I have a background in theoretical and computational nuclear physics, where I used simulations, data analysis, and statistical methods to explore matter under extreme conditions. Alongside my research, I developed strong skills in coding, data visualization, and machine learning — which I’m now excited to apply in real-world settings as I move into data science.
I’m driven by the idea that scientific thinking should extend beyond research papers — helping us understand the world more clearly, communicate more effectively, and make better decisions. I value clarity, responsibility, and continuous learning, and I’m motivated to use my skills where they can create real, tangible impact.
Studied theoretical physics and mathematics across Germany, France, and Switzerland through a double MSc at École Polytechnique and ETH Zürich. Learned to navigate diverse scientific cultures, highly-diverse teams and challenging porjects — and grew a passion for modeling complexity.
I first explored data science and machine learning during my Master’s thesis, and continued developing those skills alongside my PhD. I built state-of-the-art deep learning tools for particle physics and created automated data analysis workflows for nuclear simulations. Bridging experimental data with theoretical models taught me to understand not just how data behaves — but what it means in different contexts, and the importance of interpreting it correctly.
My PhD focused on simulating heavy-ion collisions using hybrid physics models that combine hydrodynamics with microscopic transport. I applied statistical methods, Bayesian inference, and HPC workflows to analyze and compare results with experimental data — bridging theory and computation. A major part of this work involved managing high computational costs, refining interfaces both between models and software, and maintaining rigorous quality standards across simulation pipelines.
Through climate advocacy and science communication, I’ve learned to translate complex ideas clearly — not just for specialists, but also for the public and policymakers. As a member of Scientists for Future, I speak, write, and organize to bring evidence into public discourse. Because even the best science only matters if it’s understood — and that requires clarity without compromise.
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