Alexey Kruglov
Warsaw, Masovian Voivodeship, Poland
Summary
🤩
Rockstar🎓
Top SchoolAlexey Kruglov is a deep learning engineer with 11 years of technical experience and 7 years focused on ML research and development across computer vision and speech recognition. He has a strong academic foundation (MSc in Physics) and a background in theoretical physics, which informs rigorous experimental design and original research that produced publications and patents. At Intel and OpenCV.ai he shipped production-grade PyTorch/C++ code, improved tracking quality by ~1.5x, and accelerated a C++ tracker pipeline ~2x, while contributing speech-recognition metric fixes and demos to the widely used Open Model Zoo. He combines hands-on model selection, implementation of research papers, quantization/pruning R&D, and deployment experience, plus mentoring and cross-team coordination. A former competitive programmer with math and physics contest prizes, he adapts quickly to new domains and is ready to grow into new roles.
11 years of coding experience
9 years of employment as a software developer
Master of Science - MS, Physics, with distinction (5.000 of 5.0), Master of Science - MS, Physics, with distinction (5.000 of 5.0) at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
English, Russian, Polish
Stackoverflow
61reputation
2kreached
1answer
0questions
Github Skills (12)
machine-learning10
speech-recognition10
deep-learning10
inference10
modello10
python10
openvino10
tensorflow9
cnn-model9
cprogramming-language7
c-language7
cuda6
Programming languages (4)
Github contributions (5)
openvinotoolkit/open_model_zoo
Aug 2020 - Jun 2021
Pre-trained Deep Learning models and demos (high quality and extremely fast)
Role in this project:
ML Engineer
ML EngineerContributions:96 reviews, 28 commits, 11 PRs in 9 months
Contributions summary:Alexey primarily contributed to the accuracy and functionality of speech recognition metrics within the Open Model Zoo repository, focusing on metrics like Word Error Rate (WER) and Character Error Rate (CER). Their work involved fixing and improving the implementations of these metrics, renaming and adding functionalities. The user also added a speech recognition demo and integrated adapters for CTC decoding with a language model, and integrated a public model. Further contributions involved fixing pylint warnings and adapting the project for Windows.
modelonnx-modelsdeep-learning-modelsmodel-zoopytorch-models
AlexeyKruglov/open_model_zoo
Aug 2020 - May 2021
Pre-trained Deep Learning models and samples (high quality and extremely fast)
Contributions:47 pushes, 14 branches in 9 months
pytorchcaffe2deep-learningunet-image-segmentationpre-trained
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