Amir Abbasi received his Ph.D. in engineering from Villanova University, specializing in hybrid reasoning for modeling, diagnostics, and prognostics of dynamic systems. His research focuses on the idea of hybrid systems based on a combination of physics and machine learning for dynamic systems modeling at the fundamental level, and diagnostics and prognostics at the applied level. Amir's expertise was honed during his tenure as a research scientist intern and visiting researcher at the Palo Alto Research Center (PARC). Recently, he has taken on the role of senior data scientist at Ford Motor Company, leveraging his skills to drive data-driven insights. Throughout his career, having authored over fifteen journal and conference papers and filed three patents. His work reflects a deep commitment to advancing the boundaries of knowledge in engineering and applying innovative solutions to real-world challenges.

Machine Learning, Dynamic Systems, Diagnostics, Prognostics, Hybrid Reasoning.