๐ค Research scientist working on AI for scientific research software. My goal is to develop general purpose agents that can automate key reuse tasks.
๐๏ธ Publications
๐ฌ Latest research projects
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Can machines interpret and execute plans and instructions for research software installation?
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Scientific open source Software (SOSS) - A repository that given an software arfefact DOI, it will computationally reproduce the software environment of the package.
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A Machine-actionable Approach to Simplify the Creation of Software Management Plans (SMPs) at NFDI4DS is hosting a series of Mini Hackathons at ZB Med in Cologne.
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A knowledge graph (KG) using semantic web technolgies. We defined requirements and improvements to make the most comprehensive database about historical games FAIR, with special attention as to whether the existing tools help enhance data published on the web in digital humanities.
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The Community Data Driven Insight (CDDI) is a project that implemented FAIR research data and software management strategies with digital techniques across research communities.
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Co-developed a web service to insert projects from the Institute of Data Science (IDS) and its information from git repositories, alongside with generating JSON file using DOAP schema.
In 2019, I joined the Institute of Data Science (IDS) to develop my research software engineering skills, learn more about digital technologies, and contribute to open science. As research data scientist, I've been also involved in EU-wide research projects that investigate models and methods for efficient semantic indexing, linking and retrival of heterogeneous and distributed data sources such as the European Open Science Cloud (EOSC), and EU COST Action CA19134 - Distributed Knowledge Graphs (DKG), as well as building communities and standards for research data management and software best practices as member in the FAIR for Research Software working group at Research Data Alliance. Previously, I had also worked in industry as data scientist on a project funded by the European Space Agency (ESA) and the European Investment Bank (EIB) related to data integration, visualisation and statistical analysis. Check all archived research projects in this Github repository (@carlosug) or on this ๐๏ธ PDF.
๐ญ Teaching
Introduction to software best practices for researchers of TU Delft University (2023, 2024).
Training digital skills for students and researchers at TU Delft University (2023, 2024).
Introduction to data science with Python/Pandas/Seaborn for undergraduate students of social science (2022, 2021 and 2020).
Data science in R for bachelor students in the applied data science minor (2021, 2022 - lectures and practicals).
Other workshops and courses I have been involved in teaching and developing material include: Exploring how AI tools can be integrated in the research software lifecycle (AI4RS), FAIR Research Software Program (FAIR4RS) and Version Control and Collaborative Development for Research Software (GitCoDev).
๐ ๏ธ Talks and presentations
2024:
- Exploration of AI tools for research software. Spring Symposium - AI Education hosted by TU Delft | AI Initiative, June 2024.
- Automated Extraction of Research Software Installation Instructions from README files. NSLP 2024 workshop, May 2024.
2023:
- What can an open science educator do on teaching and building digital competences in reproducibility?. Sheffield University at Teaching Reproducible Research and Open Science Conference, July 2023.
2022:
- Challenges and solutions towards building and visualising FAIR data for traditional games. Storytelling - DARIAH Annual Conference 2022 , Athens, Greece; June 2022.
- FAIR Coffee: Visualising FAIR data for traditional games. FAIR Coffee Event - Maastricht and (online); May 2022.
- The importance of FAIR and the Community of Data Driven Insights (CDDI) - the road to the science of the future. A talk about the Community Data Driven Insight project in Maastricht University, April 2022.
- FAIR practices being currently implemented in some projects CDDI. Online M-BIC Open Science Symposium, January 2022.
๐ฌ About me
Hello! I'm Carlos, and I am one of those human beings who loves to learn from others, science and research.
I now work as AI Trainer & Educational Developer for the Research Data and Software Team (RDS) at TU Delft Library , and I'm doing a PhD in the Ontology Engineering Group at the UPM. I am a strong advocate of open source and my research interests involve the usage of semantic web standards, and scientific software in general.
When not dealing with numbers or reading, Iโm a happy uncle, a swimmer, a tennis player and, last but not least, a loving supporter of Real Zaragoza football team.
Below I subjectively rated my techincal skills with scores, please refer to my ๐๏ธ CV for a better account of how those skills were used.
Python
4/5
RDF
3/5
SPARQL
3/5
Ontologies
3/5
SHACL
3/5
Bash
2/5
Linux
3/5
Docker
1/5
Git
3/5
OpenAPI
1/5
RDFLib
3/5
TypeScript
2/5
React
2/5
Material UI
12/5
HTML/CSS
3/5
ShEx
2/5
RML
2/5
Protรฉgรฉ
1/5
Rstudio
4/5
Jupyter
4/5
Node.js
2/5
Express.js
2/5
D3.js Graph
2/5
NetworkX
4/5
RDF4J
2/5
MongoDB
1/5
SQL
2/5
NLP
3/5
GraphQL
1/5
Pandas
4/5
Gatsby
2/5
MacOS
4/5