Bio: Merten received his Bachelor of Science in Mechanical Engineering and his Master of Science in Theoretical Mechanical Engineering in 2016 from Hamburg University of Technology (TUHH) in 2013. In 2014 he joined the Nonlinear Dynamics Summer School hosted by Sandia Labs at University of New Mexico, Albuquerque (NM, USA), and for the Master Thesis Merten joined the VUTC at Imperial College London to work on fundamental research in experimental tribology, digital image correlation and nonlinear dynamics. In October 2020, Merten defended his PhD thesis entitled 'Data-Driven Techniques for the Nonlinear Dynamics of Mechanical Structures', freely available here. Merten was nominated as 'GAMM Junior' by the Gesellschaft für Angewandte Mathematik und Mechanik for the years 2021-2023. Starting in Jan. 2023, Merten Stender became Professor at the Chair of Cyber-Physical Systems in Mechanical Engineering at Technische Universität Berlin.
Research: Merten's research focuses on nonlinear vibrations in complex dynamical systems and machine learning techniques. He particularly interested in hybrid methods coupling classical physics-based simulations with data-driven methods. Physics-Informed Learning and Explainable Machine Learning techniques complement Merten's research interests.