Stefano Discetti

Stefano Discetti is a Full Professor in the Department of Aerospace Engineering at Universidad Carlos III de Madrid, leading the Aerospace Engineering Research Group. His work bridges experimental fluid dynamics, machine learning, and flow control.

• Key research themes include turbulence characterization, heat transfer enhancement, and advanced measurement techniques like PIV/PTV.
• He has developed data-driven methods for flow estimation, sensor placement optimization, and physics-informed neural networks.

Research Trends from his publications show a focus on:

• Machine learning for turbulent flow reconstruction (GANs, CNNs, KNN)
• Non-intrusive sensing from wall measurements
• Manifold learning and reduced-order modeling
• Heat transfer control via plasma actuators and passive structures
• Time-resolved diagnostics using hybrid experimental/numerical approaches

Projects include principal roles in EU and national grants like NEXTFLOW (2021-2026) and EXCALIBUR (2023-2026), with industry collaborations at Airbus and TU Delft.