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Amr El-Azizi
Mid-level Robotics Software Engineer specializing in simulation, embedded systems, and robot learning
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About
Robotics engineer who built a 6-axis force-torque sensor system end-to-end at ROAM Lab, including electronics, low-level drivers, and ROS2 live inference with time-series deep learning (ultimately a 1D ResNet) to handle highly noisy, session-shifting signals. Also upgraded tactile manipulation models to time-series inputs by modifying long-standing ROS architectures, and has prior experience in defense (L3Harris) with production-grade testing and code review practices; published work: arxiv.org/abs/2410.03481.
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Key Strengths
- End-to-end robotics system ownership (mechanical concept → electronics → drivers → ML → ROS/ROS2 integration)
- Robust ML for noisy, session-varying sensor signals via improved data collection and time-series modeling
- Designed ROS2 infrastructure for live inference from embedded device to laptop with visualization tooling
- Successfully migrated interfaces to support time-series inputs (new ROS pubs/subs and backend changes) while maintaining parallel code branches
- Methodical real-time reliability approach: staged hardware testing, test cases, and code reviews (L3Harris)
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