About Me

I have a background in psychology with a focus on cognitive neuroscience and clinical psychology, but I have been drawn to computer science, machine learning, and artificial intelligence from an early stage in my academic career. I enjoy working at the intersection of these fields, applying statistical modeling and machine learning to better understand mental disorders.

During my PhD, my research focused on individualized prediction in precision psychiatry, where I pursued two main directions. First, in collaboration with Ramona Leenings, I co-developed photonai, a machine learning software designed to make advanced ML tools more accessible to researchers. Second, I investigated biomarkers for major depression, systematically analyzing univariate and multivariate approaches using photonai.

Currently, my research spans multiple areas, including normative modeling, brain age prediction, depressive subtype identification, and canonical correlation analysis. Beyond these methodological advances, I am also deeply interested in theoretical models of mental disorders and network dynamics.

In addition to my research, I am a member of the Otto-Creutzfeldt-Center for Cognitive and Behavioral Neuroscience (OCC), where I engage in interdisciplinary discussions on neuroscience and cognition.