Jaime S. Cardoso

INESC TEC · Faculty of Engineering, University of Porto

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INESC TEC
Faculty of Engineering, University of Porto
Porto, Portugal

I am a Full Professor at the Department of Electrical and Computer Engineering (DEEC), Faculty of Engineering of the University of Porto (FEUP), Portugal. I am also a researcher at INESC TEC (Centre for Telecommunications and Multimedia).

My research lies at the intersection of artificial intelligence, computer vision, medical imaging, and machine learning, with a particular focus on developing trustworthy AI systems for healthcare. My interests include explainable AI, uncertainty quantification, robust machine learning, multimodal learning, and clinical decision support systems.

My goal is to develop AI methodologies that are not only accurate but also transparent, reliable, and clinically meaningful, enabling their safe integration into real-world healthcare workflows. I am particularly interested in bridging methodological advances in machine learning with impactful applications in medical imaging.

At INESC TEC, I co-founded:

I have supervised numerous MSc and PhD students and regularly collaborate with academic institutions, hospitals, and industrial partners on national and international research projects.

Prospective Students

I welcome inquiries from prospective PhD students and postdoctoral researchers interested in artificial intelligence, computer vision, medical imaging, trustworthy machine learning, explainable AI, and healthcare applications.

Learn here why Portugal is an excellent destination for advanced studies and research.


Academic Profiles


Recognition

selected publications

  1. Information bottleneck for attribution applied to object detection
    Bruno Coelho and Jaime S. Cardoso
    IEEE Transactions on Artificial Intelligence (TAI), 2026
  2. CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification
    Cristiano Patricio, Isabel Rio-Torto, Jaime S. Cardoso, Luis F. Teixeira, and Joao C. Neves
    Computers in Biology and Medicine (Elsevier), 2025
  3. Unimodal Distributions for Ordinal Regression
    Jaime S. Cardoso, Tome Albuquerque, and Ricardo P. M. Cruz
    IEEE Transactions on Artificial Intelligence (TAI), 2025
  4. Anonymizing medical case-based explanations through disentanglement
    Helena Montenegro and Jaime S. Cardoso
    Medical Image Analysis (Elsevier), 2024
  5. Weather and Meteorological Optical Range Classification for Autonomous Driving
    Celso Pereira, Ricardo Cruz, Joao Fernandes, Joao Pinto, and Jaime S. Cardoso
    IEEE Transactions on Intelligent Vehicles, 2024
  6. Machine Learning Interpretability: A Survey on Methods and Metrics
    Diogo Vaz Carvalho, Eduardo Marques Pereira, and Jaime S. Cardoso
    Electronics (section: Artificial Intelligence), 2019