I am interested in the development and repurposing of deep learning algorithms for neurophysiological signals. In particular, I investigate how deep learning algorithms can reduce the calibration times of brain-computer interfaces, increase their robustness, and allow for new invariance. I am also interested in whether deep learning could help push the limits of what can be decoded from EEG and neural signals in general.
PhD in AI and Neurotechnology, Present
Radboud University, Donders Institute
Master in Machine Learning (M2A), 2020
Master in Computer Science (MPRI), 2019
BSc in Fundamental Computer Science, 2018