I am a PhD student, currently work on the interface between machine learning and near-term quantum computers. My interests lie mainly within noisy gate models and NISQ approaches such as QAOA and VQE.
I have a Master of Science degree in biomedical engineering (M.Sc.Eng.) from The Technical University of Denmark (DTU) and I previously worked on statistical machine learning in neuroscience as a research assistant at Section for Cognitive Systems, Department of Applied Mathematics and Computer Science.
This website is my online resume, containing past, current and upcomming projects as well as demos, relevant materials and news. It is not anywhere near finished, but I still hope you take a look around and don't hesitate to contact me!
For the past years I have been working on projects in various research groups and in cooperation with industrial partners. The projects include analysis of post-stroke brainwaves, decoding mind-states on healthy individuals using bayesian modelling, and combining physiological signals and genetics in insomnia patients to investigate correlations and categorizing subtypes. I have worked on using statistical machine learning techniques to predict treatment resistance in Schizophrenia patients from neuroimaging and cognition tests; a journal paper reporting our findings is in the making. I'm fairly new in the world of quantum physics but in the eyes of my PhD, my primary research is transitioning to the interface between computer science and quantum physics.
August this year 2019, I start a 3-year PhD at Section for Cognitive Systems at DTU Compute doing research on machine learning for quantum computers (quantum machine learning).
Aside from the academic work, I have a strong passion for innovation and entrepreneurship that integrates intelligent systems and high level user experience. As a side project, I work on a mobile application at this moment with a friend that could bring a new dimension to social games.