Dmitry Khurtin
Senior Developer at Kaspersky Lab
Russia
Summary
🤩
Rockstar🎓
Top SchoolDmitry Khurtin is a senior developer with over a decade of professional experience and roughly five years focused on modern software and ML-related back-end work. Based in Russia and currently at Kaspersky Lab, he develops and maintains Windows B2B products, drawing on a strong applied mathematics and computer science background. Dmitry is an active contributor to OpenVINO, where he has improved GNA (Gaussian Neural Accelerator) integration—tackling performance, accuracy and build-system issues that bridge low-level hardware inference and high-level model workflows. His blend of production security software experience and hands-on ML inference engineering gives him a pragmatic edge in optimizing real-world AI deployments. Notably, he has deep CMake and dependency-handling expertise that helps stabilize complex multi-component builds in large open-source toolkits.
5 years of coding experience
6 years of employment as a software developer
Магистр, Прикладная математика и информатика, Магистр, Прикладная математика и информатика at Peoples' Friendship University of Russia/Российский Университет Дружбы Народов (РУДН)
Github Skills (9)
c-language10
inference10
cprogramming-language10
openvino10
optimization9
cmake9
deep-learning8
ai7
computer-vision7
Programming languages (2)
Github contributions (5)
openvinotoolkit/openvino
Apr 2021 - Apr 2022
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
Role in this project:
Back-end Developer / ML Engineer
Back-end Developer / ML EngineerContributions:107 reviews, 24 commits, 32 PRs in 11 months
Contributions summary:Dmitry primarily focused on updating and improving the GNA (Gaussian Neural Accelerator) library within the OpenVINO toolkit. Their contributions include updating the GNA library to new versions, modifying dependency handling in the CMake build system, and addressing performance and accuracy issues, specifically around the integration of the GNA library with OpenVINO. These changes appear to involve optimizing and fixing bugs related to how neural network models are executed on GNA hardware. The user also addressed specific issues in model conversion and execution, showcasing deep understanding of the OpenVINO framework.
inference-enginepytorchmodel-optimizerdeep-learninggpu
dmitriikhurtin/openvino
Apr 2021 - Apr 2022
OpenVINO™ Toolkit repository
Contributions:157 pushes, 34 branches, 1 comment in 11 months
pytorchdeep-learninggpuopenvino-toolkitcomputer-vision
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