I'm Alejandro, a computational scientist and machine learning engineer from Barcelona working in the interesection betwee data science, machine learning, health data, and scientific software, with a background in epidemiology, bioinformatics, and the life sciences.
My work usually revolves around extracting signal from complex (and messy) data, building reproducible analytical workflows, and turning research questions into informed answers, useful tools, models, and data products. In my career, that has included machine learning on biomedical signals, observational and population health data, protein engineering, time-series and spatial analysis, and scientific software, but I tend to explore outside of those domains as well.
I use this space to share research code, open-source tools, data viz projects, homelab experiments, and other things I build at the intersection of science, my hobbies, and software.
My interests and past work include:
- machine learning, statistics, and health data analysis
- epidemiology, time series, GIS, and spatiotemporal modelling
- bioinformatics, omics, and computational biology
- scientific software, data pipelines, and reproducible research
- APIs, automation, Linux, containers, and lightweight infrastructure
- digital health, data visualisation, and analytical applications
Over the years I've worked on public-health questions including Kawasaki Disease and infectious-disease dynamics, alongside projects involving the aerobiome, microbial detection, biomedical signals, and other data-intensive biological and health systems.
I am also deeply interested in the more practical engineering side of software: self-hosting, home lab setups, VPS-based deployments, service orchestration, containerised applications, and automation-heavy workflows.
Another area I care a lot about is the digital diabetes ecosystem, including CGM data, sensors, Nightscout, open-source diabetes tooling, and the broader intersection of health technology, data access, interoperability, and real-world user needs.
Research code
- lif-bacteria-aerosols-ms: identifying airborne bacteria in real time with LIF and ML → AMT 2025
- microbial-richness-troposphere: long-distance transport of microbes above the boundary layer → PNAS 2024
- kd-metals-swc: metal-rich aerosols and Kawasaki disease outbreaks → ERL 2023
- covid-climate-signatures: climate signatures in COVID-19 waves → Nat. Comput. Sci. 2021
- vasculitis2022-conference: Tokyo's air sources and Kawasaki disease (poster) → Vasculitis 2022
Analysis packages
- sdcpy: Scale-Dependent Correlation analysis for time series → PyPI
- sdcpy-studio: web app for SDC and SDC-map analyses
Data pipelines
- jp-idwr-db: self-updating database of Japanese infectious disease surveillance
- environmental-data-japan: environmental and population-exposure data for Japan
- aqi-stations-scraper: historical air quality data from aqicn.org (retired)
Data visualisation
- strava-home-runs: every run from one starting point, animated in 3D with Blender
- arbres-bcn: map of Barcelona's street trees → live site
Diabetes and CGM
- dotscout-garmin: Garmin watch face with Nightscout glucose → Connect IQ
- sugarboard: dashboard for personal CGM data from Nightscout
- argos-extensions: GNOME and macOS menu-bar plugins, including a glucose readout
Developer tools
- rmd-notebooks-vscode:
.rmdand.qmdfiles as notebooks in VS Code → Marketplace - data-science-quarto-template: data science repo template with Quarto reports
- chatgpt-theme-switcher: Catppuccin, Gruvbox and other themes for ChatGPT → Greasy Fork
- alfontal.dev: source of my personal site (Astro + Quarto)
