Eugene Kuznetsov
Software Engineer at AMD
San Diego, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEugene Kuznetsov is a software engineer with 11 years of professional experience and a deep track record in video codec development, having led core work on DivX, DivX Plus (H.264) and multi-view 3D extensions. He combines low-level expertise in C/C++, assembly, CUDA and OpenCL with practical experience optimizing image-processing pipelines and building ultra-low-latency, ASIC-friendly codecs for wireless VR. At AMD he now focuses on enabling and optimizing TensorFlow on AMD GPUs, contributing test and stability fixes to the high-profile TensorFlow repository to improve GPU and Python integration. His background includes long tenures at Intel and early codec work at DivX, grounded by an M.S. in Physics from UC San Diego and foundational studies at MIPT. Colleagues describe him as a pragmatic systems engineer who bridges research-grade signal processing with production GPU tooling.
11 years of coding experience
18 years of employment as a software developer
University of California, San Diego-, Physics, -, Physics at Moscow Institute of Physics and Technology (State University) (MIPT)
Github Skills (10)
tensorflow10
gpu10
python10
testing10
machine-learning9
deep-learning8
deep-neural-networks7
neural-network6
cprogramming-language5
c-language5
Programming languages (10)
Github contributions (5)
tensorflow/tensorflow
Dec 2019 - Feb 2021
An Open Source Machine Learning Framework for Everyone
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:5 reviews, 54 commits, 54 PRs in 1 year 1 month
Contributions summary:Eugene primarily focuses on fixing and enabling unit tests within the TensorFlow repository, as evidenced by commit messages like "Fixing" and "Fix compilation errors." They re-enabled full tests, disabled failing subtests, and updated existing test files. Their contributions span various areas of the project, including core TensorFlow, Python components, and GPU-related functionalities. These changes ensure the proper functionality and stability of the machine learning framework.
pythondata-sciencedeep-learningmlmachine-learning
ekuznetsov139/tensorflow
Jul 2019 - Sep 2020
An Open Source Machine Learning Framework for Everyone
Contributions:33 pushes, 9 branches in 1 year 2 months
pythondata-sciencedeep-learningmachine-learningframework-learning
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