MINOAS Workshop – Day 1 at ICS-FORTH

The workshop opened with two inspiring keynote lectures. Philippe Ciuciu presented the latest advances in computational imaging and machine learning for MRI, demonstrating how data-driven methods are reshaping the future of medical imaging. Maria Vakalopoulou followed with a keynote on deep learning for medical image analysis, highlighting methodologies with strong clinical impact and the potential to significantly improve healthcare outcomes.

The afternoon of the first day featured two additional talks that expanded the discussion into new domains. Diarra Fall spoke on “Bayesian Image Restoration with Deep Learning-Based Priors,” providing novel perspectives on combining Bayesian methods with modern machine learning for improved image restoration. Vagelis Harmandaris then presented “Physics-informed and ML-based Models for Inverse Problems in Multi-scale Modeling of Complex Materials,” bridging the gap between physical modeling and data-driven techniques in the study of complex systems.

The day concluded with an engaging poster session, where participants shared their ongoing research and fostered lively scientific discussions. This interactive exchange underscored the collaborative spirit of MINOAS, offering a platform for both established experts and early-career researchers to connect and explore new ideas.