Magnus Andersson

Magnus Andersson is an Associate Professor in the Department of Management and Engineering at Linköping University, Faculty of Science and Engineering. His research is centered in the division of Applied Thermodynamics and Fluid Mechanics (MVS), where he contributes to advanced modeling and simulation in fluid systems.

His research interests span Fluid Mechanics, Applied Thermodynamics, Computational Fluid Dynamics, and the innovative integration of machine learning through Physics-Informed Neural Networks. He focuses on surrogate modeling and design optimization, particularly in applications involving drag reduction and cavitation in hydraulic systems.

The recent publications indicate a strong trend toward hybrid computational methods combining physics-based models with data-driven techniques. His work bridges traditional engineering mechanics with modern AI applications, especially in optimizing fluid flow systems and improving predictive accuracy in complex multiphase environments.

• No scientific awards were mentioned in the provided texts.

Magnus Andersson has served as an editor for the Reports in Applied Mechanics series, indicating leadership in scholarly communication. While specific grants or student advising roles are not listed, his publication and editorial activity suggest active involvement in research supervision and project leadership.

He is affiliated with the Applied Thermodynamics and Fluid Mechanics (MVS) research group within the Department of Management and Engineering, which conducts cutting-edge research in thermal and fluid engineering systems.