Andrii Tuzhykov
Machine Learning Engineer at Samsung Electronics Ukraine
Chernivtsi, Chernivtsi Oblast, Ukraine
Summary
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Top SchoolAndrii Tuzhykov is a Machine Learning Engineer with eight years of experience blending a strong math and theoretical physics background with practical ML and data science skills. He has applied physics-style modeling tools (COMSOL, Mathematica, Matlab) early in his career and now designs and validates ML systems using TensorFlow, PyTorch, fastai and JVM-based deeplearning4j workflows. Currently at Samsung Electronics Ukraine, Andrii has past roles in NLP and ML consulting and contributes regression testing and model verification work to notable open-source projects like deeplearning4j. He is comfortable across the stack—Python/Django/Flask for web, R and pandas for data work—and has domain exposure to computer vision and NLP. Outside engineering he brings project and cultural management experience from EU-funded civic initiatives and is the author of a book exploring technology’s role in everyday life.
7 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Software Engineering, Bachelor's degree, Software Engineering at Chernivci National 'Juriy Fedkovyc' University
Stackoverflow
1reputation
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Github Skills (9)
neural-network10
javas10
deeplearning4j10
artificial-intelligence10
regression-testing10
deep-learning10
neural10
java10
gpu8
Programming languages (5)
Github contributions (5)
deeplearning4j/deeplearning4j
Feb 2020 - May 2020
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
Role in this project:
ML Engineer
ML EngineerContributions:8 commits, 13 PRs, 2 comments in 3 months
Contributions summary:Andrii primarily contributes to regression testing within the deeplearning4j project, focused on validating the behavior of different neural network configurations. Their work involves porting and adapting existing test cases, specifically by copying and renaming test files. They also make minor adjustments to the test code, such as changing assertion types, and adding new namespaces. The user's commits test model implementations, including custom layers, LSTMs, and VAEs.
deeplearning4jpythonautomatic-differentiationneural-netskeras-tensorflow
KonduitAI/deeplearning4j-examples
Feb 2020 - Mar 2020
Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)
Contributions:87 commits, 1 PR, 46 pushes in 20 days
deeplearning4jdeep-learningspark-mlmachine-learningspark
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