Alexander Henkes received the B.Sc. (Mechanical Engineering) and M.Sc. (Mechanical Engineering) degrees from the University of Paderborn, Germany, in 2015 and 2018, respectively. In 2022, he received his Ph.D. with honors from the Technical University of Braunschweig (TUBS), Germany, for his thesis ‘‘Artificial Neural Networks in Continuum Micromechanics’’.
In 2022, he was elected as a junior member of the German Association of Applied Mathematics and Mechanics (GAMM) for his outstanding research in the field of artificial intelligence in continuum micromechanics. In 2023, he won the ETH Zürich Postdoctoral Fellowship and joined the Computational Mechanics group at ETH as a postdoc.
His current research focuses on spiking neural networks (SNN). Recently, he published a preprint on nonlinear history-dependent regression using SNN. This enables SNN to be used in the context of applied mathematics and computational engineering.
He is a contributor of snnTorch.