Astrophysicist · Cosmologist · Research Software & HPC Engineer
INAF – Institute of Radioastronomy · Italian ALMA Regional Centre, Bologna

I work at the intersection of extragalactic astrophysics, large-scale-structure cosmology, and scientific software engineering, targeting the next generation of surveys and experiments — SKAO in the radio, Euclid in the optical/NIR, ALMA, and the Einstein Telescope. At that scale the modelling and the software stop being separable problems, so I build both.

• 🔭 Galaxy formation & evolution — panchromatic SED modelling from the X-ray to the radio, with Bayesian inference.
• 🌌 Mock skies — full-sky, multi-population light-cones that let survey teams validate pipelines and forecast constraints before real data arrive.
• ⚙️ High-performance research software — hybrid C++/Python libraries, HPC workflows, reproducible open-source releases.

Package	Role	Stack	Distribution	Reference
GalaPy	Lead author & maintainer	C++ core + Python API	· docs	A&A 685, A161 (2024) · A&C 55 (2026)
SCAMPy	Author & maintainer	Pure Python	· docs	MNRAS 498, 2095 (2020)
T-RECS	Contributor — HI emission model	Fortran + Python	upstream (A. Bonaldi)	MNRAS 524 (2023)
CosmoBolognaLib	Contributor — void size function & catalogue cleaning	C++ + Python	upstream (F. Marulli)	A&A 607, A24 (2017)

GalaPy models the full spectral energy distribution of a galaxy — star formation history, stellar populations, two-component dust attenuation and age-dependent reradiation, synchrotron, nebular/free-free and X-ray binary continuum — and produces an SED in milliseconds on a single core with minimal memory footprint, which is what makes Bayesian photometric fitting tractable at survey scale. Number-crunching is compiled, object-oriented C++; the user-facing layer is Python. Released under GPLv3, Python ≥ 3.7, 9 releases on PyPI to date.

Always glad to talk about survey simulations, SED modelling, or research software.
tommasoronconi.github.io · tommaso.ronconi@inaf.it