Nicole Aretz

Biography

After finishing her master's degree in mathematics at RWTH Aachen University, Nicole started as a doctoral fellow at the Aachen Institute for Advanced Studies in Computational Engineering Science (AICES) and joined the International Research Training Group "Modern Inverse Problems" (IRTG MIP) as soon as it opened. In her research project, she developed reduced basis techniques for the efficient approximation of variational data assimilation methods under flexible model configurations. As part of her training at IRTG MIP, Nicole was elected student representative, advised master students, and visited the Oden Institute as part of Prof. Tan Bui-Thanh's group for 6 months. After submitting her PhD thesis in September 2020, she is excited to return to the Oden Institute as a Research Fellow to work with Prof. Karen Willcox on operator inference and digital twins.

As part of the Willcox Research Group, Nicole combines different uncertainty quantification methods in a framework for digital twins. She is particularly interested in Bayesian inversion, multi-fidelity approximations, and optimal experimental design. With her background in reduced basis methods branching off to non-intrusive operator inference, Nicole closely follows the developments of model order reduction methods in general to better understand the needs of different applications and learn new analytical techniques. She is always interested to collaborate with other researchers and explore challenges and ideas across disciplines.