Dr. Ali Pourzangbar has a rich academic and professional background in machine learning and water sciences. He received his Bachelor's and Master's degrees in Civil Engineering (hydraulics) and a PhD with the prestigious "Doctor Europaeus" certification in coastal engineering. During his MSc, he studied the maximum scour depth at coastal structures due to waves using laboratory experiments and AI-based methods. During his PhD, he developed a numerical solver for the resolution of shallow water equations in FORTRAN to study the effects of the bottom boundary layer and suspended sediment transport on the evolution of natural sand bars. This numerical solver has been successfully applied to analyze the evolution of marine sandbars, specifically in real-life situations.
Dr. Pourzangbar's expertise extends to the development of AI-based models, contributing to various EU projects, including developing soft sensors for wastewater treatment (DIGITAL-WATER.city - Leading Urban Water Management to Its Digital Future) and regional climate change adaptation plans (ADRIACLIM). Currently, he is a Postdoctoral Research Associate at the Karlsruhe Institute of Technology (KIT), focusing on developing a machine learning-based toolbox to identify flood-prone regions and forecast morphological changes under various scenarios.
Recently, Dr. Pourzangbar was awarded the MSCA-PF grant for his project FAST, focusing on innovative modeling methods for flash floods, debris, and human behavior to ensure safe evacuation, hosted by the University of Nottingham.
Germany