Expand Niels FAUCHER's Resume
About Niels FAUCHER
Personal Introduction
Hello! I am Niels FAUCHER, a computational physicist and AI enthusiast with a strong passion for non-linear systems and condensed matter physics, with a specific focus on the emergent behavior of magnetic skyrmions. As a computational physicist, I specialize in predictive modeling using Reservoir Computing (RC). My work is focused on applying these models to highly complex non-linear systems, pushing the boundaries of their predictive capabilities while continuously advancing their architecture. I am fluent in English (C1+) and French (native), with basic knowledge of Italian.
Professional Introduction
I hold a Master's degree in Computational Physics and am applying this expertise at Adularia, a company dedicated to developing next-generation immunotherapies. My role is to pioneer an AI strategy using generative models, architecting systems with techniques like Flow Matching that excel at constructing complex, structured data from simple noise.
Alongside this focus on generative AI, I have a distinct specialization in an alternative computational paradigm: Reservoir Computing. This expertise is not just theoretical; it was the core of my research internship at the University of Tokyo, where I was tasked with designing and building a numerical Physical Reservoir Computer (PRC) from the ground up, using the dynamics of magnetic skyrmions.
Education
- Master 2 & Master 1 – Physics & Computational Physics, University of Bourgogne Franche-Comté
- Bachelor – Fundamental Physics, University of Montpellier
Research Experience
- Physical Reservoir Computing based on magnetic skyrmion, Physical Intelligence Lab, Tokyo University
- Study of the Kuramoto model for Photonic AI, FEMTO-ST
- Developement of a Monte Carlo Markov Chain (MCMC) to study the internal structure of planets, University of Zurich
- Developement of the world investement network (WIN) based on the Pagerank algorithm, University of Bourgogne Franche-Comté
- PhotoElectric Heating On Interstellar Grains Simulation, University of Bourgogne Franche-Comté
Projects
- GPU/CPU Optimized N-Body Simulation
- Non-linear model simulation: Study of the Tamari model
- Application of principal component analysis(PCA) to the analysis of sports results
- Study the behavior of two types of Carbon NanoTubes using the software VASP (Vienna Ab initio Simulation Package)
Skills & Focus Areas
- Programming: Fortran, OpenMP, OpenACC, Python, Bash
- Frameworks & Tools: Magnum.np, TensorFlow, PyTorch, Jupyter, LaTeX
- Numerical & Physical Simulations
Interests
- Exploring complex system and utilized them for next-generation computing and predictive intelligence.
- Procedural Simulations & AI Research
- Sports : swimming, hiking and wrestling
Featured Projects
MCMC
Markov Chain Monte Carlo (MCMC) simulations to estimate internal structure parameters of a planetary model.
View ProjectRate-equations-for-modeling-growth
Simulation of the aggregation and diffusion of particles on a surface. A Monte Carlo approach was used to ensure our findings were statistically robust and validate the predictions of theoretical Rate Equation models.
View ProjectKuramoto Model
The Kuramoto model can be used to study synchronization dynamics in coupled systems — specifically, in vertical-cavity surface-emitting lasers (VCSELs), which are key components in photonic neural networks.
View ProjectN-Body using Fortran OpenMP and OpenACC
A high-performance Fortan N-Body simulation. The project contains a single threaded, a multi-threaded CPU OpenMP, and an OpenACC GPU approaches. Results can be verified using the conservation of energy and momentum.
View ProjectContact Niels FAUCHER
To discuss a potential project or to learn more, please get in touch.