Mikel completed his masters degree in computer science at the university of Duesseldorf and holds a Bachelor degree in Economics from the Westfälische Hochschule. His research interests are models for heterogeneous and multimodal graph representation learning along with their applications within the medical domain. In his master thesis he investigated upon models for learning and simulating large scale and heterogeneous graphs. As a PhD candidate at WisPerMed Research Training Group, Mikels research centers around applying Graph Representation Learning techniques such as GNNs along with intersecting Large Language Models to patient graphs derived from FHIR resources to facilitate various AI based approaches such as patient profile modeling or synthetic data generation and discover synergies between graph and language based models.