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title: Arthur Danjou • Mathematics Lover and IA Enthusiast
description: I'm Arthur, a Mathematics lover and IA enthusiast. I'm currently
  studying at the University of Paris-Saclay. I'm passionate about Mathematics,
  Computer Science, and Artificial Intelligence.
---

Hey, I'm :home-name, a Master 2 student in Statistical & Financial Engineering (Master ISF) at Paris-Dauphine University.

I sit at the intersection of :hover-text{hover="Learning Theory, RL & Advanced ML 🧠" position="top" text="theoretical research"} and :hover-text{hover="From MLOps to Production 🚀" position="right" text="software engineering"}. Unlike a pure theorist, I build what I model. Unlike a pure developer, I understand the math behind the code.

I am currently pivoting towards :hover-text{hover="Alignment, Robustness & Interpretability 🧭" text="Research in AI Safety"}. I will soon start my Master's Thesis focusing on :hover-text{hover="Robustness & Adversarial Defenses 🛡️" text="Cybersecurity"} and :hover-text{hover="Ensuring AI alignment and stability 🤝" text="Safe Deep Learning"}, exploring how to make AI systems mathematically robust and secure.

To support this research, I leverage
:prose-icon[Python]{color="amber" icon="i-logos:python"},
:prose-icon[PyTorch]{color="orange" icon="i-logos:pytorch-icon"} and
:prose-icon[R]{color="blue" icon="i-logos:r-lang"} to design robust architectures, using tools like
:prose-icon[Docker]{color="sky" icon="i-logos:docker-icon"} and
:prose-icon[Linux]{color="zinc" icon="i-logos:linux-tux"} to ensure reproducibility in my :hover-text{hover="I self-host my own GPU cluster 🔌" text="homelab"}.

When I'm not working on generalization bounds or fixing pipelines, I enjoy :hover-text{hover="Former Team Captain 🏉" text="Rugby"} and :hover-text{hover="Exploring the world 🌍" text="Traveling"}.

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## 🛠 Scientific & Technical Arsenal

My research capabilities rely on a **dual expertise**: advanced mathematical modeling for conception, and robust engineering for execution.

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## 💼 Research & Engineering Path

Theoretical knowledge is nothing without concrete application. From building distributed systems to designing defensive AI pipelines, my journey reflects a constant shift towards more complex and critical challenges.

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## 🎓 Academic Foundation

Mathematical rigor is the cornerstone of Safe AI. My background in **Statistics, Probability, and Optimization** provides the necessary tools to understand and secure modern Deep Learning architectures.

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## 📊 Continuous Integration

Research requires discipline. Whether I am fine-tuning a model or maintaining my infrastructure, I believe in consistency and transparency.

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