Evgeniy Vasilyev
PhD Candidate
Nizhny Novgorod, Nizhny Novgorod Oblast, Russia
Summary
👤
Senior🎓
Top SchoolEvgeniy Vasilyev is a QA engineer and PhD candidate with over a decade of experience in software projects and 3+ years of commercial QA practice, including more than two years in fintech. He combines hands-on manual and API testing across web and mobile platforms with practical skills in SQL, Kafka, Grafana, Jenkins and OpenShift, and has supported UI automation in Java/Selenium. Evgeniy has worked on high-profile banking and enterprise projects, managing test cycles, CI deployments and complex log/metric analysis to keep releases stable. Beyond QA, he has iOS development experience and contributes to open-source ML tooling—adding a style transfer model to OpenVINO’s model zoo—demonstrating an ability to bridge testing, development and ML integration. As a teacher assistant and PhD student in Nizhny Novgorod, he pairs academic rigor with pragmatic engineering, often digging into logs and mock services to reproduce hard-to-find issues. Practical, detail-oriented, and curious, he thrives on implementing reliable processes that make complex systems observable and testable.
11 years of coding experience
3 years of employment as a software developer
Диплом специалиста по инженерной специальности, транспортные комплексы, Диплом специалиста по инженерной специальности, транспортные комплексы at Moscow State Automobile and Road Technical Institute (State Technical University) (MADI)
English, Russian
Github Skills (8)
computer-vision10
deep-learning10
modello10
python10
openvino10
style-transfer10
cnn-model9
inference8
Programming languages (4)
Github contributions (5)
openvinotoolkit/open_model_zoo
Feb 2020 - May 2020
Pre-trained Deep Learning models and demos (high quality and extremely fast)
Role in this project:
ML Engineer
ML EngineerContributions:28 commits, 6 PRs, 35 comments in 3 months
Contributions summary:Evgeniy contributed to the implementation and integration of a style transfer model within the accuracy checker framework. Their work involved adding a new style transfer model, including relevant annotation converters, adapters, metrics, and postprocessors to the accuracy checker tool. They also addressed PyLint warnings and made minor fixes, indicating a focus on code quality and integrating a new model type within the OpenVINO ecosystem.
deep-learningmodelscaffemodeltensorflow-modelsmodel-zoo
itlab-vision/CV-WINTER-CAMP-2021
Jan 2021 - Feb 2021
COMPUTER VISION WINTER CAMP
Contributions:25 commits, 25 pushes in 28 days
computer-vision
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