
Jaime Cardoso
Research Coordinator
Jaime S. Cardoso holds a Licenciatura (5-year degree) in Electrical and Computer Engineering in 1999, an MSc in Mathematical Engineering in 2005 and a Ph.D. in Computer Vision in 2006, all from the University of Porto.
Cardoso is an Associate Professor with Habilitation at the Faculty of Engineering of the University of Porto (FEUP), where he has been teaching Machine Learning and Computer Vision in Doctoral Programs and multiple courses for the graduate studies. Cardoso is currently a Senior Researcher of the ‘Information Processing and Pattern Recognition’ Area in the Telecommunications and Multimedia Unit of INESC TEC. He is also Senior Member of IEEE and co-founder of ClusterMedia Labs, an IT company developing automatic solutions for semantic audio-visual analysis.
His research can be summed up in three major topics: computer vision, machine learning and decision support systems. Cardoso has co-authored 150+ papers, 50+ of which in international journals. Cardoso has been the recipient of numerous awards, including the Honorable Mention in the Exame Informática Award 2011, in software category, for project “Semantic PACS” and the First Place in the ICDAR 2013 Music Scores Competition: Staff Removal (task: staff removal with local noise), August 2013. The research results have been recognized both by the peers, with 6500+ citations to his publications and the advertisement in the mainstream media several times.
Publications
Enhancing Weakly-Supervised Video Anomaly Detection With Temporal Constraints
Caetano, F;Carvalho, P;Mastralexi, C;Cardoso, JS;
2025
IEEE ACCESS
An inpainting approach to manipulate asymmetry in pre-operative breast images
Montenegro, H;Cardoso, MJ;Cardoso, JS;
2025
CoRR
CountPath: Automating Fragment Counting in Digital Pathology
Vieira, AB;Valente, M;Montezuma, D;Albuquerque, T;Ribeiro, L;Oliveira, D;Monteiro, JC;Gonçalves, S;Pinto, IM;Cardoso, JS;Oliveira, AL;
2025
CoRR
Parameter-Efficient Generation of Natural Language Explanations for Chest X-ray Classification
Rio-Torto, I;Cardoso, JS;Teixeira, LF;
2024
MEDICAL IMAGING WITH DEEP LEARNING
Supervised Theses
Machine Learning Applied to Fall Prediction and Detection Using Wearable Sensors
Joana Raquel Cerqueira da Silva
D - 2019
UP-FEUP
A Deep Learning-based Radio-Pathomics Approach for Breast Tumor Signature
Sara Isabel Pires de Oliveira
D - 2019
UP-FEUP
Deep Aesthetic Assessment of Breast Cancer Surgery Outcomes
Wilson José dos Santos Silva
D - 2019
UP-FEUP
Towards Automatic Detection and Quantification of Gait in Arthritic Rats
Ana Filipa Adonias Costa
M - 2019
UP-FEUP


