Abstract: Primoz Kocbek's (University of Maribor, Expected 2021) research focuses on interpretability and the use of synthetic data in machine learning models processing electronic health record (EHR) data. In particular, Primoz's research examined and provided a more nuanced analysis of the kinds of interpretability enabled by various kinds of models, including classifications of models as providing local vs. global or model-dependent vs. model-agnostic interpretability. Primoz also hopes to extend his research in the future with the use of synthetic data as additional structure to data, primarily leveraging the natural graph structure of some subsets of EHR data to improve predictive power.