About me
I trained as an astrophysicist — spending several years modelling relativistic jets, fitting models to multi-wavelength observational data, and running large simulations on European supercomputing clusters. The work required building tools from scratch, reasoning carefully about sources of error, and producing results that could be reproduced and checked.
That approach carries over directly into data science and engineering: build something, test it against reality, be precise about what it does and does not show.
Research, in one minute
I study energetic outflows from active galactic nuclei — supermassive black holes that launch relativistic jets across hundreds of thousands of light-years. The work combines magnetohydrodynamic simulations with multi-wavelength observations to understand how these jets produce the radiation we measure.
The underlying method is general: build a physical model, derive observable predictions, compare with data, and document what holds and what does not.
Featured project
A selected project from the portfolio.
More projects are available on the Projects page.
Available for data science and engineering roles. Feel free to reach out.