Alvaro Gonzalez-Jimenez

Alvaro Gonzalez-Jimenez is a Post-Doc Researcher at University Hospital of Basel and a Research Associate at the Applied Artificial Intelligence (AAI) Research Lab at Lucerne University of Applied Sciences and Arts (HSLU). He completed his PhD in Biomedical Engineering at the University of Basel in 2025 with Summa Cum Laude distinction. His academic journey includes a Master's degree in Computer Science from Grenoble Institute of Technology and a Bachelor's degree from the University of Sevilla.

His educational background includes:

• 2021-2025: PhD in Biomedical Engineering, University of Basel ("Learning Dermatology with Noisy and Limited Data")
• 2019-2020: MSc in Computer Science, Grenoble Institute of Technology
• 2014-2015: BSc in Computer Science, Budapest University of Technology and Economics (ERASMUS)
• 2013-2018: BSc in Computer Science, University of Sevilla

Gonzalez-Jimenez's research focuses on the intersection of machine learning and dermatology, with particular emphasis on developing methods that can learn effectively from noisy and limited medical data. His work spans several key areas including:

• Robustness in AI systems for medical applications
• Hyperbolic geometry for medical anomaly detection
• Medical image segmentation with noisy labels
• Dermatology-focused AI applications

His recent publications demonstrate a strong trend toward addressing critical challenges in medical AI, particularly in dermatology. His work frequently explores innovative approaches to handle limited and noisy data in medical contexts, with a growing emphasis on geometric deep learning and robust optimization techniques. His research has significant implications for making AI-assisted dermatological diagnosis more accessible and reliable, especially in resource-limited settings.

His scientific achievements include:

• Best Paper Award at MICCAI 2023
• Early Acceptance (Top 9%) at MICCAI 2025 for "Is Hyperbolic Space All You Need for Medical Anomaly Detection?"
• Early Acceptance (Top 11%) at MICCAI 2024 for "PASSION for Dermatology"

Gonzalez-Jimenez is actively involved in several research projects including PASSION (focusing on dermatology in Sub-Saharan Africa), SelfClean (for data cleaning), and T-Loss (for robust medical image segmentation). He co-organizes the first Hyperbolic Learning for Medical Imaging (HyperMI) tutorial at MICCAI 2025, reflecting his leadership in emerging AI methodologies for medical applications.