Luis Domenzain
Staff Engineer at domenza.in
Paris, Ile-de-France
Summary
👤
SeniorLuis Domenzain is a trilingual Staff Engineer based in Paris with 10 years of experience designing IoT consumer and scientific products, combining electronics, computer science and hardware design expertise from a Master’s at the Sorbonne. He leads cross-disciplinary teams at GoPro while consulting on camera and computer vision products through his firm, bringing a rare blend of hands-on R&D and product-focused delivery. Luis contributes to open-source Bayesian tooling—adding log CDF implementations to PyMC—demonstrating applied probabilistic modeling skills that complement his firmware and systems background. Known for translating complex hardware-software requirements into reliable products, he excels at bridging research, engineering and product teams across international projects.
10 years of coding experience
English, Spanish, French, Japanese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
statistics10
probabilistic-programming10
python10
bayesian-inference10
statistic10
numpy9
scipy9
mcmc9
testing8
Programming languages (8)
Github contributions (5)
pymc-devs/pymc
Mar 2017 - Jan 2019
Bayesian Modeling and Probabilistic Programming in Python
Role in this project:
Back-end Developer / Data Scientist
Back-end Developer / Data ScientistContributions:5 reviews, 20 commits, 7 PRs in 1 year 10 months
Contributions summary:Luis implemented log CDF calculations for several probability distributions within the PyMC3 library. Their contributions focused on enhancing the statistical capabilities of the library by adding functions for the Laplace, Normal, Weibull, Exponential, HalfNormal, Cauchy, Gumbel, Uniform, and other distributions. The work involved modifying existing code and adding tests to ensure the accuracy of the new log CDF functions, demonstrating expertise in probabilistic programming and Bayesian modeling. This work directly expands the suite of supported distributions, improving the library's usefulness for statistical analysis.
pythonbayesian-inferencestatistical-inferencemachine-learningprobabilistic-programming
domenzain/fava-docker
Nov 2020 - Dec 2023
A Dockerfile for beancount-fava
Contributions:3 PRs, 15 pushes in 3 years 1 month
dockerfilebeancountfavadocker
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.