionally, the user was involved in performance analysis and added runtime checks.
xgboostpythonflinkdaskdataflow
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