Gregor Pirš
Statistical Engineer
Maribor, Slovenia
Summary
👤
Senior🎓
Top SchoolGregor Pirš is a Statistical Engineer with nine years of experience applying Bayesian statistics and practical data engineering to production analytics. With a PhD in Bayesian methods, he bridges rigorous probabilistic modeling and scalable pipelines using Python, R, Spark, Airflow and GCP—extending models for forecasting, anomaly detection and density estimation while also building the infrastructure that keeps them reliable. His background spans actuarial pricing, academic research (including a Columbia visiting scholar stint working on hierarchical stacking) and industry roles where he designed ML microservices and optimized data lakes. An active contributor to the Stan Math library, he has implemented reverse-mode autodiff for matrix operations, reflecting a low-level numerics skillset that complements his end-to-end product focus. Based in Maribor, Slovenia, he excels at turning advanced statistical ideas into efficient, maintainable systems across biotech, pharma and energy domains.
9 years of coding experience
9 years of employment as a software developer
MSc Mathematics, MSc Mathematics at Univerza v MariboruPhD Computer and Information Science, PhD Computer and Information Science at University of Ljubljana, Faculty of Computer and Information ScienceMathematics, Mathematics at Ludwig-Maximilians-Universität München
Github Skills (12)
automatic-differentiation10
c-language10
eigen10
cprogramming-language10
math-library9
linear-algebra9
math9
stan9
cpp9
mathematics9
mathlib9
boost7
Programming languages (9)
Github contributions (5)
stan-dev/math
Mar 2021 - May 2021
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:26 reviews, 61 commits, 7 PRs in 1 month
Contributions summary:Gregor primarily focused on extending the Stan Math Library by implementing and refining the `diag_post_multiply` function, which is used for matrix operations. Their contributions involved adding reverse-mode (rev) implementations, which is crucial for automatic differentiation and its usage in probabilistic modeling. The user extended the tests for this function to incorporate mix tests to increase the quality of the results. The user also added the function to the fun.hpp file for wider use.
automatic-differentiationprobabilistic-modelingsundialsmodestemplate-library
gregorp90/math
Jan 2021 - May 2021
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.
Contributions:49 pushes, 14 branches in 3 months
automatic-differentiationprobabilistic-modelingmodestemplate-libraryeigenvalues
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