Daniel Hauke joined King’s College London in 2026 as an AI+ Senior Academic Research Fellow and Wellcome Early Career Award holder. His research in computational psychiatry integrates computational modelling, AI and neuroimaging with clinical expertise to address critical challenges in psychiatry including patient subtyping, treatment response prediction and prognosis. As part of King's AI+ Initiative, he contributes to advancing responsible and clinically meaningful applications of artificial intelligence in healthcare research, policy and education.

Daniel completed a BSc in Psychology at the University of Göttingen and the Universidade Federal do Ceará, followed by an MSc in Cognitive Neuroscience at Maastricht University, where he conducted his master's research at the Translational Neuromodeling Unit, University of Zurich and ETH Zurich. He earned his PhD in Computer Science at the University of Basel and the Krembil Insitute for Neuroinformatics in Toronto. Before joining King's, Daniel was a Senior Research Fellow in Prof Rick Adam's lab at UCL. His work at UCL focused on developing methods to infer cell and neuroreceptor function from non invasive data. He validated these models in pharmacological studies and across the psychosis spectrum through collaborations with major international consortia, including the North American Prodrome Longitudinal Study (NAPLS) and the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP).

Daniel’s long term goal is to establish “computational assays” that test for cell or receptor abnormalities in psychiatric and neurological disorders. This includes 1) identifying new drug targets using digital twin simulations, 2) identifying critical time windows for early interventions and 3) using model parameters as biologically explainable (XAI) predictors for treatment response and transition risk to advance personalized care.