معرفی
Jan-Hendrik Bastek is a Researcher affiliated with the Department of Mechanics and Materials Research at ETH Zürich. His work focuses on computational mechanics, mechanical metamaterials, and the application of physics-informed machine learning in engineering challenges. Based in Zürich, Switzerland, he contributes to advancing material design through interdisciplinary approaches that integrate deep learning, inverse problem solving, and advanced modeling techniques.
His research interests span topics such as nonlinear mechanics, material property prediction, and the development of novel metamaterials with tailored properties. He has published extensively on physics-informed neural networks, data-driven simulation methods, and the optimization of truss-based metamaterials. His work bridges computational science and engineering applications, emphasizing practical solutions for complex structural and material systems.
Recent publications highlight trends in applying video denoising diffusion models for metamaterial design, GNN-assisted phase space integration, and viscoelastic behavior analysis of time-dependent materials. His contributions reflect a commitment to merging traditional mechanics with cutting-edge AI techniques to address forward and inverse problems in computational mechanics.
No scientific awards or grants are explicitly listed in the provided information. Bastek collaborates within the Mechanics and Materials Research group at ETH Zürich, contributing to both fundamental and applied research projects in the field.
