About me

Applied AI research with impact
Associate Professor at UPM working on machine learning, optimization, and signal processing for healthcare, autonomous systems, and industry.
GAPS
SSR
ETSIT
UPM
IPTC
53 Publications
21 Q1 Journals
12 R&D Projects
496 Citations
12 H-Index
Research Profile
My work focuses on combining machine learning, optimization, and signal processing to solve real-world problems. My research encompasses medical applications, autonomous navigation, cybersecurity, communications, industrial applications, and audio-related problems.
Healthcare AI Federated Learning Signal Processing Optimal Control Autonomous Navigation Applied AI
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For Students
If you are a UPM student interested in applying AI, machine learning, optimization, or signal processing to your Bachelor's or Master's thesis, feel free to contact me. Topics may include healthcare AI, autonomous systems, communications, and data-driven industrial applications.
Teaching and supervision →
For Industry & Institutions
I collaborate with companies and institutions interested in applying AI to real-world challenges, especially in healthcare, autonomous systems, and industrial data analysis. I am open to joint R&D, consulting, and collaborative research projects.
Research projects →
Latest Publications
2026

The Geometry of Privacy: A Two-Stage Analysis of Generative Membership Inference in Federated Learning

1. Arroyo Galende, B., Apellániz, P. A., Almodóvar, A., Uribe, S., Álvarez, F., & Parras, J.
Big Data and Cognitive Computing
2026

Real-Time, Interpretable Diagnostics for Solid-State Batteries via Machine Learning on In Situ Impedance Spectra

Warren, Z., Cuasquer, F., Sánchez, R., Apellániz, P. A., Almodóvar, A., Parras, J., & Rosero-Navarro, C.
Battery Energy
2026

Attentive Neural Processes for Fast Trajectory Prediction in Underwater Acoustic Networks

Fernández Salvador, F., Parras, J., & Zazo, S.
IEEE Journal of Oceanic Engineering
2026

Advancing Cancer Research with Synthetic Data Generation in Low-Data Scenarios

Apellániz, P. A., Arroyo Galende, B., Jiménez, A., Parras, J., & Zazo, S.
IEEE Journal of Biomedical and Health Informatics
2026

Enhancing Survival Analysis through Federated Learning in Non-IID and Scarce Data Scenarios

Apellániz, P. A., Parras, J., & Zazo, S.
Computers in Biology and Medicine
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