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manjavacas/README.md

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Hi there πŸ‘‹

PhD in Information and Communication Technologies at the University of Granada. My research focuses on applying Deep Reinforcement Learning to solve real-world optimization problems, particularly in building energy management.

πŸ”¬ Research interests

  • (Deep) Reinforcement Learning
  • Building Energy Optimization
  • HVAC Control
  • Safe & Trustworthy AI
  • Digital Twins
  • Energy Efficiency

πŸš€ Working on...

  • 🏒 Reinforcement Learning for real-world HVAC control and building energy optimization.
  • 🌱 Developing and maintaining Sinergym, an open-source benchmark connecting RL agents with EnergyPlus simulations.
  • πŸ“š Research on trustworthy deployment of RL agents in safety-critical systems.

πŸ› οΈ Technologies

Python β€’ PyTorch β€’ Gymnasium β€’ Stable-Baselines3 β€’ EnergyPlus
Docker β€’ Linux β€’ Git β€’ CI/CD β€’ Scientific Computing

🌍 Open Source

I enjoy building reproducible research software and contributing tools that bridge the gap between AI research and real-world engineering applications.

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  1. ugr-sail/sinergym ugr-sail/sinergym Public

    Gym environment for building simulation and control using reinforcement learning

    Python 234 58

  2. typslides typslides Public

    Minimalistic Typst slides.

    Typst 108 14

  3. melgym melgym Public

    Gymnasium-based interface for continuous control using MELCOR.

    Python 13 1

  4. melkit melkit Public

    MELCOR file manipulation toolkit.

    Python 5 1

  5. cloudy cloudy Public

    CLOUDY automates the execution of experiments on Google Cloud.

    Shell 4

  6. rl-temario rl-temario Public

    Temario sobre aprendizaje por refuerzo en espaΓ±ol.

    Typst 5 1