Projects

CALM4GRAINS develops cross-domain adaptation and learning methods for microscopy as Subproject 2 of the coordinated GRAINS project on green and responsible AI for sustainable bioimaging.

AIM-Net is a national Spanish research network that connects microscopy, quantitative biology, and AI groups to integrate bioimaging data across molecular, cellular, and tissue scales.

TOSBI develops scalable and generalizable deep learning methods for biomedical image analysis, with a focus on limited annotation, computational efficiency and robust transferability.

Development of novel deep learning methods for biomedical and facial image analysis, focusing on data efficiency, generalization, and scientific reproducibility.

CARLA explores methods of computer vision and artificial intelligence in scenarios with limited annotated data, targeting biomedical and facial image analysis applications.