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Stefan Haufe is a Professor at Technische Universität Berlin, leading an interdisciplinary research group focused on machine learning and uncertainty modeling in neuroimaging and medical data. He specializes in the development and validation of signal processing techniques and their applications in inverse modeling and machine learning. His expertise is recognized through joint appointments, including a position at the Physikalisch-Technische Bundesanstalt Berlin, where he heads Working Group 8.44 on Machine Learning Uncertainty. Additionally, Haufe directs the ERC-funded Braindata Group at Charité - Universitätsmedizin Berlin, which conducts advanced research on brain data interpretation. He has an extensive academic background with postdoctoral experiences at prestigious institutions, including Columbia University and UC San Francisco, where he has contributed significantly to the field of computational neuroscience. His proactive involvement in research collaborations and various projects further accentuates his commitment to advancing the understanding of complex data interactions in medical settings.
Technische Universität Berlin • Berlin, Germany
Head of FG UNIML, leading research on Machine Learning and Uncertainty.
Physikalisch-Technische Bundesanstalt Berlin • Berlin, Germany
Leading research on Machine Learning Uncertainty.
Charité - Universitätsmedizin Berlin • Berlin, Germany
Direction of research focused on brain data analysis.
Requirements are consistent for general engineering and computer science programs. Specific advanced master's (MBA/Energy) may require 1 year of professional experience.