I came to audio ML from an unexpected place: industrial electronics and years of taking synthesisers apart to understand how they work.
That background changed how I approach data. I build tools at the intersection of audio and data science — frequency classifiers using MFCC + MDS, automation systems that eliminate friction in technical workflows, and data analysis pipelines from scraping to modelling.
When a process repeats, I build the tool that removes it.
📍 Barcelona, Spain
| Project | Description | Tech |
|---|---|---|
| 🔊 Clasificación Frecuencial MDS | Frequency classifier for audio samples using MFCC cross-correlation & MDS | R warbleR igraph |
| 🤖 Article Generator | Transforms technical notes into professional articles using local AI (Ollama) | Python Ollama Automation |
| 🛠️ Bash Tools | CLI utilities: Conda env manager, Git search, file tools | Bash Automation |
| 🕷️ Hispasonic Web Scraper | Extraction & analysis of 10,000+ posts from Spanish music market | Python BeautifulSoup SQLite |
| 📄 OCR Translation Pipeline | Automated OCR, translation & AI processing workflow | Bash Tesseract Ollama |
| 📈 Dataquest Projects | Data analysis portfolio: market research, traffic analysis, surveys | Python Pandas Matplotlib |
Languages
Audio ML & Signal Processing
Data & Analytics
BI & Visualization
Tools
- 🧩 LEGO Serious Play Facilitator - Certified
- 📊 Google Business Intelligence Professional - Coursera 2024
- 📈 Google Data Analytics - Coursera 2023
- 🐍 Data Scientist in Python - Dataquest
- 🎓 Master in BI & Data Science - IEBS 2020
Let's connect!
Data Science · Audio ML · Automation — always learning, always building.
