Fernando Garcia de la Cruz
Research engineer, signal processing and machine learning for audio and music
Experience
Independent practice
Research engineer
Sony Computer Science Laboratories (CSL)
Research Scientist Intern
- Machine learning and signal processing research for music and audio applications.
Music Technology Group, Universitat Pompeu Fabra
Research Assistant, IA y Música: Cátedra ENIA 2022 (TSI-100929-2023-1)
- Research on detecting and quantifying AI-generated music in real broadcast monitoring scenarios, in collaboration with BMAT Music Innovators; published as two papers at ISMIR 2026.
- Data pipelines and ML workflows: integrating multiple AI music generators, improving automated audio reference pipelines, and training detection models on real-world data.
- Integrated the Essentia library into real-time audio plug-ins with JUCE; led the essentia-plugins repository.
- Project funded by the Spanish Ministry for Digital Transformation and the Civil Service, with European Commission participation.
Dolby Laboratories
Software Developer, Entertainment Tech (internship)
- C and C++ libraries for audio and signal processing for internal use.
- Audio plug-in development and internal research projects using AI models.
Ear Candy Technologies
Audio Developer, DSP Engineer
Globant
Python Data Engineer, Data & Artificial Intelligence Studio
Everis
Python Engineer, Data & Analytics
Education
MSc Sound and Music Computing
Universitat Pompeu Fabra, Music Technology Group
BSc Electronics and Communications Engineering, specialising in acoustics
Instituto Politécnico Nacional (ESIME)
Publications
Teaching and community
Music Technology Group, UPF
Teaching assistant, Generative Music AI workshop
The Sound of AI
Assistant director of the first Sound of AI Accelerator, a startup programme in music and audio AI
The Sound of AI
Organiser and participant, first Sound of AI Hackathon; my team built Modelizer
The Sound of AI
Project manager, Open Source Research project (200+ contributors), co-author of the AIMC 2022 paper
Ciencia desde Cero
Science communicator
Guit-Art Music School
Guitar teacher and audio engineer
Technical skills
- Audio and DSP
- JUCE (C++), Essentia, Pure Data, Matlab
- Languages
- Python, C/C++, Go, Cmajor, Matlab
- Machine learning
- PyTorch, TensorFlow, Keras, scikit-learn, librosa, torchaudio
- Data engineering
- Apache Beam, Airflow, Kafka, Spark
- Cloud and DevOps
- GCP, Docker, Kubernetes, Jenkins, Travis CI
- Databases
- PostgreSQL, MySQL, BigQuery, MongoDB
- Web and APIs
- FastAPI, Flask, Django
Languages
- Spanish
- Native
- English
- Fluent, professional proficiency