Stergios Christodoulidis

Stergios Christodoulidis is a researcher specializing in artificial intelligence and its applications in medical imaging and earth sciences. His work spans deep learning methodologies for image analysis, including multiple instance learning, dosiomics, and registration techniques. He contributes to interdisciplinary research in computational biology, digital pathology, and radiomics.

• Core research in AI-driven medical image analysis
• Contributions to earth sciences through remote sensing and satellite imagery
• Focus on low-data regimes and uncertainty quantification in AI models

His recent publications highlight innovative approaches in:

• Visually grounded bias discovery in clinical AI
• Conformal prediction adaptation for vision-language models
• Self-supervised learning for histopathology and radiology applications
• Integration of biological constraints in machine learning workflows