معرفی
Dr. Alex Skillen is a Lecturer in Engineering Simulation and Data Science at the Department of Mechanical and Aerospace Engineering, University of Manchester. His research focuses on the intersection of Computational Fluid Dynamics (CFD) and machine learning, with applications in magnetohydrodynamics, environmental flows, and subcooled boiling phenomena. He actively contributes to interdisciplinary projects such as the Fluids Research Group and Physics-informed Deep Learning for Fusion Thermal Hydraulics.
Education: PhD in Mechanical Engineering from the University of Manchester (2012), investigating overset grid methods for Navier-Stokes equations.
Research Interests: CFD algorithm development, turbulence modeling, machine learning integration in flow simulations, and numerical analysis of multiphase phenomena. His work aligns with UN Sustainable Development Goals related to affordable and clean energy, and industry innovation.
Collaborations include international projects on thermal hydraulics in nuclear systems and turbulence super-resolution using generative models. He has contributed datasets for turbulence research and developed open-source tools for fluid-structure interaction simulations.
Advising: Supervised one PhD thesis titled 'The overset grid method applied to the solution of the incompressible Navier-Stokes equations in two and three spatial dimensions.' Active in mentoring within the Fluids Research Group.
Labs/Teams: Core member of the Fluids Research Group and collaborator on the Exascale Partitioned Fluid-Structure Interaction (ParaSiF_CF) framework development.
