Zeynab Salehi

I am a Ph.D. candidate in Mechanical Engineering at the University of Alberta, specializing in developing advanced machine learning models for energy systems. My current research focuses on state-of-health estimation and remaining useful life prediction of solid oxide fuel cells (SOFCs), leveraging innovative techniques such as physics-informed temporal graph convolutional networks and attention-based probabilistic forecasting models. I conduct this research under the supervision of Dr. M. Shahbakhti and Dr. C. R. Koch in collaboration with Cummins Inc.

I hold MSc and BSc degrees in Mechatronics and Aerospace Engineering. During my master’s thesis, I worked on Dynamic Simulation of an Internal Combustion Engine and Vehicle Dynamics for Real-Time Usage in the Hardware-In-the-Loop Control System. Considering this diverse background, I am passionate about addressing real-world challenges at the intersection of machine learning, control and diagnostics systems, and sustainable energy technologies.