Abstract: A wide range of natural and engineering systems exhibit extreme events, i.e., spontaneous intermittent behavior manifested through sporadic bursts in the time series of their observables. Examples include ocean rogue waves, intermittency in turbulence, extreme weather patterns and epileptic seizure. Because of their undesirable impact on the system or the surrounding environment, the real-time prediction and mitigation of extreme events is of great interest. In this talk, I will discuss three aspects of extreme events. First, I introduce a variational method that unveils the mechanisms underpinning the formation of extreme events. Next, I show how this framework enables the data-driven, real-time prediction of extreme events. I demonstrate the application of this method with several examples, including the prediction of ocean rogue waves and the intermittent energy dissipation bursts in turbulent fluid flows. Finally, I will discuss a closed-loop adaptive control and a delay feedback control for mitigating extreme events.

Bio: Dr. Farazmand is an Assistant Professor of Mathematics at NC State University. He received his PhD in Mathematics from ETH Zurich in 2014. Subsequently, he joined Georgia Tech for one year as J. Ford Postdoctoral Fellow before joining MIT as a postdoctoral associate. His interests span a wide range of problems in nonlinear dynamics, such as coherent structure extraction, reduced-order modeling and extreme event prediction. He develops rigorous data-driven methods to address these problems. For his contributions, Dr. Farazmand has received the Lloyd H. Donnell Applied Mechanics Reviews Paper Award from ASME and the FRDP award from NC State.