

Welcome to our research group's website!
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.
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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New video abstract is available on Youtube! Sep 18, 2020
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Presented work on the synchronization dynamics of wake flows to the McKeon research group at Caltech. Mar 25, 2020