We warmly welcome our new PhD student Mengjie Zhao!
Mengjie Zhao holds degrees in Computational Mechanics (MSc) with honors track and in Engineering Science (BSc) from the Technical University of Munich (TUM).
From the early years of her studies, Mengjie was fascinated by the modeling of multiphysics and multiscale systems. As a student research assistent at TUM and research intern at International Centre for Numerical Methods in Engineering (CIMNE), she gained a solid understanding of both the theoretical and algorithmic fundamentals as well as a wide range of applications. Through the BGCE project with the Elitenetzwerk Bayern (ENB), which dealt with the mesh sensitivity prediction with deep neural network, she realized that leveraging data could bring physical modeling far beyond the current computational limits. Later, in her master's thesis in coorperation with Siemens, she turned to the reduced-order modelling with enforced physical invariants, which showed better accuracy and generality.
In her PhD, she would like to step towards a further combination of deductive research (modelling and simulation) and inductive (data-driven) research by embedding physics into machine learning.
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