Abdelaziz Zayed
Teaching Assistant at McGill University
Montreal, Quebec, Canada
Summary
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Rockstar🎓
Top SchoolAbdelaziz Zayed is a software engineer and teaching assistant at McGill University with seven years of experience spanning compilers, machine learning, and production engineering. He researches domain-agnostic compiler optimizations and presented work on optimizing MLIR programs with equality saturation at CGO 2025, while also TA-ing a Compiler Design course where students build a C-subset compiler from scratch. His internships at Amazon, AWS (contributing to the popular Deep Java Library), NVIDIA, and Morgan Stanley reflect hands-on impact in ML model deployment, deep-learning frameworks, and compute-graph engineering. Abdelaziz combines strong theoretical grounding in programming languages with practical systems work—implementing PyTorch/TensorFlow operators and demos for generative models—and a passion for math and teaching that informs both research and developer-focused contributions.
7 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Compilers and Programming Languages, Master of Science - MS, Compilers and Programming Languages at McGill University
English, French
Github Skills (10)
javas10
pytorch10
machine-learning10
deep-learning10
tensorflow10
ndarray10
ai10
java10
image-generation9
computer-vision9
Programming languages (8)
Github contributions (5)
deepjavalibrary/djl
May 2021 - Aug 2021
An Engine-Agnostic Deep Learning Framework in Java
Role in this project:
ML Engineer
ML EngineerContributions:7 reviews, 17 commits, 23 PRs in 3 months
Contributions summary:Abdelaziz primarily contributed to adding and improving deep learning operations within the DJL framework, specifically focusing on PyTorch and TensorFlow integrations. Their work included implementing the `truncatedNormal` and `oneHot` operators for TensorFlow and PyTorch, respectively, alongside bug fixes and integration tests. Further contributions involve the addition of a BigGAN demo with clean-up and documentation improvements, and a super-resolution demo for TensorFlow. This indicates a focus on expanding the framework's capabilities related to image generation and enhancement.
deep-learningjavaneural-networkaimxnet
AzizZayed/Snake
Jun 2019 - Apr 2020
Contributions:20 commits, 4 pushes in 10 months
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