José L. Corcuera Bárcena

Pontificia Universidad Católica del Perú

Av. Universitaria 1801, San Miguel 15088, Peru

+51 1 6262000 ext. 4899

I am a Researcher and Full-time Contract Professor at the Pontificia Universidad Católica del Perú (PUCP) and a member of the Artificial Intelligence Research & Development Group (AI-DII). I obtained my PhD in Information Engineering from the University of Pisa (Supervisors: Prof. P. Ducange, Prof. A. Bechini, Prof. F. Marcelloni) and an M.Sc. in Computer Engineering (Cum Laude).

My work focuses on Machine Learning, Federated Learning, and Explainable AI (XAI), approached from a distributed systems perspective. I combine algorithmic design with distributed execution to develop federated versions of explainable learning and clustering algorithms, ensuring their reliable execution to real-world conditions—often leveraging actor-based designs in Erlang. Drawing on 10+ years as a Software Architect and Technical Lead, I design robust, production-ready systems with a focus on performance and scalability. My expertise includes AWS cloud architecture, backend development (Python, Java), and performance optimization.

Feel free to get in touch with me via email at jlcorcuera@pucp.pe.

selected publications

FGCS

Devising an Actor-based Middleware Support to Federated Learning Experiments and Systems

A. Bechini and J.L Corcuera Bárcena

Future Generation Computer Systems, 2025

DOI Bib

@article{bechini2025devising,
  title = {Devising an Actor-based Middleware Support to Federated Learning Experiments and Systems},
  author = {Bechini, A. and Corcuera Bárcena, J.L},
  journal = {Future Generation Computer Systems},
  year = {2025},
  volume = {166},
  pages = {107646},
  publisher = {Elsevier},
  doi = {10.1016/j.future.2024.107646},
  url = {https://www.sciencedirect.com/science/article/pii/S0167739X24006101},
}

INFFUS

Increasing trust in AI through privacy preservation and model explainability: Federated Learning of Fuzzy Regression Trees

J.L. Corcuera Bárcena, P. Ducange, F. Marcelloni, and 1 more author

Information Fusion, 2025

DOI Bib

@article{corcuera2025increasing,
  title = {Increasing trust in AI through privacy preservation and model explainability: Federated Learning of Fuzzy Regression Trees},
  author = {Corcuera Bárcena, J.L. and Ducange, P. and Marcelloni, F. and Renda, A.},
  journal = {Information Fusion},
  volume = {113},
  year = {2025},
  publisher = {Elsevier},
  doi = {10.1016/j.inffus.2024.102598},
  url = {https://www.sciencedirect.com/science/article/pii/S1566253524003762},
}

IEEE TAI

Federated c-means and Fuzzy c-means Clustering Algorithms for Horizontally and Vertically Partitioned Data

J.L. Corcuera Bárcena, F. Marcelloni, A. Renda, and 2 more authors

IEEE Transactions on Artificial Intelligence, 2024

DOI Bib

@article{corcuera2024federated,
  title = {Federated c-means and Fuzzy c-means Clustering Algorithms for Horizontally and Vertically Partitioned Data},
  author = {Corcuera Bárcena, J.L. and Marcelloni, F. and Renda, A. and Bechini, A. and Ducange, P.},
  journal = {IEEE Transactions on Artificial Intelligence},
  year = {2024},
  pages = {1--15},
  publisher = {IEEE},
  doi = {10.1109/TAI.2024.3426408},
  url = {https://ieeexplore.ieee.org/document/10595840},
}