Marco Colombo
Heidelberg, Baden-Württemberg, Germany
Summary
🤩
Rockstar🎓
Top SchoolMarco Colombo is a materials scientist and multidisciplinary researcher with 18 years of experience applying advanced X-ray fluorescence (MA‑XRF), spectroscopy and statistical methods to problems in cultural heritage, geology and instrument R&D. He completed a PhD at TU Darmstadt driving the first commercial MA‑XRF geological application and publishing methodological work with industry partners (Bruker) and museums, and has hands‑on experience in PyMca, Datamuncher, LabVIEW and Bayesian/analytical data modeling for large, high‑dimensional datasets. Marco also contributes to open‑source C++ projects in the Stan ecosystem, improving numerical precision, error handling and automatic differentiation routines—an unusual cross of heritage science and backend scientific software development. Comfortable working across European research cultures, he brings a musician’s discipline from a decade of clarinet study to meticulous experimental design, data processing and collaborative project leadership.
18 years of coding experience
1 year of employment as a software developer
Technischen Universität DarmstadtBachelor’s degree Sciences and Technologies for Cultural Heritage (BS) Chemistry and Physics, Bachelor’s degree Sciences and Technologies for Cultural Heritage (BS) Chemistry and Physics at Università degli Studi di FerraraLifelong Learning Programme (LLP) Erasmus, Lifelong Learning Programme (LLP) Erasmus at Instituto Politécnico de TomarMaster’s degree Science for the Conservation-Restoration of Cultural Heritage (MS) Chemistry and Physics, Master’s degree Science for the Conservation-Restoration of Cultural Heritage (MS) Chemistry and Physics at Alma Mater Studiorum – Università di BolognaConservatorio di Musica "F. Venezze", Rovigo
Portuguese, German, English, Italian
Github Skills (14)
mathematics10
automatic-differentiation10
c-language10
stan10
cprogramming-language10
math10
testing10
bayesian-inference9
variational-inference9
bayesian9
eigen9
bayesian-statistics9
error-handling8
documentation8
Programming languages (14)
Github contributions (5)
stan-dev/math
Jan 2018 - Mar 2020
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:329 commits, 125 PRs, 115 pushes in 2 years 1 month
Contributions summary:Marco primarily focused on enhancing the Stan Math Library by implementing, testing, and amending mathematical functions. Their contributions involved checking input conditions, applying existing functions, and providing better error messages. The user demonstrated the ability to understand, modify, and test C++ template libraries for automatic differentiation, as evidenced by code changes in header files and test files.
automatic-differentiationprobabilistic-modelingsundialsmodestemplate-library
stan-dev/stan
Sep 2017 - Jan 2020
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Role in this project:Back-end Developer
Back-end DeveloperContributions:16 commits, 9 PRs, 48 branches in 2 years 4 months
Contributions summary:Marco's contributions primarily involve code modifications and documentation updates within the Stan development repository. They focused on enhancing the precision of ELBO (Evidence Lower Bound) values, improving code documentation, and replacing deprecated functions. Additionally, the user made changes related to string handling within Eigen vectors and implemented general code improvements. This suggests the user is involved in debugging, optimization, and maintenance tasks within the Stan project.
bayesian-inferencestanmasterbayesian-statisticsdetails
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