Albin Correya is a CTO and ML engineer with 10 years of experience turning audio and music research into production-ready AI systems, currently leading technology at nowon AG from Copenhagen. He combines deep expertise in music information retrieval, audio DSP and ML—contributed core algorithms and fixes to the well-known Essentia audio library—and has built contextual music recommendation and cover-song identification systems in both research and industry settings. His background spans hands-on C++/Python engineering, WebAssembly-based audio tooling, and large-scale ML at companies like Wolt, Deezer and Moodagent, giving him a rare ability to bridge research-grade models to scalable products. Colleagues rely on him for pragmatic architectures that respect signal-processing realities, and he often surfaces subtle algorithmic fixes (e.g., similarity computation stability) that improve production reliability.
10 years of coding experience
9 years of employment as a software developer
Master of Science Sound and Music Computing, Master of Science Sound and Music Computing at Universitat Pompeu Fabra
C++ library for audio and music analysis, description and synthesis, including Python bindings
Role in this project:
Back-end Developer
Contributions:73 commits, 12 PRs, 2 pushes in 1 year 8 months
Contributions summary:Albin implemented several math functions, including pairwise euclidean distance and percentile, within the `essentiamath.h` file, indicating contributions to the project's core functionality. They then added algorithms for computing cross similarity matrices and cover song similarity, showing focus on music information retrieval. Further, they fixed segfault errors in similarity computations and added references/refactored code comments, demonstrating attention to accuracy, and code quality.
C++ library for audio and music analysis, description and synthesis, including Python bindings
Contributions:73 pushes, 7 branches in 4 years 6 months
audio-processingpythoncppc-libraryaudiounit
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