Professor Hamidreza Jamalabadi

His academic journey began in electrical engineering at the University of Tehran, where he completed bachelor’s and master’s training and developed expertise in control systems, machine learning and cognitive robotics. He then moved into neuroscience, completing a PhD in neural information processing at the University of Tübingen. This transition gave him a distinctive research perspective: the brain could be studied not only as a biological organ, but also as a dynamic system whose states, constraints and responses can be modelled mathematically.

During subsequent research appointments at the University of Tübingen, the Max Planck Institute for Biological Cybernetics and Ludwig Maximilian University of Munich, he combined neuroimaging, computational modelling and data science. His work examined multivariate brain data, neural connectivity, cognitive processes and psychiatric symptoms, while addressing the methodological challenges created by high-dimensional biomedical datasets. This period established the interdisciplinary foundation for his later work in computational psychiatry.

At Philipps University Marburg, Professor Jamalabadi leads research that applies dynamical-systems theory, network control theory, machine learning and generative AI to mental health. His group studies how neural, behavioural and psychological trajectories relate to depression and other affective disorders, how treatment response may be predicted, and how interventions can be designed around the dynamics of individual patients rather than static diagnostic labels.

His current work extends from brain controllability and electroconvulsive-therapy response to ecological momentary assessment, multimodal learning and responsible AI for mental health. As a principal investigator in major collaborative programmes, including The Adaptive Mind and the CRC/TRR 393 on trajectories of affective disorders, he brings engineering methods into clinically meaningful research. The MindShift initiative further advances this direction by combining modern AI, basic neuroscience and clinical psychiatry to validate scalable tools for personalised mental-health care.

With more than 160 research publications and a Google Scholar h-index of 21, Professor Jamalabadi has developed a substantial interdisciplinary record across neuroscience, psychiatry, engineering and artificial intelligence. His work moves beyond classification toward mechanistic understanding: identifying the dynamics that shape cognition and mental illness, testing whether those dynamics can be predicted, and developing principled methods for steering them toward healthier outcomes.