KIONA K. WEISEL, MSc
Tel (+49) 09131-85 67570
Kiona Weisel studied Business Psychology (B.Sc.) with a minor in Digital Media and Cultural Informatics at the Leuphana University Lüneburg. After her undergraduate studies, she completed a graduate program (M.Sc.) in Information Technology and Cognition at the University of Copenhagen in Denmark. The main focus of the program was on the practical application of data analysis on large datasets with Machine Learning in Python, natural language processing and cognitive science. In the second year of her graduate program she worked as a student research assistant in the lab Valuation and Decision-Making of Dr. Jan Gläscher at the Institute for Systems Neuroscience at the University Medical Center Hamburg-Eppendorf. Her main tasks included the data collection and completion of social decision making experiments, the preparation of MRT experiments, and the analysis of experimental data with Matlab.
She has always been fascinated by the interface between psychology and digitalization, and therefore in late 2015 decided to pursue a PhD in the field of digital mental health at the Friedrich-Alexander-University Erlangen-Nürnberg. Her PhD focuses on trends and developments in internet-based and mobile-based interventions for mental health. Since 2015, Kiona Weisel has been working as a scientific researcher in the EU-funded project ICare „Integrating Technology into Mental Health Care Delivery in Europe”. As co-study coordinator, she is responsible for the planning, realization and evaluation of randomized-controlled trials in the field of transdiagnostic prevention and treatment of anxiety disorders and major depressive disorder.
Kiona Weisel has presented her scientific work at international and national conferences: European Society for Research on Internet Interventions (ESRII), International Society for Research on Internet Interventions (ISRII), Deutsche Gesellschaft für Psychologie (DGPs).
digitalization, mental health, internet interventions, mHealth, risk factors and risk profiles in mental health, transdiagnostic approaches for anxiety and depression, machine learning