Machine learning for clinical time-series forecasting: an interview with Mayra Elwes

In a series of interviews, we're meeting some of the PhD students that were selected to take part in the Doctoral Consortium at the International Joint Conference on Artificial Intelligence and the 29th European Conference on Artificial Intelligence (IJACI-ECAI 2026) . This time, we hear from Mayra Elwes about her work developing machine learning methods for clinical time-series data. Tell us a bit about your PhD - where are you studying, and what is the topic of your research? I am a second-year computer science PhD student at the Institute for Biomedical Informatics at the University Hospital Cologne. My research focuses on the generalisation and domain adaptation of machine learning for clinical time-series forecasting, especially for clinic-to-clinic generalization scenarios.