Peyman Khademi
Software Engineer at Microsoft
Iran
Summary
🤩
Rockstar🎓
Top SchoolPeyman Khademi is a software engineer with eight years of experience specializing in back-end development and machine learning interoperability. He has contributed to high-profile open-source projects like ONNX and Microsoft CNTK, improving test coverage for operator nodes and refining model export logic to ensure correct initializer handling. Based in Iran and working at AraminIt Group, Peyman combines practical QA/test-automation skills with model conversion expertise, helping bridge deep learning frameworks and production workflows. Notably, his work on opset converter backward compatibility and initializer representation has strengthened the stability of ML model interchange across ecosystems.
8 years of coding experience
BS, BS at Isfahan University of Technology
English
Github Skills (18)
python10
testing10
machine-learning10
test-framework10
cntk10
onnx10
numpy10
deeplearning-ai10
deep-learning10
cplus10
cpp10
test-automation10
deep-neural-networks9
neural-network9
keras8
Programming languages (3)
Github contributions (5)
onnx/onnx
Feb 2018 - Apr 2019
Open standard for machine learning interoperability
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:9 commits, 32 PRs, 1 push in 1 year 2 months
Contributions summary:Peyman primarily contributed to the testing framework of the ONNX repository, focusing on node operator tests. They added tests for various operations, including `transpose`, `reshape`, `concat`, `cast`, `split`, and `lstm`. The user also worked on adapting the testing framework to support opset converter backward compatibility. Their work improved the test coverage and stability of the ONNX project, ensuring that new features and changes integrate well with existing functionality.
pytorchmxnetdeep-learninginteroperabilitymachine-learning
microsoft/CNTK
May 2018 - Jan 2019
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:51 commits, 46 pushes, 21 branches in 8 months
Contributions summary:Peyman's commits primarily focus on modifying code related to the conversion of CNTK models to the ONNX format, specifically dealing with initializing parameters and constants during the saving process. The changes involve altering how initializers are handled, ensuring the correct representation of model parameters within the ONNX graph. These modifications indicate a focus on ensuring the proper export and interoperability of deep learning models developed using CNTK.
pytorchpythondeep-learningc-plus-plusmachine-learning
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