Dr. Soleimani’s main research interest lies in the multi-hazard resilience assessment of structures and critical infrastructure systems to empower risk-informed mitigation strategies. In particular, her research focuses on developing physics-guided machine-learning-based frameworks to tackle challenges towards a natural hazard resilient society, with specific interests in seismic analysis of structures and probabilistic modeling.
She develops computationally effective tools to enhance understanding of the seismic performance of structural systems by establishing predictive models and conducting sensitivity analysis. The outcome of her research in this domain enhances the vulnerability assessment of structures, promotes advanced resilience quantification techniques, and provides a means to achieve an effective post-disaster recovery framework. She also has multi-disciplinary research collaborations in the intersections of data science and STEM education to enhance educational practices and improve diversity.
Dr. Soleimani’s teaching interests include courses related to the fundamental fields of structural engineering such as statics, dynamics, and structural analysis, as well as essential applied mathematics and statistics courses. She is also interested to teach classes that benefit from her multidisciplinary research experience including structural dynamics, earthquake engineering, finite element methods, matrix analysis, bridge engineering, and application of reliability theory and risk assessment in civil engineering.