Hey, I'm Arthur Danjou, a at Paris-Dauphine University.
I sit at the intersection of and . Unlike a pure theorist, I build what I model. Unlike a pure developer, I understand the math behind the code.
I am dedicating my research to . I will soon start my Master's Thesis focusing on and , exploring how to make AI systems mathematically robust and secure.
To drive this research, I leverage Python, PyTorch and R to design architectures, relying on Docker and Linux to ensure reproducibility within my .
When I'm not deriving generalization bounds or fixing 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.
💼 Research & Engineering Path
Theoretical knowledge is nothing without concrete application. From to designing , my journey reflects a constant shift towards critical challenges.
🎓 Academic Foundation
Mathematical rigor is the cornerstone of Safe AI. My background in provides the necessary tools to understand and secure modern Deep Learning architectures.
📊 Live Telemetry
Research requires discipline and transparency. Here is a real-time overview of my and historical data.