Moamen Abdelrazek
AI Engineering Manager at SETS
Montreal, Quebec, Canada
Summary
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Rockstar🎓
Top SchoolMoamen Abdelrazek is an AI Engineering Manager based in Montreal with 10 years of experience building production-grade machine learning systems across NLP and computer vision. He has led teams at RBC and now SETS, bringing research rigor to industry—evidenced by 8+ papers at top ML venues like NeurIPS and CVPR—while shipping practical solutions that prioritize user impact. Hands-on in PyTorch, he maintains a scalable project template used for segmentation, classification, GANs and RL, and has contributed model integrations and training improvements such as ERFNet weighted loss support. A competitive programmer who values clean code, Moamen bridges cutting-edge research and reliable deployment, ensuring models not only perform in benchmarks but delight customers in daily use.
10 years of coding experience
8 years of employment as a software developer
High School, Science and Maths, 414/410, High School, Science and Maths, 414/410 at Modern Narmer Language SchoolBachelor’s Degree, Computer Engineering, Very Good, Bachelor’s Degree, Computer Engineering, Very Good at Cairo University
English, Arabic
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (6)
semantic-segmentation10
pytorch10
machine-learning10
deep-learning10
python10
dqn8
Programming languages (2)
Github contributions (5)
moemen95/Pytorch-Project-Template
Mar 2018 - May 2021
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 17 commits, 3 PRs in 3 years 2 months
Contributions summary:Moamen's contributions primarily focused on integrating and modifying deep learning models within the PyTorch project template. They added support for the ERFNet model, a semantic segmentation architecture, and addressed a warning in the summary writer. Furthermore, the user implemented weighted loss calculations for ERFNet, enhancing the training process. The user also made modifications to the DQN agent and the CondenseNet agent files, reflecting ongoing developments and testing.
image-segmentationpytorch-project-templatescemanticreinforcementclassification
moemen95/Webville-Furniture-Studio
Aug 2020 - Sep 2020
Contributions:25 pushes, 1 branch in 1 month
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