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.
Check out our YouTube channel at youtube.com/@mode-lab for videos on our latest research, seminar talks, lectures on math and science and more!
News
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Our latest JFM article is now online! We developed an equation-based framework for sensor/actuator placement aiming at open-loop flow control. Sep 25, 2023
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Erick Kracht joined the group as a PhD student—welcome! He will be working in the intersection between data-driven modeling and hydrodynamic stability. Aug 7, 2023
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Efrain passed his final exam to become a mechanical engineer—congratulations! Jun 2, 2023
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Diemen Delgado joined the group —welcome! He will be working on data-driven sparse model discovery of nonlinear dynamics on manifolds. Mar 27, 2023
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Nicolás Torres joined the group —welcome! He will be working on data-driven modeling of parametrized high-dimensional dynamical systems. Nov 25, 2022
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MODE-Lab was present at JMC 2022 in Valdivida! Matías, Javier, Efraín and Prof. Herrmann gave talks about data-driven modeling, dynamical systems and fluid mechanics. Oct 7, 2022
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Benjamin Reyes joined the group as an undergraduate research assistant—welcome! Aug 24, 2022
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B. Herrmann gave a talk on Dimensionality reduction for dynamical systems at CMM Pucón 2022. Aug 18, 2022
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Our minisymposium on methods for Data-driven modeling of unsteady fluid flows at the 19th USNCTAM was a big success! Jun 24, 2022
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B. Herrmann enjoyed a productive visit to the McKeon group at Caltech! May 21, 2022
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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