Computational Psychiatry 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 during psychotherapy.

We would like to congratulate Martin to his new job at the Faculty of Psychology of the University of Basel

There are currently no new positions available at our lab.

Recent publications

Machine Learning Emotion Recogntion in Psychotherapy Silence in Psychotherapy Supervised speaker diarization using Random Forests
Why smiling and happiness is associated to better therapy outcome? This study investigates the potential of machine learning emotion recognition in psychotherapy process research. 
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, et al. Zimmermann, et al. Fürer, et al.
Psyarxiv Personality Disorders: Theory, Research and Treatment Frontiers in Psychology