Martin Uhrin
MIAI Research Fellow Chair at Université Grenoble Alpes
Grenoble, Auvergne-Rhône-Alpes, France
Summary
👤
Senior🎓
Top SchoolMartin Uhrin is a computational physicist and research fellow with 14 years of experience bridging academia and software engineering, currently leading research at Université Grenoble Alpes on generative models for inverse materials and molecular design. He holds a PhD from UCL and has driven machine-learning-for-materials projects at EPFL and DTU, blending physics-inspired modeling with practical ML engineering. A hands-on developer, he contributes to prominent open-source projects such as AiiDA and e3nn, improving back-end process frameworks, testability, and developer tooling for equivariant neural networks. His background ranges from high-performance C/C++ game programming at Microsoft to modern Python and DevOps workflows, enabling him to translate theoretical ideas into production-ready code. Colleagues praise his ability to tighten scientific rigor with software best practices, a combination that accelerates reproducible discovery in materials informatics.
14 years of coding experience
9 years of employment as a software developer
Master's Degree, Physics, High Performance Computing, Computer Science, 1st class, Master's Degree, Physics, High Performance Computing, Computer Science, 1st class at The University of EdinburghDoctor of Philosophy (Ph.D.), Computational Physics, Doctor of Philosophy (Ph.D.), Computational Physics at University College London, U. of London
English, Slovak, French
Github Skills (13)
pytorch10
machine-learning10
infrastructure10
pytest10
back-end-development10
python10
devops9
documentation9
type-checking9
typehinting9
linear-algebra8
githubaction-workflow7
github-ci7
Programming languages (8)
Github contributions (5)
aiidateam/aiida-core
Apr 2015 - Dec 2019
The official repository for the AiiDA code
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 reviews, 367 commits, 93 PRs in 4 years 8 months
Contributions summary:Martin's primary contribution appears to be related to the codebase's infrastructure and functionality, as evidenced by the focus on adding setup configurations and the implementation of a new system to run processes. The user's work includes building or modifying a framework to run the processes and the related documentation.
aiidaworkflow-engineschedulerprovenancessh
e3nn/e3nn
Jun 2021 - Sep 2022
A modular framework for neural networks with Euclidean symmetry
Role in this project:ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:10 reviews, 10 commits, 3 PRs in 1 year 2 months
Contributions summary:Martin primarily focused on improving the development environment and code quality within the e3nn repository. They added a pre-commit hook with a linter, integrated testing frameworks, and included type hints to improve code maintainability. Additionally, they added a 'dev' extra to facilitate easier setup for developers, including the installation of testing and linting tools. The user also addressed documentation ambiguities and implemented tests for error conditions within the core libraries.
modular-frameworksymmetrydeep-learningneural-networkseuclidean
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