Welcome to my GitHub profile! I'm an AI Research Scientist with a passion for applied mathematics, artificial intelligence, and exploring the broader tech landscape. Here, you'll find a collection of my projects, notes, and contributions to the open-source community.
Short Bio
I am an AI Research Scientist working at the intersection of academic research and industry. I am currently a postdoctoral researcher at CREST, supervised by Arnak Dalalyan, where my research focuses on generative modeling, with particular interest in diffusion models and flow matching. This work builds on a PhD in statistics and over six years of experience in data science and artificial intelligence.
My career spans both applied research and real-world deployment. I began at Thales, working on time series analysis, signal processing, object detection, and anomaly detection. I later joined Iktos, where I designed deep learning models for drug discovery, before contributing to foundational biological models at MBZUAI and GenBio AI.
In parallel with research, I maintain strong ties to industry and entrepreneurship. In 2025, I explored venture creation by developing proofs of concept for AI-driven decision-making tools, while freelancing on projects ranging from LLM observability platforms (Rollstack) to improving Retrieval-Augmented Generation systems (Clarifeye). I am driven by the challenge of translating cutting-edge theory into impactful, scalable AI systems.
Nicolas' Notebook
This is a collection of my notes and thoughts on various topics. I'm using this as a way to keep track of what I'm learning and to share that knowledge with others. I hope you find it helpful!
Feel free to explore my repositories, and don't hesitate to reach out if you have any questions or ideas for collaboration. I'm always excited to connect with like-minded individuals and explore new opportunities in the tech world.
📫 How to reach me: LinkedIn