Jose M. Juarez

Jose M. Juarez is a Full Professor at the University of Murcia specializing in Artificial Intelligence for healthcare applications. He leads the MedAI Lab and coordinates the university's AI master studies program, bridging cutting-edge AI research with clinical practice to enhance healthcare delivery.

His research centers on Medical AI and Explainable AI (XAI), developing machine learning, reinforcement learning, and deep learning solutions for real-world clinical challenges including hospital outbreak management, antibiotic resistance phenotyping, and interpretable diagnostic systems. This work prioritizes transparency in AI decision-making to build clinician trust and improve patient outcomes.

Recent publications (2025) reveal a concentrated focus on spatiotemporal epidemiological modeling, with innovations in infection spread visualization, patient trajectory analysis, and subgroup discovery for antimicrobial resistance. His work consistently integrates healthcare informatics with advanced AI to address urgent clinical needs.

Key recognitions include:

• Best Paper Award at AIME (2025)
• Best paper student award HealthInf (2024)

Dr. Juarez maintains an active PhD supervision program across AI and Medical Informatics, mentoring students on hospital outbreak simulation, patient phenotyping, and antimicrobial stewardship. His former students hold positions at NTT Data, Savana (as CTO), and academic institutions.

• AI PhD Cohort: Denisse M. Kim (2024), Antonio Lopez Mtnez-Cararasco (2024), Isidoro Casanova (2023), Eduardo Lupiani (2014)
• Medical Informatics PhD Cohort: Lorena Pujante (2025), Natalia Iglesias (2021), Bernardo Canovas-Segura (2019)

He directs the MedAI Lab which develops deployable AI tools for healthcare institutions, and co-founded both the Spanish Society of AI in Biomedicine (2023) and the XAI-Healthcare workshop (2021) to advance community collaboration in clinical AI research.