Aman completed his PhD in Bioinformatics at the University of Duisburg-Essen, where he developed computational workflows for the analysis of sequencing data. His work focused on building robust, reproducible pipelines that enable researchers to reliably process and analyze new datasets.
He is now a postdoctoral researcher in the CARE group (Clinical Research and Real-World Evidence) at IKIM. His current research focuses on developing agentic AI workflows for patient urgency monitoring and clinical shift handovers using electronic health records.
His broader goal is to help move agentic AI from promising demonstrations toward dependable clinical infrastructure. By bringing a methods-oriented perspective to CARE’s real-world evidence research, he contributes to IKIM’s mission of translating data-driven AI methods into measurable improvements in patient care.
