Andreas Kallinteris

Private (Electronic Warfare. Signal Intelligence)

Greece
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Summary

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Andreas Kallinteris is an AI and robotics engineer with eight years' experience combining high-performance code enthusiasm and practical systems work, currently maintaining Gymnasium MuJoCo environments and managing the Gymnasium-Robotics project at the Farama Foundation. He brings a strong technical writing focus to open-source reinforcement learning, clarifying action/observation spaces and reward functions for widely used benchmarks. Trained as an integrated Master in Electrical & Computer Engineering from the Technical University of Crete, he pairs rigorous academic grounding with hands-on troubleshooting and signal-intelligence experience in long-range surveillance systems. Comfortable working under pressure, he has a track record of reducing downtime through protocol improvements and enjoys bridging research-grade AI with production-quality implementations.
code8 years of coding experience
book(Integrated Master) - Electrical & Computer Engineering, Computer Engineering, 8.34/10, (Integrated Master) - Electrical & Computer Engineering, Computer Engineering, 8.34/10 at Technical University of Crete / Πολυτεχνείο Κρήτης
languagesGreek, English
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Stackoverflow

Stats
41reputation
1kreached
6answers
2questions
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Github Skills (11)

gymnasium10
mujoco10
api10
technical-writing10
reinforcement-learning8
openai-gym6
xml6
robotics6
cmake6
python6
numpy6

Programming languages (17)

C#JavaC++RustCValve Data FormatGoMustache

Github contributions (5)

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Farama-Foundation/Gymnasium

Oct 2022 - Jan 2023

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
Role in this project:
userTechnical Writer
Contributions:179 reviews, 10 commits, 178 PRs in 2 months
Contributions summary:Andreas primarily contributes by documenting and clarifying various aspects of the Gymnasium environment, specifically focusing on MuJoCo environments such as Ant, Humanoid, and Reacher. Their work includes fixing action descriptions, clarifying the observation space, and providing detailed explanations of reward functions, including the impact of `use_contact_forces`. The contributions are focused on improving clarity and accuracy within the documentation.
apiagentreinforcement-learningreinforcement-learning-agentgymnasium
A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)
Contributions:356 pushes, 13 branches in 2 years 5 months
apidiversereinforcement-learningreinforcementgym
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Andreas Kallinteris - Private (Electronic Warfare. Signal Intelligence)