Welcome to the new version of my personal academic website!
When I launched this site back in 2020, it was a modest space where I shared initial thoughts as I began my journey into applied research. Over the past few years, my work at Tecnalia Research & Innovation and my doctoral research at the University of the Basque Country (UPV/EHU)—co-supervised by Dr. Roberto Garay Martinez (DeustoTech, University of Deusto) and Dr. Iñigo Mendialdua (UPV/EHU)—has matured significantly.
As my research expanded into advanced control paradigms—ranging from Deep Reinforcement Learning (DRL) and Model Predictive Control (MPC) to empirical testing at Tecnalia’s KUBIK experimental building—I felt it was time for the website to evolve as well.
What’s New in this Version?
Here are the key improvements integrated into this release:
- Entirely in English: To foster international collaboration, share preprints, and engage with the global building energy and machine learning research communities.
- Comprehensive Publications Catalog: A dedicated, searchable, and filterable Publications page featuring all 17 peer-reviewed journal articles, conference papers, and book chapters, complete with direct DOI links and one-click BibTeX citations.
- Structured Research Lines: A clear overview of my core Research Lines, detailing methodologies, simulation workbenches, and physical testbed validations.
- Full-Featured RSS 2.0 Feed: You can now subscribe directly via RSS (/feed.xml) in your favourite feed reader (NetNewsWire, Feedly, Thunderbird, etc.) without relying on social media algorithms to catch new posts and paper announcements.
- Verified Academic Profiles: Direct connections to my profiles on Google Scholar, ORCID, and the Tecnalia Science Portal (Pure).
- Modern, Responsive Design: Built from the ground up with clean typography (Inter + Merriweather), a light and dark mode toggle, and a responsive mobile interface.
Looking Ahead
Moving forward, I will use this blog to share:
- Breakdowns and plain-language summaries of newly published papers.
- Practical insights on training reinforcement learning agents on thermodynamic building models.
- Open-source tools, simulation workbenches, and dataset releases.
- Takeaways and presentations from scientific conferences.
Feel free to browse around, check out the Publications, subscribe via RSS, or reach out via email or LinkedIn if you are interested in collaborating!
