Jordan researches machine learning in ESM studies.
Jordan is a PhD student at KU Leuven under the supervision of Eva Ceulemans and Ginette Lafit. His research focuses on longitudinal models and data, particularly in Experience Sampling Methods (ESM), where he develops methods for sample size planning, data preprocessing, and quality assessments. Additionally, he investigates how ESM characteristics (e.g., designs, missing data patterns) influence model performance. This November, he is visiting Mirka Henninger's group to explore machine learning and interpretable methods for ESM studies.