Siemens (Germany)

Supporting AI Readiness Through Digital Workflows in Materials Science

Materials science produces heterogeneous data across experiments, simulations, and industrial processes that often remain bound to local formats, manual procedures, and project‐specific software. Digital workflows address this fragmentation through explicit, repeatable, and machi...

Partial differential equations in the age of machine learning: a critical synthesis of classical, machine learning, and hybrid methods

Abstract Partial differential equations (PDEs) govern physical phenomena across the full range of scientific scales, yet their computational solution remains one of the defining challenges of modern science. This critical review examines two mature but epistemologically distinct...

Deep Learning–Based Distortion Correction for Brain Diffusion-weighted Imaging

BACKGROUND: Single-shot echo-planar imaging DWI (ss-EPI DWI) is susceptible to geometric distortions near air-tissue interfaces, limiting diagnostic accuracy. Multishot readout-segmented DWI (RESOLVE DWI) mitigates these artifacts but requires longer acquisition times. This study...

Numerical and Experimental Investigation of High-Pressure Stoichiometric Hydrogen-Oxygen Combustion In a Steam Atmosphere

Abstract The present work deals with the numerical and experimental investigation of a novel combustion system for the generation of superheated steam. This combustion system is based on the stoichiometric combustion of pure oxygen and hydrogen in an atmosphere of high-pressure,...