Seyedshahabaddin MirjaliliView profile
Assistant Professor
Seyedshahabaddin Mirjalili is an Assistant Professor in Fluid Mechanics at the Department of Engineering Mechanics, KTH Royal Institute of Technology, Sweden. He is affiliated with the Swedish e-Science Research Center (SeRC) and Digital Futures at KTH. Education: BS in Mechanical Engineering from Sharif University of Technology, MS and PhD in Mechanical Engineering from Stanford University. Former Positions: Research Associate (2022–2024) and Postdoctoral Fellow (2019–2022) at Stanford University. His research spans fluid mechanics, scientific computing, and machine learning, focusing on computational methods for multi-physics, multi-phase, and multi-scale flows. Applications include propulsion systems, additive manufacturing, biophysical systems, and environmental flows. He develops conservative phase field models, energy-preserving numerical schemes, and physics-informed machine learning frameworks for high-fidelity simulations and reduced-order modeling. Recent work involves inverse asymptotic treatments for discontinuities, microbubble dynamics in breaking waves, and energy-conserving momentum transport in two-phase flows. His methods emphasize boundedness, conservation properties, and reduced spurious currents in numerical simulations. Scientific Awards: Gallery of Fluid Motion Award (2018) from the American Physical Society Division of Fluid Dynamics He contributes to software initiatives under SeRC and collaborates on high-performance computing (HPC) applications. His teaching includes courses like Particle Dynamics (SG1115).











