Damian Nadales is a software engineer and founder with 11+ years building high-assurance, maintainable systems—specializing in Haskell and functional, declarative design. He runs Sustainable Software Solutions, offering consultancy in distributed systems and correctness-focused development, and previously redesigned a Haskell-based model-based testing tool at TNO. His open-source contributions include meaningful back-end work to scikit-image (color space conversions) and to the Cardano ledger, showing comfort across scientific software and blockchain ledger rules. Damian prefers Unix-native toolchains, values team culture and rigorous solutions over quick hacks, and deliberately avoids object-oriented paradigms in favor of provable, maintainable code. He brings research depth from a PhD in Computer Science and practical experience spanning GPGPU, CI, web interfaces, and IoT cloud services. An analytical “thinker,” he excels on projects where formal correctness and long-term sustainability are prioritized.
11 years of coding experience
6 years of employment as a software developer
Licentiate degree, Computer Science, Licentiate degree, Computer Science at Universidad Nacional de Río Cuarto
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Technische Universiteit Eindhoven
The ledger implementation and specifications of the Cardano blockchain.
Role in this project:
Back-end Developer
Contributions:27 reviews, 204 commits, 143 PRs in 3 years 5 months
Contributions summary:Damian made several contributions to the Cardano ledger implementation, focusing on implementing and refining the ledger specification rules. Their work involved modeling various aspects of the ledger, including UTXO, witnesses, and delegation rules. They also incorporated feedback from other contributors and made changes to support delegation in the chain. Moreover, the user worked on creating the update payload for the chain traces and improving the generators.
Contributions summary:Damian focused on adding and testing new functionality related to color space conversions within the scikit-image library. They introduced support for various illuminants and observers in the `xyz2lab` and `luv2xyz` color space conversion functions. Their work included modifying the `colorconv.py` file to incorporate the new features and writing corresponding tests to ensure the correctness of the conversions across different configurations, modifying test files to accommodate these new features.
image-processingpythoncomputer-visionimage
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Damian Nadales - Owner at Sustainable Software Solutions