Mohamed Elsayed

Student Researcher at Google DeepMind

Edmonton, Alberta, Canada
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Summary

👤
Senior
🎓
Top School
Mohamed Elsayed is a PhD student and student researcher at the University of Alberta (affiliated with Amii) focusing on scalable, real-time learning from continuous experience, with published work at NeurIPS, ICML, and ICLR. His research tackles streaming deep reinforcement learning, continual learning, and efficient recurrent architectures, blending model-free and model-based approaches to enable lifelong adaptation. He brings a decade of experience spanning academia and industry, including internships applying deep RL to self-driving vehicles and a current research post at Google DeepMind. A seasoned instructor for foundational computing and reinforcement learning courses, he pairs strong teaching skills with hands-on research deployment. Notably, his background in visual SLAM and biomedical signal projects highlights a breadth across perception and sequential modeling beyond core RL.
code11 years of coding experience
bookDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at University of Alberta
bookBachelor's degree, Communication and Information Engineering, Bachelor's degree, Communication and Information Engineering at Zewail City of Science and Technology
bookElectronics and Communications Engineering, Electronics and Communications Engineering at Cairo University
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Github Skills (11)

batch-updates10
optimization-methods9
optimizer9
hessian9
deep-reinforcement-learning8
reinforcement-learning8
pytorch7
machine-learning7
deep-learning7
ros4
artificial-intelligence1

Programming languages (3)

C++CMakePython

Github contributions (5)

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mohamedelsayed95/goselo-ros

May 2019 - Jun 2019

Contributions:66 commits in 28 days
mohmdelsayed/HesScale

Oct 2021 - Mar 2023

Scalable Computation of Hessian Diagonals
Contributions:115 commits, 6 PRs, 70 pushes in 1 year 4 months
hessianoptimizerdeep-learningoptimization-methodspytorch
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