Alaa Saade
Research Engineer at DeepMind
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolAlaa Saade is a research engineer based in Paris with 11 years of experience applying theoretical physics and machine learning to real-world systems, currently working at DeepMind. He holds a PhD in Machine Learning and Statistical Physics from École normale supérieure and has a track record of translating rigorous theory into practical algorithms for clustering, community detection and matrix completion. Previously he built on-device NLU and speech models as a Senior Machine Learning Scientist at Snips, focusing on resource-efficient deep learning for offline devices. As an active contributor to the tract project, he has deep experience implementing and debugging ONNX/TensorFlow inference operators and improving low-level tensor handling for production-grade neural network runtimes. His background bridging statistical physics, numerical modeling (including work on materials and plasma) and applied ML gives him a rare combination of theoretical depth and systems-level engineering. Colleagues describe him as a pragmatic researcher who prefers compact, robust solutions that scale from prototype to deployment.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Machine Learning and Statistical Physics, summa cum laude, Doctor of Philosophy (Ph.D.), Machine Learning and Statistical Physics, summa cum laude at Ecole normale supérieureClasses préparatoires, Mathématiques et Physique, Classes préparatoires, Mathématiques et Physique at Lycée Henri IVEngineering degree, Theoretical Physics and Mathematics, Engineering degree, Theoretical Physics and Mathematics at École PolytechniqueMaster 2, Theoretical Physics and Mathematics, summa cum laude, Master 2, Theoretical Physics and Mathematics, summa cum laude at École normale supérieure
French, English, Arabic, Spanish
Github Skills (10)
neural-network10
rust-lang10
artificial-intelligence10
rust10
tensorflow10
onnx10
data-manipulation9
algorithms8
algorithm8
implement8
Programming languages (2)
Github contributions (5)
sonos/tract
Feb 2019 - Mar 2019
Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:25 commits, 3 PRs, 7 pushes in 15 days
Contributions summary:Alaa contributed significantly to the `tract` repository, focusing on implementing and integrating ONNX operators. They added support for the `ConstantOfShape` and `Gather` operators, enhancing the library's capabilities for neural network inference. Furthermore, the user's work involved fixing dimension checks and type conversion errors. The commits also included refactoring and optimizing aspects of the concatenation operations and improving the overall flexibility of the system.
rust-libraryno-nonsenseself-containedrustdeep-learning
alaa-saade/BetheHessian.jl
Jul 2015 - Oct 2015
Contributions:24 commits, 14 pushes, 3 branches in 3 months
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