Daniel Sonntag

Daniel Sonntag is a Research Professor at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern, Germany, with extensive contributions to artificial intelligence, particularly in medical applications and human-AI interaction. His work spans multiple domains including explainable AI, medical imaging analysis, eye tracking technology, and clinical decision support systems.

His research interests focus on developing interpretable AI systems for healthcare applications, with particular emphasis on ophthalmology and radiology. He investigates how to make AI systems more transparent and trustworthy through concept bottleneck models, multi-agent systems, and interactive learning approaches. His work bridges the gap between theoretical AI advancements and practical clinical applications, ensuring that AI tools are both effective and understandable for medical professionals.

Sonntag's publication record demonstrates a consistent trend toward more interactive and interpretable AI systems, with recent work focusing on multi-agent RAG systems for radiology report generation, clinical decision support tools for ophthalmology, and biodiversity monitoring through soundscape analysis. His research shows a strong interdisciplinary approach, combining computer vision, natural language processing, and human-computer interaction to solve complex problems in healthcare and environmental monitoring.

His work has appeared in leading venues including IUI, ICMI, KI, and various IEEE and ACM conferences, reflecting his contributions to both the theoretical foundations and practical applications of artificial intelligence.