Rocco
Ballester Benito
Industrial PhD Student
Learning Systems
Research areas:
- Federated Learning
- Machine Learning
- Quantum Computation
- Optimisation
- Citizen Science
- Probabilistic Graphical Models
Impact areas:
- Smart Cities
SDGs:
- GOAL 09: Industry, Innovation & Infrastructure
- GOAL 03: Good Health and Well-being
- GOAL 16: Peace, Justice and Strong Institutions
2025
Rocco Ballester,
Jesus Cerquides,
& Luis Artiles
(2025).
Quantum federated learning: a comprehensive literature review of foundations, challenges, and future directions.
Quantum Machine Intelligence, 7, 73.
https://doi.org/10.1007/s42484-025-00292-2.
[BibTeX]
2024
Pol Rodríguez-Farrés,
Rocco Ballester,
Carlos Ansótegui,
Jordi Levy,
& Jesus Cerquides
(2024).
Implementing 3-SAT Gadgets for Quantum Annealers with Random Instances.
Leonardo Franco, Clélia Mulatier, Maciej Paszynski, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, & Peter M. A. Sloot (Eds.),
Computational Science -- ICCS 2024
(pp. 277--291).
Springer Nature Switzerland.
[BibTeX]
[PDF]
2023
Rocco Ballester,
Yanis Labeyrie,
Mehmet Oguz Mulayim,
Jose Luis Fernandez Marquez,
& Jesus Cerquides
(2023).
Mathematical and Computational Models for Crowdsourced Geolocation.
Ismael Sanz, Raquel Ros, & Jordi Nin (Eds.),
Frontiers in Artificial Intelligence and Applications, Vol. 375: Artificial Intelligence Research and Development (pp 301--310).
IOS Press.
https://doi.org/10.3233/FAIA230699.
[BibTeX]
[PDF]