Machine Learning for the Dynamical Systems Approach to Turbulence

Learn about machine learning applications in dynamical systems and turbulence through a seminar talk delivered by Dr Jacob Page from the University of Edinburgh at the INI Seminar Room 2. Explore the mathematical and statistical foundations of data-driven engineering, focusing on how machine learning techniques can be applied to understand and analyze turbulent flows from a dynamical systems perspective. Gain insights into cutting-edge research that bridges the gap between traditional fluid dynamics and modern computational approaches during this hour-long academic presentation, which is part of the broader discussion on data-driven engineering's future.