Bruno Giacomazzo

Scientific Computing and Data Science

Utrecht, The Netherlands

About Me

I'm a computational scientist with extensive experience in developing high-performance scientific computing software. My background combines deep technical expertise in numerical methods, algorithm development, and scientific programming to solve complex problems in mathematics and physics.

I specialize in building robust, efficient code for scientific applications, with particular strength in Python and Fortran. My tools are used by researchers worldwide to accelerate discovery and train the next generation of scientists.

What I bring: Strong analytical and problem-solving skills, experience with complex algorithms and numerical methods, proven track record of developing maintainable code, and the ability to translate scientific concepts into practical software solutions.

Portfolio Projects

SciReader

AI Web App

LLM-powered web application that generates concise summaries of arXiv scientific papers. Built end‑to‑end as a production-ready MVP and used by 100+ researchers.

LLM Applications • AI Software Engineering • Prompt Engineering • Full‑Stack Development • Lovable.dev • Product MVP Development

SciReader →

Google Data Analytics Capstone Project

SQL

Capstone project in which I performed a data analysis of the city of Chicago (IL, USA) bike sharing.

SQL • BigQuery • Looker Studio • Data Analysis

View on GitHub →

Numerical Methods for Partial Differential Equations

Python / Jupyter

PhD-level course material on numerical methods for partial differential equations. Covers advanced techniques for solving complex mathematical problems computationally. It includes practical exercises.

Python • Jupyter • Numerical Analysis • PDEs • Scientific Computing

View on GitHub →

Introduction to Python

Python / Jupyter

Comprehensive Python programming course materials covering scientific computing, data visualization, and numerical methods. Well-documented Jupyter notebooks with practical examples and exercises.

Python • Jupyter • NumPy • SciPy • pandas • Matplotlib

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The Spritz Code

Fortran / C++

HPC code written in Fortran 90 (with some routines in C/C++) that is used to solve the equations of general relativistic magnetohydrodynamics without approximations on a Cartesian grid.

Fortran • Numerical Methods • HPC • MagnetoHydroDynamics

View on Zenodo →

Advection Equation Solver

C++

C++ implementation of different numerical methods to solve the advection equation. This code can be used to teach basic concepts on numerical methods for hyperbolic partial differential equations.

C++ • Numerical Methods • Algorithm Implementation

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Exact Riemann Solver

Fortran

Fortran 90 code implementing the first exact solution of the Riemann problem for special relativistic magnetohydrodynamics. Used by research teams worldwide.

Fortran • Numerical Methods • CFD • MagnetoHydroDynamics

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Docker LORENE Tutorial

Docker

Containerized environment for the LORENE spectral methods library.

Docker • Linux • Scientific Software

View on GitHub →

Technical Skills

Python Fortran Jupyter Notebooks NumPy SciPy Matplotlib pandas SQL BigQuery Looker Studio C++ Docker Numerical Methods Algorithm Development Scientific Computing Data Analysis CFD PDEs High-Performance Computing (HPC) Git/GitHub Linux

Get In Touch

I'm always open to new opportunities in software development, scientific computing, and data science. Let's connect!