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FrancoisPorcher/README.md

👋🏻 Welcome to my GitHub!

Hi there! I'm François, a Research Scientist in Artificial Intelligence at Meta from 🇫🇷 and 🇪🇸

My ambition is to push the boundaries of AI, especially in highly impactful areas: Healthcare, Neurosciences, Ecology, and Energy.

🚀 About Me

  • 🏢 Currently a Research Scientist intern at Meta (FAIR).
  • 🎓 Alumnus of UC Berkeley (❤️☀️), where I earned my Master's degree in AI/Computer Sciences in May 2023. I also obtained Bachelor of Science in Engineering from CentraleSupelec.
  • 📚 And for a bit of fun, I challenged myself to get a Master’s in Pure Mathematics from Paris Saclay, which is one of the toughest Mathematics curriculum. Was fun, but quite hard ngl haha
  • ✏️ Author: I share insights and research on my Medium Blog.
  • 🎸 Hobbies: I enjoy shredding on the electric guitar, hiking, and staying active with sports (🏋️‍♂️, 🏃‍♂️, 🏊‍♂️). I also love learning new languages! I currently speak 🇫🇷, 🇪🇸, 🇬🇧 fluently, and I’m currently focusing on 🇩🇪 and 🇮🇹.

🔭 Core Research Interests

  • Representation Learning
    Joint Embedding Spaces, Hierarchical representations, Cross-modal integration.
  • Uncertainty Estimation
    Calibration, search optimization, long-term planning.
  • Self-Supervised Learning
    Masking, Contrastive learning, and generative approaches.
  • Multimodal Learning
    Robust zero-shot learning, representation fusion.
  • Explainable AI (XAI)
    Neural network interpretability, decision-making transparency.

🌐 Let's Connect!

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  1. awesome-ai-tutorials awesome-ai-tutorials Public

    The best collection of AI tutorials to make you a boss of Data Science!

    Jupyter Notebook 62 16

  2. Simulated-Bifurcation Simulated-Bifurcation Public archive

    Simulated Bifurcation (Quantum Physics model for Ising models) to find heuristics for NP hard problems with great computational efficiency

    Python 7 4

  3. vit-pytorch vit-pytorch Public

    A Pytorch implementation of ViT

    Python 1

  4. calibration_curve calibration_curve Public

    Pushing classifiers to their limits by chaining a second model to calibrate probabilities

    Jupyter Notebook 3