Judith Sáinz-Pardo Díaz

According to our database, Judith Sáinz-Pardo Díaz authored at least 15 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning.

Judith Sáinz-Pardo Díaz, Álvaro López García

CoRR, May, 2026

Metric-privacy-inspired noise calibration in federated learning: Improving convergence and preventing client inference attacks.

Judith Sáinz-Pardo Díaz, Andreas Athanasiou, Kangsoo Jung, Catuscia Palamidessi, Álvaro López García

Knowl. Based Syst., 2026

2025

AI4EOSC: a Federated Cloud Platform for Artificial Intelligence in Scientific Research.

Ignacio Heredia, Álvaro López García, Germán Moltó, Amanda Calatrava, Valentin Kozlov, Alessandro Costantini, Viet D. Tran, Mário David, Daniel San Martín, Marcin Plóciennik, Marta Obregón Ruiz, Saúl Fernandez, Judith Sáinz-Pardo Díaz, Miguel Caballer, Caterina Alarcón Marín, Stefan Dlugolinský, Martin Seleng, Lisana Berberi, Khadijeh Alibabaei, Borja Esteban Sanchis, Pedro Castro, Giacinto Donvito, Diego Aguirre, Sergio Langarita, Vicente Rodríguez, Leonhard Duda, Andrés Heredia Canales, Susana Rebolledo Ruiz, João Machado, Giang Nguyen, Fernando Aguilar Gómez, Jaime Díez

CoRR, December, 2025

Machine learning operations landscape: platforms and tools.

Lisana Berberi, Valentin Kozlov, Giang Nguyen, Judith Sáinz-Pardo Díaz, Amanda Calatrava, Germán Moltó, Viet D. Tran, Álvaro López García

Artif. Intell. Rev., June, 2025

Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks.

Judith Sáinz-Pardo Díaz, Andreas Athanasiou, Kangsoo Jung, Catuscia Palamidessi, Álvaro López García

CoRR, February, 2025

Landscape of machine learning evolution: privacy-preserving federated learning frameworks and tools.

Giang Thu Nguyen, Judith Sáinz-Pardo Díaz, Amanda Calatrava, Lisana Berberi, Oleksandr Lytvyn, Valentin Kozlov, Viet D. Tran, Germán Moltó, Álvaro López García

Artif. Intell. Rev., February, 2025

Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data.

Judith Sáinz-Pardo Díaz, Álvaro López García

CoRR, January, 2025

Exploring Federated Learning for Thermal Urban Feature Segmentation - A Comparison of Centralized and Decentralized Approaches.

Leonhard Duda, Khadijeh Alibabaei, Elena Vollmer, Leon Klug, Valentin Kozlov, Lisana Berberi, Mishal Benz, Rebekka Volk, Juan Pedro Gutiérrez H. Muriedas, Markus Götz, Judith Sáinz-Pardo Díaz, Álvaro López García, Frank Schultmann, Achim Streit

Proceedings of the Computational Science and Its Applications - ICCSA 2025 - 25th International Conference, Istanbul, Turkey, June 30, 2025

2024

Personalized federated learning for improving radar based precipitation nowcasting on heterogeneous areas.

Judith Sáinz-Pardo Díaz, María Castrillo, Juraj Bartok, Ignacio Heredia Cacha, Irina Malkin Ondík, Ivan Martynovskyi, Khadijeh Alibabaei, Lisana Berberi, Valentin Kozlov, Álvaro López García

Earth Sci. Informatics, December, 2024

An Open Source Python Library for Anonymizing Sensitive Data.

Judith Sáinz-Pardo Díaz, Álvaro López García

CoRR, 2024

Making Federated Learning Accessible to Scientists: The AI4EOSC Approach.

Judith Sáinz-Pardo Díaz, Andrés Heredia Canales, Ignacio Heredia Cacha, Viet D. Tran, Giang T. Nguyen, Khadijeh Alibabaei, Marta Obregón Ruiz, Susana Rebolledo Ruiz, Álvaro López García

Proceedings of the ACM Workshop on Information Hiding and Multimedia Security, 2024

2023

Study of the performance and scalability of federated learning for medical imaging with intermittent clients.

Judith Sáinz-Pardo Díaz, Álvaro López García

Neurocomputing, 2023

Comparison of machine learning models applied on anonymized data with different techniques.

Judith Sáinz-Pardo Díaz, Álvaro López García

Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2023

2022

pyCANON: A Python library to check the level of anonymity of a dataset.

Judith Sáinz-Pardo Díaz, Álvaro López García

CoRR, 2022

Forecasting COVID-19 spreading trough an ensemble of classical and machine learning models: Spain's case study.

Ignacio Heredia Cacha, Judith Sáinz-Pardo Díaz, María Castrillo Melguizo, Álvaro López García

CoRR, 2022