Aikaterini Giannoukou

Katerina studied Electrical and Computer Engineering with a focus on Software Engineering and Mathematics at the National Technical University of Athens, where she received her Master’s degree in 2017. The focus of her MSc thesis was the dynamic prediction of the glucose curve for Type I diabetes patients using a numerical simulation.

In the next four years, Katerina gained significant experience in the industry as a Software and Machine Learning Engineer at the UK-based Artificial Intelligence company Amplyfi, where she had the chance to work on various research projects using predictive models for Natural Language Processing and Understanding.

Katerina joined the Chair of Risk, Safety and Uncertainty Quantification in September 2021 as a PhD student to work on the European project GREYDIENT. Specifically, she will construct multi-fidelity models and will apply active learning approaches to optimally distribute the available computational/financial resources among different fidelity levels.