Jose David Martin Guerrero

Jose David Martin Guerrero is a Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is conducted within the Intelligent Data Analysis Laboratory (IDAL), focusing on the intersection of quantum computing, machine learning, and biomedical applications.

His research interests span Quantum Machine Learning, Reinforcement Learning for Quantum Control, Deep Learning for Medical Image Analysis, and Long-COVID Symptom Trajectory Modeling. He applies advanced AI techniques to solve complex problems in physics, healthcare, and engineering, particularly in modeling prostate cancer, hemodialysis, and post-COVID neurological and functional impairments.

The recent publications highlight a strong trend toward integrating quantum computing with classical machine learning, especially in developing quantum neural networks, quantum autoencoders, and reinforcement learning for quantum gate optimization. Simultaneously, a significant body of work uses clustering, deep learning, and Bayesian modeling to analyze longitudinal clinical data from multicenter studies like LONG-COVID-EXP, aiming to understand symptom persistence and recovery patterns in post-COVID patients.

Dr. Martin Guerrero earned his PhD from the Universitat de València in 2004 with a thesis on unsupervised techniques for web trend detection and collaborative filtering-based recommendation systems, supervised by Dr. Emilio Soria Olivas and Dr. Paulo Jorge Gomes Lisboa.

His work demonstrates active collaboration across disciplines, particularly in clinical research involving multicenter studies, and in quantum computing applications in physics and finance. While no specific grants are mentioned, his involvement in large-scale clinical studies and quantum computing research suggests significant project leadership and funding acquisition.

He leads research within the Intelligent Data Analysis Laboratory (IDAL), which focuses on self-organizing maps, clustering, learning vector quantization, and their applications in security, healthcare, and quantum systems.