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Welcome to our research group's website!

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Our group specializes in data-driven modeling of dynamical systems for mechanical engineering applications. In particular, our research lies at the exciting and fertile intersection between data-science methods, dynamics and control theory, and fluid mechanics applications.

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News​

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  • Paper just published in the Proceedings of the Royal Society A describes our new data-driven method—LANDO— that allows disambiguation between linear and nonlinear dynamics from measurements. Apr 13, 2022

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  • Our 2-part series of papers on gust mitigation control was published in PRF. Take a look at part I and part II. Jan 10, 2022

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  • We organized a seminar on data science for dynamical systems. Presentations are available here! Dec 22, 2021

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  • "Data-driven resolvent analysis" paper published in JFM! May 05, 2021

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  • Communications Physics paper, "Modeling synchronization in forced turbulent oscillator flows", is now online! Oct 30, 2020

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  • New preprint available online, where I show how to do resolvent analysis from data!  Oct 5, 2020

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  • B. Herrmann gave a talk at the Second Symposium on Machine Learning and Dynamical Systems of the Fields Institute. Sep 21, 2020

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  • Presented work on the synchronization dynamics of wake flows to the McKeon research group at Caltech. Mar 25, 2020

© Benjamin Herrmann