Speaker
Description
Prof. Dr. Kurt Stockinger is Professor of Computer Science, Director of Studies in Data Science, and Head of the Intelligent Information Systems Group at Zurich University of Applied Sciences. He is also affiliated with University of Zurich. Kurt Stockinger’s research focuses on Data Science with emphasis on Big Data, Natural Language Query Processing, Query Optimization and Quantum Computing. Essentially, his research interests are at the intersection of information systems, natural language processing and machine learning. Previously Kurt Stockinger was (1) a visiting scholar at University of Washington in Seattle, Washington, USA, (2) he worked at Credit Suisse in Zurich, Switzerland, (3) at Lawrence Berkeley National Laboratory in Berkeley, California, USA, (4) at California Institute of Technology in Pasadena, California, USA, (5) as well as at CERN in Geneva, Switzerland. He holds a Ph.D. in computer science from CERN / University of Vienna.
Summary
Generative AI and Large Language Models (LLMs) are rapidly transforming biomedical research and clinical practice. Yet, a key challenge remains their susceptibility to generating inaccurate or non-factual responses, commonly known as hallucinations. In this talk, we will present recent advances in the use of agentic AI for the exploration of complex, multi-modal medical data. Our approach enables the integration and analysis of heterogeneous data sources, including structured clinical data, textual data and imaging data. We demonstrate how agentic AI systems can reliably interact with these diverse datasets through natural language queries, allowing clinical researchers to explore patient cohorts, uncover relationships across modalities, and generate actionable insights. The presented approach illustrates how trustworthy, agent-based AI can enhance data accessibility and support more intuitive and effective clinical decision-making.