Alejandro Guerrero-López

Alejandro Guerrero-López

Applied ML for healthcare and medical data science. Trustworthy AI, multimodal decision-support, and open-source tools.

Alejandro Guerrero-López

Overview

I am a postdoctoral researcher at the Institute of Medical Microbiology (IMM), University of Zurich (UZH), working in Prof. Dr. Adrian Egli’s group. From July 2026, I will hold a Marie Skłodowska-Curie Postdoctoral Fellowship (MSCA PF) for OUTBRAID, a project on AI-driven outbreak detection from multimodal microbiology data.

My long-term goal is to build an independent research group in applied machine learning for health and medical data science. I work on clinically grounded AI problems together with domain experts, with a focus on multimodal clinical decision support, trustworthy biomedical AI, and open-source tools and datasets that make advanced methods usable for clinicians, microbiologists, and biomedical researchers.

Research Program

  • Multimodal clinical decision support. I develop machine learning methods that integrate heterogeneous biomedical data and expert knowledge to support diagnosis, surveillance, and treatment-related decisions.
  • Trustworthy biomedical AI. I am interested in interpretable, reliable, and clinically useful AI systems that can be understood and evaluated by the professionals who use them.
  • Open-source software and data resources. I build reusable tools, applications, and public datasets that lower the barrier for applying AI in real health workflows.

Selected Outputs

Funding, Leadership, and Current Activities

  • MSCA PF awardee (2026-2028). I was awarded a Marie Skłodowska-Curie Postdoctoral Fellowship for OUTBRAID, focused on AI-driven outbreak detection with multimodal microbiology data.
  • Supervision and mentoring. I have supervised 3 BSc theses, 8 MSc theses, and I currently co-supervise 3 PhD students.
  • Teaching and training. I have contributed to undergraduate, master’s, and professional training in machine learning and health data science, and I currently participate as faculty in the ESCMID AI and Machine Learning in Medical Microbiology Diagnostics course.
  • Scientific community engagement. My recent activities include invited talks, participation in international workshops, and contributions to community-facing open science efforts in biomedical AI.
  • Open-source translational development. I am currently developing an AST application to turn AI models into a practical, reusable tool for microbiology workflows.

Short Bio

Collaborate

I am especially interested in collaborations at the interface of AI in healthcare, medical data science, clinical microbiology, speech-based biomarkers, and medical imaging. If you are building clinically meaningful AI systems, translational software, or open biomedical data resources, feel free to get in touch.