Regular biography
Saleh Rezaeiravesh is a Lecturer in Engineering Simulation and Data Science within the Department of Mechanical and Aerospace Engineering at The University of Manchester. His research interests include computational fluid dynamics, scale-resolving simulation of turbulent flows, and the development and application of uncertainty quantification and data-driven techniques to fluid mechanics problems. He earned his PhD in Scientific Computing (Numerical Analysis) from Uppsala University, Sweden, in 2018, and joined the FLOW Centre at KTH Royal Institute of Technology, Sweden, prior to his current position. Rezaeiravesh's work contributes to Sustainable Development Goals 4 and 9. He teaches courses in numerical methods, data-driven methods for engineers, and computer-aided engineering.
Scholar-generated biography
Saleh Rezaeiravesh is a researcher at The University of Manchester, UK, focusing on data-driven methods, large eddy simulation (LES), and uncertainty quantification (UQ). His work explores the application of Bayesian optimization, Gaussian process regression, and physics-informed neural networks to enhance computational fluid dynamics (CFD) simulations. He investigates the impact of grid resolution, numerical uncertainties, and wall modeling on turbulent flows, particularly in wall-bounded and high-speed reacting flows. His research also addresses the accuracy and robustness of CFD models through uncertainty quantification frameworks and statistical analysis tools. Rezaeiravesh develops open-source libraries and Python packages to support these efforts, emphasizing the integration of data-driven techniques with traditional simulation methods.