George Aalbers is a postdoctoral researcher at the Psychiatry department of the Amsterdam UMC, location VUmc. His current research focuses on recognising and forecasting depression with smartphone- and wearable-based data and machine learning. Previously, George applied cross-sectional and time-series network analysis to study psychopathology and its relation to social media use. Most recently, his PhD research (conducted at Cognitive Science & Artificial Intelligence, Tilburg University) combined methodological and conceptual insights from psychology, computational, and communication science to predict momentary well-being from passively logged smartphone app use. George is trained in Communication Science (BSc) and Clinical Psychology (BSc; rMSc) at the University of Amsterdam.

Research question

“To what extent can we predict the presence of depression and/or anxiety disorders from smartphone- and wearable-based data, and what are the most important features for doing so?”


Three studies apply an explainable machine learning approach to multi-modal Dutch and international cohort data, quantifying the link from smartphone- (location, phone use, in-app surveys) and wearable-based (sleep, physical activity) data to gold-standard measures of depression and anxiety disorders. By combining feature selection with cross-validation and explanation of machine learning models, I aim to identify behavioural predictors of psychiatric status that might be useful for monitoring daily life stress.

George Aalbers

Amsterdam UMC

Portrait photo of George Aalbers