Gustav Hultgren

Gustav Hultgren is a Postdoctoral Researcher at the Royal Institute of Technology (KTH), affiliated with the Department of Materials and Structural Mechanics. His work focuses on fatigue analysis, fracture mechanics, and the application of machine learning in engineering mechanics. He teaches courses such as Advanced Design of Welded Structures (SD2420) and assists in Data-driven Methods in Engineering Mechanics (FSM3001 and SM2001). His research emphasizes probabilistic modeling of welded joints, material aging effects, and the integration of advanced manufacturing techniques like High-Frequency Mechanical Impact (HFMI).

Research Interests: Fatigue analysis of welded joints, fracture mechanics of materials, machine learning for stress identification, probabilistic modeling of structural components, and material durability under cyclic loading.

Publications highlight his contributions to understanding fatigue life prediction, weld geometry impacts, and the role of manufacturing defects in composite materials. His work bridges experimental measurements, numerical simulations, and data-driven approaches to improve structural reliability in engineering systems.