Data-Driven Neurotechnology Lab, Donders Institute, Radboud University
After graduation in Computer Science and receiving a PhD from the University of Tübingen, Germany, Michael Tangermann was a member of the Berlin BCI (BBCI) research lab at the TU Berlin before he became head of the brain state decoding laboratory at the Albert-Ludwigs-University of Freiburg, Germany in 2013 and served as a substitute professor of the Autonomous Intelligent Systems Lab in Freiburg. Since 2021, he is assoc. professor at the Donders Institute in Nijmegen, Netherlands, where he is the head of the Data-Driven Neurotechnology lab and head of the Dept. Machine Learning and Neural Computing at the Radboud University. Michael Tangermann investigates machine learning approaches to tackle neuroscientific and neurotechnological data problems. His research interests comprise adaptive unsupervised and supervised methods for the classification and regression of non-stationary brain signals, regularization techniques, reinforcement learning and deep learning. He translates these methods into clinical brain-computer interface applications (e.g. for rehabilitation of stroke-induced hand motor and language deficits, closed-loop deep brain stimulation in Parkinson's disease).
