Computational Psych Lab

Welcome to our lab. We work on new computational methods in psychology and psychiatry. Our aim is to improve clinical practice and theoretical understanding in this field. We use innovative data sources and new computational techniques. This includes methods from statistics, computer science and machine learning. We combine various signals like audio, video and neurophysiological measures to get a better understanding of what happens, e.g. during psychotherapy.

Check out our new paper on Ant Colony Optimization (ACO) to develop a questionnaire for the identification of personality disorders.

There are currently no new positions available at our lab.

Recent publications

A swarm intelligence machine learning algorithm for test development Silence in Psychotherapy Supervised speaker diarization using Random Forests
In this study we used the "intelligence" of a swarm of ants to develop a short questionnaire to detect personality disorders in adolescence. Check out our study on Plos One.
Usually, silence is an important thing in psychotherapy. However, in this study we studied the association of silence in psychotherapies of adolescent patients. Find out more about this study below. Who speaks when? This information is key, when you want to find out about the flow of a conversation, also in psychotherapy. This study by Fürer et al. introduces a methodology to diarize the audio signal for two different speakers.
Steppan / Zimmerann, et al. Zimmermann, et al. Fürer, et al.
Plos One Personality Disorders: Theory, Research and Treatment Frontiers in Psychology