My research has spanned a broad spectrum of materials systems across multiple engineering applications. 

My research began during my master’s degree with fatigue testing of composite materials, where I developed a strong foundation in material behavior and failure analysis. During my PhD, I further investigated the effects of blast loading on steel alloys, exploring the relationship between mechanical properties and microstructural evolution. 

During my research, I employ Acoustic Emission (AE) techniques as a non-destructive monitoring tool to investigate fatigue damage in  materials. AE enabled real-time detection of crack initiation and propagation, as well as the identification of different damage mechanisms.

I utilize Scanning Electron Microscopy (SEM) and Electron Backscatter Diffraction (EBSD) for advanced materials characterization, enabling detailed analysis of microstructural features such as grain morphology, phase distribution, and crystallographic orientation. These techniques support the investigation of deformation mechanisms, phase transformations, and failure behavior at the microscale. 

I apply machine learning and deep learning models to predict material behavior and failure mechanisms based on experimental and microstructural data.