Published a book chapter in 'Women, Technology, and Power'; EU-CERV funded project InterVisions officially started, focusing on bias auditing for multimodal foundation models; Paper 'Over the Top-1: Uncertainty-Aware Cross-Modal Retrieval with CLIP' accepted at UAI 2025; Paper 'Measuring Text-Image Retrieval Fairness with Synthetic Data' accepted at SIGIR 2025.
Research Experience
Currently a Research Fellow (Ramón y Cajal RYC2020-030775-I) at Universitat Autonoma de Barcelona and a member of the Computer Vision Center (CVC). Former TECNIOspring Research Fellow (2018-2020), co-funded by the European Commission under the Marie Skłodowska-Curie Actions. Had research stays at Media Integration and Communication Center (MICC) in Florence, Italy, and Intelligent Media Processing Group in Osaka, Japan. An active contributor to the ICDAR Robust Reading Competitions.
Education
No specific educational background information provided.
Background
Research interests lie at the intersection of computer vision, machine learning, and responsible AI. Currently, his research focuses on detecting and mitigating algorithmic bias in multimodal AI systems, as well as addressing privacy and ethical concerns in deep learning algorithms. He is also involved in applying computer vision techniques to the analysis and preservation of cultural heritage assets.
Miscellany
Has a strong interest in the social implications of AI and aims to make deep learning models more fair and interpretable.