Quantifying the intelligence of computer systems, is of equal importance to quantifying its absence.
Throughout my career I have engaged my self with the design of intelligent systems, particularly systems that rely on statistical methods for providing the ability to forecast and make informed decisions. I entered the realm of machine learning prior to its modern renaissance (2012—), during my masters (M.Sc. in Software Engineering), and has since applied it to a variety of fields, such as: medical (Enversion), insurance (Ecsact, Tryg Insurance), logistics (Ecsact), and energy commodity trading (Norlys Energy Trading).
Along this journey, I obtained a PhD degree from Department of Electronic Systems, Aalborg University. This degree lead me to research and explore the field of adversarial machine learning, which developed my expertice in robustness and failure modes of modern machine learning techniques, e.g. deep learning.