Title: Uncovering Brain Dynamics Using Directional Statistics and Functional Neuroimaging Data.I develop unsupervised machine learning models to leverage the potential of dynamic functional brain connectivity to inform on brain function in both resting state and task fMRI, EEG, and MEG. Specifically, I focus on scale and polarity invariant models of interregional brain coherence networks using methods from directional statistics. Main supervisor: Prof. Morten Mørup

Developed a dynamic functional connectivity model by accounting for the geometric structure of oscillatory processes. I applied my model to fMRI data from a psilocybin study to further our understanding of the acute effects of 5-HT2AR modulation on network-level brain activity.

Data analysis and signal processing of EEG/fMRI data for a large sleep study at Rigshospitalet. Primary focus is processing of EEG data corrupted by MR-artifacts using machine learning techniques.

Part-time administrative worker at the department of medical technologies. Work mainly included mapping the amount of medical equipment belonging to different hospital sections with the purpose of future relocation.

Held weekly classes in the course Cell and Tissue Biology (10 ECTS) given on the 3rd semester of the bachelor education in Biomedical Engineering.

Weekly tasks for the research unit Center for Hyperpolarization in Magnetic Resonance (HYPERMAG) at DTU

Part of a team of students aiding hospital employees in the use of the new IT-system "sundhedsplatformen".

PostNord Copenhagen (1y)PostNord Kalundborg (2y)KWIK Spar Kalundborg (2,5y)Kalundborg Golf Club (1y).