Adrien Hadj-salah
Fondateur
Toulouse, Occitania, France
Summary
👤
Senior🎓
Top SchoolAdrien Hadj-salah is a founder and aerospace AI expert based in Toulouse with 11+ years turning space mission design from slow, bespoke practice into automated, validated engineering workflows. He led a 15–20 person computer vision team at Airbus Defence and Space building end-to-end AI for autonomous spaceflight and Earth observation, and earlier developed mission planning and optimization algorithms for satellite constellations. At Vecteur he marries domain tools (NASA SPICE, Orekit) with AI to compress concept-to-PDR cycles from months to hours, reflecting a pragmatic focus on engineering velocity and verifiable outputs. His background spans research in deep reinforcement learning for EO planning and hands-on systems work across RF/SIGINT simulation and ground-segment deployments, so he equally speaks the languages of algorithms, simulation, and production engineering. Known for obsessively enabling engineers to design space missions, he combines academic training from ENAC and TU Berlin with founder-level product execution.
11 years of coding experience
BAC, BAC at Lycée le bon sauveurMaster's degree, Air and Space Operations Technology, Master's degree, Air and Space Operations Technology at Technische Universität BerlinMaster's degree, Engineering, Master's degree, Engineering at ENAC - Ecole Nationale de l'Aviation CivilePrépa math sup math spé, Prépa math sup math spé at Jeanne d'Albret
English, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
q-learning8
gymnasium8
reinforcement-learning7
deep-reinforcement-learning7
pytorch6
deep-learning6
machine-learning6
openai4
rl-environment3
scheduling2
dynamics1
Programming languages (2)
Github contributions (5)
Hadjubuntu/breeze-bb
Apr 2016 - Oct 2017
Contributions:564 pushes, 5 branches, 1 tag in 1 year 6 months
Hadjubuntu/baby_env
Feb 2020 - Mar 2020
A simple RL environment to mock EO scheduling
Contributions:40 commits, 94 pushes, 24 branches in 27 days
mockreinforcement-learningrl-environmentscheduling
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