Hey, I'm Arthur Danjou, an and a .
I work at the intersection of and . Unlike a pure theorist, I ship what I model. Unlike a pure developer, I understand the math behind the code.
My current work is dedicated to . Through my M2 internship, I focus on and .
To drive this research, I leverage Python, PyTorch and LaTeX to document and formalize architectures, relying on Docker and Linux to ensure reproducibility within my .
When I'm not debugging training dynamics or refining research pipelines, I enjoy and .
Scientific & Technical Arsenal
My research capabilities rely on a : for conception, and for execution.
Skills
Scientific Computing & AI
Core expertise in mathematics, statistics, and machine learning. Building and training neural networks, statistical models, and data science solutions.
Data Engineering & MLOps
Infrastructure, data pipelines, and production deployment. Managing databases, containerization, and scalable systems for ML models.
Fullstack Development
Web and backend development with modern frameworks. Building responsive UIs and scalable server-side applications.
Mathematical Foundation
Rigorous mathematical training applied to machine learning: from gradient-based optimization and statistical inference to numerical stability and learning guarantees.
Research & Engineering Path
Theoretical knowledge is nothing without concrete application. From to designing , my path reflects a constant shift toward high-impact and safety-critical challenges.
Academic Foundation
Mathematical rigor is the cornerstone of Safe AI. My background in provides the foundations to analyze, stress-test, and secure modern deep learning architectures.
Live Telemetry
Research requires discipline and transparency. Here is a real-time overview of my and historical data.
Let's start a discussion
Thanks for stopping by my digital garden! Whether you have a question about a theorem, a suggestion for a project, or just want to say hi, I'd love to hear from you.
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