Hoe gek is Nederland? (translation: "How nuts are the Dutch?") is an online platform designed to support self-measurement of mental health for the entire population of the Netherlands by allowing them to fill out questionnaires and by providing them with personalized feedback. Currently, the web application has ~11,000 active users. One of the ways that we provide feedback is by applying Autovar to find VAR models that determinine contemporary and causal relations between quality of life indicators of EMA data. We then plot those relations as graphs to provide insight to the user, e.g., for identifying the indicators that have a high likelihood of being significant for improving their well-being. To the best of our knowledge, this is the first fully-automated derivation and application of vector autoregression models. This project is an initiative of the ICPE and was conceived as a pilot study for the Leefplezier project funded by Espria.

Leefplezier (translation: "Well-being") is an online platform to support self-measurement of mental health for the elderly population of the Netherlands by allowing them to fill out questionnaires and by providing them with personalized feedback. Here, we aim to provide the same depth of feedback as for HoeGekIsNL but with focus on the elderly and on the issues that are important to them. This project is an initiative of the ICPE and is funded by Espria.

Autovar is an R package (with a web application front end) that I developed to automate the process of generating vector autoregression (VAR) models for time series data (in particular: EMA data). The application covers the entire range from preprocessing to optimal VAR model creation and analysis. This project was conceived by Elske Bos, Judith Rosmalen, and Peter de Jonge from the University Medical Center Groningen.

Wegweis is a web application designed for schizophrenia patients that offers direct access to assessment results and to personalized advice based on those assessment results. We use an ontology-based approach to prioritize information in order to provide patients a second opinion and to better prepare them for discussing their treatment plan. This project is a joint initiative of the Computer Science Department of the University of Groningen and the Department of Psychiatry of the University Medical Center Groningen.

I received my Ph.D. degree in Computer Science at the University of Groningen, focusing on knowledge management, data mining, automating vector autoregression, statistical inference, ontological reasoning, and personalization. I received my B.Sc. and M.Sc. (cum laude) degrees in Computer Science at the University of Groningen, with the specialization Intelligent Systems. During my studies, I also worked ~2.5 years as a teaching assistant for several courses.