Scientist
Hamidreza Eivazi is a postdoctoral researcher in the Division Data-Driven Modeling of Mechanical Systems at the Institute of Applied Mechanics, Technische Universität Braunschweig, where he joined in January 2026. He received his PhD in Scientific Machine Learning and Multiscale Simulation from Technische Universität Clausthal in August 2025, with the grade summa cum laude, under the supervision of Prof. Andreas Rausch, and was previously a visiting researcher at KTH Royal Institute of Technology in Stockholm under the supervision of Prof. Ricardo Vinuesa.
His research focuses on AI for Science and scientific machine learning for computational mechanics, particularly physics-informed neural networks and operators, reduced-order modeling, and surrogate modeling for multiscale systems. During his doctoral work, including his contributions to CircularLiB at Technische Universität Braunschweig, he developed explainable and generative methods for lithium-ion battery degradation prediction; his broader interests include machine learning for turbulence and sustainability-related applications such as weather prediction, flood forecasting, and climate-related modeling.