Joan Miguelez
Research Staff at Barcelona Supercomputing Center
Barcelona, Catalonia, Spain
Summary
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Senior🎓
Top SchoolJoan Miguelez is a research staff scientist at the Barcelona Supercomputing Center with 11 years' experience at the intersection of computational social science, data-centric machine learning, and responsible data-sharing practices. He holds a PhD focused on data-sharing for Responsible AI and has blended academic roles with applied engineering—teaching, building web services, and architecting back-end systems across public and private sectors. His background includes leading cross-technology teams, designing REST APIs and CI/CD pipelines, and contributing to policy and tech discourse as a former Member of the Catalan Parliament focused on science and technology. Comfortable moving between research and production, he brings hands-on software craftsmanship from PHP/Drupal and Node stacks to rigorous empirical methods for trustworthy ML. Colocated in Barcelona, he combines deep technical experience with practical governance insight, making him adept at operationalizing ethical data practices in real-world projects.
11 years of coding experience
11 years of employment as a software developer
Master in Telecommunication Engineering, Master in Telecommunication Engineering at Universitat Autònoma de BarcelonaUOC (Universitat Oberta de Catalunya)
Spanish, Catalan, English
Github Skills (41)
dataset-generation10
model-driven10
datasets10
schema-org10
vscode10
json-ld10
open-datasets10
machine-learning9
open-data9
modeling9
rails-app8
information-retrieval8
multi-agent8
semantic-search8
agent-framework8
Programming languages (5)
Github contributions (5)
SOM-Research/CMS-Headless-Modeling
Sep 2020 - Sep 2022
Eclipse Modeling Framework plugin able to model CMS Sites using the data exposed by its default REST API. Compatible with Drupal (JSON:API) and Wordpress
Contributions:101 commits, 4 PRs, 95 pushes in 2 years
cmsdrupaleclipserestrest-api
JoanGi/croissant
Jan 2024 - Dec 2025
Croissant is a high-level format for machine learning datasets that brings together four rich layers.
Contributions:2 PRs, 94 pushes, 9 branches in 1 year 10 months
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