Pavel Druzhkov
Principal Engineer at Huawei
Russia
Summary
🤩
Rockstar🎓
Top SchoolPavel Druzhkov is a Principal Engineer with 12 years of deep expertise in computer vision and deep learning, currently leading R&D efforts at Huawei after a long tenure at Intel where he progressed from software engineer to AI research scientist. He has a strong academic foundation in applied mathematics and discrete mathematics (PhD studies) and a track record of taking state-of-the-art models from research to production via ONNX/OpenVINO toolchains and training extensions. His hands-on contributions to the high-profile open_model_zoo show practical impact—updating instance segmentation, action recognition and detection demos and improving accuracy checker support for new models. Pavel’s work spans instance segmentation, pose estimation, action recognition and interactive segmentation, and he’s comfortable across the stack from algorithm design to deployment optimizations. Colleagues value his blend of rigorous research background and pragmatic engineering that consistently enables SOTA models for real-world use.
12 years of coding experience
9 years of employment as a software developer
PhD student, Discrete Mathematics and Mathematical Cybernetics, PhD student, Discrete Mathematics and Mathematical Cybernetics at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Github Skills (9)
computer-vision10
deep-learning10
python10
openvino9
ml9
modello9
inference9
mle9
cnn-model7
Programming languages (3)
Github contributions (5)
openvinotoolkit/open_model_zoo
Apr 2019 - Feb 2021
Pre-trained Deep Learning models and demos (high quality and extremely fast)
Role in this project:
ML Engineer
ML EngineerContributions:27 reviews, 60 commits, 21 PRs in 1 year 10 months
Contributions summary:Pavel contributed to the `open_model_zoo` repository, focusing on improving and updating demo applications related to deep learning models. This involved updating the instance segmentation demo, action recognition demo, and the object detection demo. The user also worked on enabling and improving support for various models within the accuracy checker, including person-detection-0106 and fixing typos in accuracy checker components related to action recognition.
modelonnx-modelsdeep-learning-modelsmodel-zoopytorch-models
itseez-academy/itseez-ss-2016-practice
Jun 2016 - Jul 2016
Contributions:46 commits, 23 PRs, 11 pushes in 14 days
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