scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
I am a postdoc specializing in unsupervised ML methods for understanding the dynamics of brain connectivity and function. I apply my methods to functional neuroimaging data from healthy controls and consciousness-perturbing experiments and patient groups, including psychedelic drugs, coma-patients, and sleep. During my PhD I focused on methods for modeling phase coherence networks in the healthy human brain using functional neuroimaging data, including fMRI and M/EEG. At the Neurobiology Research Unit I currently work on human fMRI/EEG/PET/SPECT/ASL data from psilocybin/lsd and sleep experiments as well as porcine EEG/fMRI/SPECT data from a glymphatic system experiment.
I maintain a close collaboration with the lab of Prof. Morten Mørup, who supervised my BSc/MSc/PhD. Furthermore, I collaborate with the lab of Prof. Dimitri Van De Ville in Geneva, Switzerland, where I have studied graph signal processing of functional neuroimaging data on structural connectomes.