Gamaleldin Elsayed
Principal Applied Scientist at Amazon
Mountain View, California, United States
Summary
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Senior🎓
Top SchoolGamaleldin Elsayed is a Principal Applied Scientist specializing in AGI at Amazon with a decade of research and engineering experience across DeepMind and Google Brain. He holds a PhD in Neurobiology and Behavior from Columbia and blends deep neuroscience insight with practical ML engineering, having contributed ML code and loss-function implementations to high-profile Google Research projects. His trajectory—from brain residency to senior research roles—reflects expertise in bridging theoretical models and scalable experiments, including hands-on work reproducing and open-sourcing research experiments (e.g., MNIST large-margin loss integrations). Based in Mountain View, he brings a quantitative signal-processing background and a track record of moving ideas from lab studies to production-ready code.
10 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.Sc.) Electrical and Electronics Engineering, Bachelor of Science (B.Sc.) Electrical and Electronics Engineering at The American University in CairoMaster of Science (MS) Electrical Engineering, Master of Science (MS) Electrical Engineering at KAUST (King Abdullah University of Science and Technology)Master of Science (MS) Electrical and Systems Engineering, Master of Science (MS) Electrical and Systems Engineering at Washington University in St. LouisDoctor of Philosophy (PhD) Neurobiology and Behavior, Doctor of Philosophy (PhD) Neurobiology and Behavior at Columbia UniversityExchange Student Electrical and Computer Engineering, Exchange Student Electrical and Computer Engineering at Rose-Hulman Institute of Technology
Arabic, English
Github Skills (7)
machine-learning10
tensorflow10
python10
deep-learning9
mask-rcnn9
faster-rcnn9
mnist8
Programming languages (2)
Github contributions (5)
google-research/google-research
Oct 2018 - Jan 2021
Google Research
Role in this project:
ML Engineer
ML EngineerContributions:19 commits in 2 years 3 months
Contributions summary:Gamaleldin primarily contributes to the development and implementation of machine learning techniques within the Google Research repository. Their work focuses on the large margin loss function, including open-sourcing the code from a research paper, adding new loss function options, and integrating a data provider and model specifically for MNIST experiments. Furthermore, the user made modifications to the loss, train, and eval scripts to better match the MNIST experiments of the paper.
googlemachine-learningai
gamaleldin/CFR
Jan 2017 - Apr 2017
Contributions:32 commits, 34 pushes, 1 branch in 3 months
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