Yağmur is from Cyprus. She studied Biomedical Science at The University of Hull and completed her master’s degree in Data Science for Life Sciences at Hanze University of Applied Sciences. Afterwards, she joined Trinity College Dublin/ADAPT Centre, contributing to the HELICAL and later to the PARADISE project. She is particularly interested in applying her expertise to health-related challenges. In April 2025, she joined MERLN for her PhD work and the focus of her research is on Automated Knowledge Graphs for Kidney Physiology and Pathology. The progressive decline in kidney function leads to the accumulation of toxins, accelerating chronic kidney disease (CKD) and its comorbidities. The proximal tubule (PT) plays a vital role in toxin and drug elimination, yet the mechanisms behind these interactions remain unclear. As part of the project, her responsibility is to build a map of PT transport and metabolism and implement an automated workflow. This work, and the automation thereof, will contribute to the development of dynamic models to better predict and manage the complex interactions occurring in CKD.