I have a MSc in Biomedical Engineering from the Technical University of Denmark, during which I have directed my studies towards signal processing, computational data analysis and machine learning. A particular interest for machine learning and how it can be used to further our understanding of sleep has led me to pursue projects such as Validation and Optimization of Automatized Sleep Spindle Detectors in Elderly Healthy Subjects and Patients with Parkinson’s Disease, A Mathematical Model of Hyporectin Neurons’ Synaptic Efficacy in Different Patterns of Sleep and A Dynamical Model of the Circadian Rhythm-Synchronization. I am currently a Ph.D.-student at the University of Copenhagen, where I am investigating how we can use different deep learning models to automatize the manual sleep stage classification procedure, identify biomarkers and find new substages of sleep/wake in mice. I love to spend my free time on crossfit and roadbiking.