The research teams in the OPTISIM

Prof. Xiaoying Zhuang’s key research area is machine learning and computational mechanics for the modelling and design of novel photonic systems, metamaterials and nanostructures. She has developed numerous innovative and robust numerical methods including level-set methods, partition-of-unity methods (such as mesh-free methods, XFEM formulations, phantom node methods and finite cover methods), multiscale methods, phase field models and error-driven adaptive methods developed and implemented. She also has experience with coupled (hydro-mechanical, thermo-mechanical, thermo-hydro-mechanical and electro-mechanical) problems, uncertainty analyzes/uncertainty quantification as well as inverse methods and optimization processes. She has applied innovative numerical methods to solve complex problems in engineering, solid state physics, and materials science. The research focus of Sofja Kovalevskaja Project funded by the Humboldt Foundation is the modeling, optimization and development of polymer composite materials. Her ongoing ERC Starting Grant is focused on the optimization and development of piezoelectric and flexoelectric nano-energy converters.

The group's research activities is concerned with theoretical investigation of complex dynamics appearing in nonlinear systems in different fields. These fields include modern nonlinear optics, quantum optics, material science and condensed matter physics, but also fluid dynamics and related fields. The investigations comprise theoretical analyses of the fundamental effects, modelling, as well as developing and applying adequate numerical methods. A wide range of methods varying from spectral and statistical methods to finite difference time domain schemes are developed and applied. Our activities can be divided into three main categories: method development, nonlinear wave interaction and soliton physics, and nonlinear condensed matter photonics.