Open to new opportunities
Robotics R&D Engineer and Data Scientist based in Paris, France. Working on autonomous systems, ML pipelines, and digital twins — currently at Airbus via Accenture.
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About
I'm a Robotics R&D Engineer and Data Scientist with a Master's degree in Advanced Robotics from École Centrale de Nantes and over 8 years of engineering experience spanning Lebanon, France, and international aerospace projects.
My work lives at the intersection of autonomous systems, machine learning, and cloud-connected solutions. I design robots, train models, build digital twins in NVIDIA Omniverse, and validate concepts through physics-based simulation before they ever touch the factory floor.
At Airbus (via Accenture), I've contributed to TRL6 milestones on aircraft assembly automation, pioneered mobile robotics concepts for next-gen aircraft production, and engineered motion-control systems for Stewart platforms — all backed by rigorous data analytics.
Experience
March 2023 — Present
Robotics R&D Engineer & Data Scientist
Airbus · Accenture — Saint-Nazaire, France
October 2021 — February 2023
Industrial Architect R&D Engineer
Airbus · Umlaut (Part of Accenture) — Saint-Nazaire, France
February 2021 — August 2021
Robotics Research Intern
LS2N (Laboratoire des Sciences du Numérique de Nantes) — Nantes, France
November 2016 — August 2019
Project Engineer & Head of Technical Department
Quest-4 — Beirut, Lebanon
Skills
Education
M.Sc. Control & Robotics — Advanced Robotics
École Centrale de Nantes — Nantes, France
GPA: 3.48 / 4.0 · Rank: 6 / 43
Sep 2019 — Aug 2021
B.Eng. Mechanical Engineering
Notre Dame University-Louaize — Lebanon · Minor: Engineering Management
Senior Project: Solar-assisted fixed-wing aircraft design & implementation.
Sep 2011 — Aug 2016
Certifications
Solutions Architect — Associate
Amazon Web Services — April 2026
Valid until April 2029
Deep Learning Specialization
deeplearning.ai — February 2025
Machine Learning Specialization
deeplearning.ai — April 2024
Featured Project
Master's Thesis · LS2N · 2021
Quadrotor Trajectory Planning
in Confined Spaces via MPC
Designed a Model Predictive Control framework for autonomous quadrotor navigation in GPS-denied, cluttered environments. The algorithm incorporates drone dynamics, robustness criteria, and real-time re-planning — validated through Gazebo/ROS2 simulation and live experimental flights.
Languages
Contact
Let's build something
intelligent.
Whether it's a robotics system, an ML pipeline, a cloud-connected solution, or a collaboration on the next frontier of autonomous systems — I'd love to hear about your project.
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