Bio


I am a postdoctoral scholar at the Stanford Center for Biomedical Informatics Research. I earned my PhD in Biomedical Sciences from KU Leuven, Belgium. My research during my PhD program focused on machine learning applications in healthcare, particularly in the field of survival analysis.

My doctoral thesis was centered on the development of predictive models for critically ill patients with acute kidney injury (AKI). By leveraging electronic health record (EHR) data, we created personalized risk profiles for AKI survivors upon ICU discharge, leading to tailored follow-up plans. Additionally, we developed machine learning-based models to predict outcomes post-AKI, including progression to chronic kidney disease (CKD) and mortality.

In another study, we investigated the utilization of unlabeled data to enhance the accuracy of survival time predictions. By integrating partial supervision from censored data within a semi-supervised wrapper approach, we consistently achieved superior results. This approach has the potential to significantly improve survival outcome predictions, offering valuable insights for clinical decision-making.

In my current role at Stanford, I continue to advance the integration of machine learning in healthcare, collaborating with experts to improve patient care and outcomes.

Professional Education


  • PhD, KU Leuven, Biomedical sciences (2023)

Stanford Advisors