My research focus is on computational electromagnetics and physics-informed data driven modeling in the subject areas of plasma engineering, physical electronics, materials science, and photonics.
Specifically, this relates to
- the numerical modeling of the dynamics and the electromagnetic response of tunable periodic (plasma) band gap structures and RF devices, and
- the multi-scale / multi-physics model coupling of the plasma-surface interface.
These topics are addressed using conventional numerical methods (e.g., Finite Difference, Finite Element, and Finite Volume techniques) as well as data-driven methods such as surrogate models and artificial neural networks. The latter involves machine learning algorithms to realize the bridging, for instance, of the atomistic surface dynamics scale and the macroscopic scale of the gas-phase in plasma modeling.