About me

Applied AI research with impact
Ph.D. candidate at UPM researching on applied Artificial Intelligence for personalized medicine.
GAPS
SSR
ETSIT
UPM
IPTC
6 Publications
1 Q1 Journals
2 R&D Projects
6 Citations
2 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

Deep survival analysis in multimodal medical data: A parametric and probabilistic approach with competing risks

Garrido, A., Almodóvar, A., Apellániz, P. A., Zazo, S., & Parras, J.
Scientific Reports
2026

Trust-Aware Counterfactual Generation for Validating Causal Inference in Clinical Observational Data

Almodóvar, A., Elizo, M., Garrido, A., Apellániz, P. A., Zazo, S., & Parras, J.
2026

Interpretable Causal Survival Analysis with Kolmogorov-Arnold Networks

Almodóvar, A., Garrido, A., Elizo, M., Apellániz, P. A., Zazo, S., & Parras, J.
IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
2026

Not All Jensen-Shannon Divergence Estimators Are Equal

Garrido, A., Almodóvar, A., Elizo, M., Apellániz, P. A., Zazo, S., & Parras, J.
2026

Censoring-Aware Deep Learning for Patient-Level Causal Survival Analysis in Medical Data

Almodóvar, A., Elizo, M., Benoit-Perejon, J. Z., Garrido, A., Apellániz, P. A., Zazo, S., & Parras, J.
Browse full publication list →
In the Media
2026

¿Cómo la Inteligencia artificial puede ayudar tratar las enfermedades raras?

La Vanguardia (México) · Digital news · Healthcare AI
2026

Algoritmos nómadas: el fin del aislamiento de las enfermedades raras

The Conversation · Article · Healthcare AI