Maria Kaglinskaya
Software Engineer at Intel Corporation
Russia
Summary
🤩
Rockstar🎓
Top SchoolMaria Kaglinskaya is a software engineer with six years of experience specializing in computer vision and neural network optimization at Intel Corporation. She contributes to the prominent openvinotoolkit/nncf project, focusing on filter pruning, model analysis, export functionality, and robustness fixes that improve inference efficiency. Her background combines hands-on engineering with academic teaching in probability, statistics, and data analysis, reflecting strong theoretical foundations and communication skills. Maria began as an intern accelerating CNN performance and has since delivered production-oriented improvements to model compression workflows. Known for adding tests and refactoring complex analysis code, she balances rigorous correctness with practical performance gains. Based in Russia and trained in applied mathematics and informatics, she brings a research-minded approach to industrial ML engineering.
5 years of coding experience
Bachelor's degree, Computer Science (Applied Mathematics and Informatics), 8.03, Bachelor's degree, Computer Science (Applied Mathematics and Informatics), 8.03 at Higher School of Economics
Russian, English
Github Skills (8)
pytorch10
machine-learning10
modeling10
python9
sparse9
compression9
quantization9
testing8
Programming languages (2)
Github contributions (4)
openvinotoolkit/nncf
Jun 2020 - Oct 2021
Neural Network Compression Framework for enhanced OpenVINO™ inference
Role in this project:
ML Engineer
ML EngineerContributions:97 reviews, 29 commits, 15 PRs in 1 year 3 months
Contributions summary:Maria primarily contributed to the `nncf` repository, a Neural Network Compression Framework, focusing on filter pruning and model analysis. Their work included implementing export functionalities related to pruning, adding and refactoring code for model analysis, and fixing issues related to gradients and batch normalization within the pruning framework. They also added tests to ensure the correctness of the pruning process.
bertsemantic-segmentationmixed-precision-trainingtensorflowclassification
mkaglins/nncf_pytorch
Jun 2020 - Oct 2021
Neural Network Compression Framework for PyTorch*
Contributions:92 pushes, 16 branches in 1 year 4 months
pytorchneural-network-compressiondeep-learningcompressionneural-network
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