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πŸ‘‹ Hi, I'm Nicolas Drapier

AI PhD Student | Deep Learning Researcher | Polyglot Developer

I'm a passionate AI researcher working at the intersection of deep learning, computer vision, and natural language processing. My research leverages PyTorch and Hugging Face Transformers to tackle real-world challenges in satellite imagery and spatio-temporal forecasting.

When I'm not training models, I build high-performance systems using Rust, Go, and Kotlin, always aiming for efficiency, safety, and scalability.

πŸ› οΈ Tech Stack

  • AI/ML: PyTorch, Transformers
  • Languages: Python, Rust, Go, Kotlin
  • Tools: Git, Linux, Docker, Jupyter

πŸ“š Research Interests

  • Deep Learning & Representation Learning
  • Computer Vision (Satellite Imagery)
  • Natural Language Processing & Causal Modeling
  • Efficient Neural Architectures

πŸ“„ Publications

Combining Transformers and CNNs for Efficient Object Detection in High-Resolution Satellite Imagery

ICCV 2025
πŸ‘‰ Paper Link We propose a hybrid architecture that leverages the global context of Transformers and the local feature extraction power of CNNs to achieve state-of-the-art efficiency and accuracy in detecting objects in large-scale satellite images.

Enhancing Maritime Trajectory Forecasting via H3 Index and Causal Language Modelling (CLM)

TMLR 2025
πŸ‘‰ Paper Link We reformulate vessel trajectory prediction as a language modeling task using Uber’s H3 geospatial indexing system and adapt Causal Language Models to capture complex navigational patterns with strong generalization.

πŸ“« Let's Connect

Open to research collaboration, open-source contributions, or technical discussions!

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"The best way to predict the future is to invent it." – Alan Kay

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