معرفی
David Steyrl is an active researcher in the Faculty of Psychology, Department of Cognition, Emotion, and Methods in Psychology. His academic credentials include Dipl.-Ing. Dr.techn., indicating a technical doctorate. With 73 publications spanning from 2012 to 2025, his research output shows consistent productivity with recent activity including 8 publications in 2024 and 7 publications in 2025.
Steyrl's research interests center on the intersection of neuroscience, psychology, and computational methods. His work prominently features brain-computer interfaces, neuroimaging techniques (particularly fNIRS and EEG), and the application of machine learning to psychological questions. His research fingerprint reveals strong expertise in Brain-Computer Interface (100% Neuroscience), Functional Magnetic Resonance Imaging (91% Psychology), Neurofeedback (90% Psychology), and Random Decision Forests (54% Computer Science).
His recent publications demonstrate a clear trend toward applying machine learning methods to complex neuroscience and psychological questions, with particular focus on PTSD, interbrain synchrony, climate-related behaviors, and relationship quality in sexual minority populations. Steyrl has also been active in presenting his work, with recent talks on interpretable machine learning frameworks for hypothesis testing.
Steyrl has participated in research projects including 'Jointly Optimized Allocation of Functionality in Systems of Systems' (2021-2024), indicating collaboration with researchers like Scharnowski and Melinšcak. His work contributes to UN Sustainable Development Goals, particularly in areas related to health and well-being.
