Research output per year
Research output per year
Personal profile
ShortBio
PhD in Computer Engineering (Cum Laude) from the University of the Basque Country (UPV/EHU, 2026), Bachelor’s Degree in Informatic Engineer with a specialization in Computer Science from the University of the basque Country (UPV/EHU) and MSc in Artificial Intelligence from Universidad Internacional de La Rioja (UNIR, 2021).
Throughout his academic and professional career, he has worked at TECNALIA as a researcher in Artificial Intelligence within the Factory Learning platform, focusing on the development of Machine Learning models for industrial tabular data, with particular attention to scenarios involving data scarcity, class imbalance, and high experimental acquisition costs.
His doctoral thesis focused on the research and application of Active Learning and synthetic data generation techniques to improve the efficiency, robustness, and reliability of Machine Learning models in industrial environments.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
-
SDG 4 Quality Education -
SDG 9 Industry, Innovation, and Infrastructure
Fingerprint
Dive into the research topics where Luis Moles Rodriguez is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
Enhancing design of experiments through uncertainty estimation and synthetic data generation
Moles, L., Andres, A., Echegaray, G. & Boto, F., Mar 2026, In: Results in Engineering. 29, 109409.Research output: Contribution to journal › Article › peer-review
Open AccessFile1 Citation (Scopus)10 Downloads (Pure) -
Exploring Data Augmentation and Active Learning Benefits in Imbalanced Datasets
Moles, L., Andres, A., Echegaray, G. & Boto, F., 19 Jun 2024, In: Mathematics. 12, 12, 1898.Research output: Contribution to journal › Article › peer-review
Open AccessFile22 Citations (Scopus)10 Downloads (Pure) -
On the use of machine learning for predicting femtosecond laser grooves in tribological applications
Moles, L., Llavori, I., Aginagalde, A., Echegaray, G., Bruneel, D., Boto, F. & Zabala, A., Dec 2024, In: Tribology International. 200, 110067.Research output: Contribution to journal › Article › peer-review
Open AccessFile10 Citations (Scopus)26 Downloads (Pure) -
Convolutional Neural Networks for Structured Industrial Data
Moles, L., Boto, F., Echegaray, G. & Torre, I. G., 2023, 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2022, Proceedings. García Bringas, P., Pérez García, H., Martinez-de-Pison, F. J., Villar Flecha, J. R., Troncoso Lora, A., de la Cal, E. A., Herrero, A., Martínez Álvarez, F., Psaila, G., Quintián, H. & Corchado Rodriguez, E. S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 361-370 10 p. (Lecture Notes in Networks and Systems; vol. 531 LNNS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
2 Citations (Scopus)
Thesis
-
Active Learning and Synthetic Data Generation Methodology: Applications for Industrial Use Cases
Moles Rodriguez, L. (Author), Sierra Araujo (Supervisor) & Andres Fernandez (Supervisor), 2026Doctoral thesis: Doctoral Thesis