Journal of Fluid Mechanics Webinar Series: Petros Koumoutsakos, ETH-Zentrum

The Leeds Institute for Fluid Dynamics is delighted to partner with the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, the UK Fluids Network, and the Journal of Fluid Mechanics to deliver a regular webinar series on fluids-related topics.

The next seminar will take place at 4:00pm BST on Friday 5th June, 2020.

Speaker: Petros Koumoutsakos, ETH-Zentrum, Switzerland
Date/Time: Friday 5th June, 2020. 4:00pm BST/11am EDT

Title: Machine Learning for Fluid Mechanics

Abstract: Recent advances in machine learning and an ever increasing availability of data offer new perspectives (and hope) for solving long standing fluid mechanics problems. Despite early connections dating back to Kolmogorov, the link between Fluid Mechanics and Machine Learning (ML) has not been fully explored. The situation is rapidly changing with ML algorithms entering in numerous efforts for modeling, optimising, and controlling fluid flows. In this talk I will present works from our group on the interface of Fluid Mechanics and ML ranging from low order models for turbulent flows to deep reinforcement learning algorithms and Bayesian experimental design for collective swimming. I hope to demonstrate that ML has the potential to augment, and possibly even transform, current lines of fluid mechanics research.

The webinar will take place on Zoom. Register for this event and the whole series here.