معرفی
Christos Matsoukas is a Researcher and Industry doctoral student at the Division of Computational Science and Technology, KTH Royal Institute of Technology. His work bridges Artificial Intelligence and Planetary Science, focusing on medical image analysis via advanced machine learning techniques and exploring Titan's surface composition using remote sensing data from missions like Cassini.
His research interests span Medical Image Analysis, leveraging transformer models and self-supervised learning for diagnostic applications, as well as Planetary Science analyzing Titan’s chemical composition through spectral and morphological analysis of craters and geological features. Recent studies investigate the efficacy of foundation models in low-data medical contexts and domain adaptation strategies for high-content imaging.
Publications highlight innovations like Random Token Fusion for multi-view diagnosis, Metadata-guided consistency learning, and compositional mapping of Titan’s surface using Cassini/VIMS and RADAR data. His work contributes to both AI-driven healthcare solutions and understanding Titan’s habitability potential.
