Daniel
Pardo Navarro
PhD Student
Learning Systems
Research areas:
- Deep Learning
- Machine Learning
Impact areas:
- Industry
SDGs:
- GOAL 09: Industry, Innovation & Infrastructure
In Press
Daniel Pardo Navarro,
Mehmet Oguz Mulayim,
Bernat Pérez,
Xavier Marín,
Laia Ocaña,
& Manuel Castillo
(In Press).
NIR Spectroscopy and AI to Predict Time and Weight During Cheese Ripening From the Rind.
Proceedings of the XIII Congreso Nacional CyTA-CESIA 2026
.
[BibTeX]
2025
Daniel Pardo Navarro,
Mehmet Oguz Mulayim,
& Manuel Castillo
(2025).
Decoding Cheese Ripening: A Deep Learning Approach to Non-Invasive Monitoring.
Karla Trejo, Isabel Aguiló, Juan Vicente Riera, & Jordi Pascual (Eds.),
Frontiers in Artificial Intelligence and Applications.
IOS Press.
https://doi.org/10.3233/FAIA250613.
[BibTeX]
[PDF]
Daniel Pardo Navarro,
Manuel Castillo,
Mehmet Oguz Mulayim,
& Jesus Cerquides Bueno
(2025).
Machine Learning in Cheese-Making: Methods, Applications, and the Future.
Food Engineering Reviews.
https://doi.org/10.1007/s12393-025-09420-x.
[BibTeX]
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