Machine Learning, Dynamical Systems and Control

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Our mission is to develop the next generation of advanced machine learning tools for controlling complex physical systems by discovering physically interpretable and physics-constrained data-driven models through optimal sensor selection and placement. Our work is anchored by a common task framework that evaluates the performance of machine learning algorithms, architectures, and optimization schemes for the diverse tasks required in engineering applications. We will push beyond the boundaries of modern techniques by closing the loop between data collection, control, and modeling, creating a unique and cross-disciplinary architecture for learning physically interpretable and physics constrained models of complex dynamic systems from time series data. The common task framework will further support sustainable and open-source challenge datasets, which will be foundational for developing interpretable, ethical, and inclusive tools to solve problems fundamental to human safety, society, and the environment.



Founded Oct. 1, 2021, as part of the National Science Foundation's effort to advance machine learning and AI across the sciences, the Institute is committed to integrating machine learning and artificial intelligence methods for a broad range of scientific and engineering applications. The $20 million investment integrates institutions from the Pacific Northwest (Washington, Montana State, Nevada, Hawaii, Portland State, Boise State and Alaska) with Harvard and Columbia Universities. Our aim is to not only develop fundamental ML/AI methods and algorithms, but also to broadly share these methods with the science and engineering communities by providing open-source code, data, and lectures on the broad and diverse range of topics we consider as an Institute. Thus, we have three key efforts: fundamentals, applications, and education.




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National AI Research Institutes Hill Day
September 5, 2023 — The Institute is participating in the National Artificial Intelligence Research Institutes Congressional Showcase on Capitol Hill. Learn more about the NSF AI Institutes in the AI Institutes Hill Day Booklet.


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Website Update
August 8, 2023 — As part of the Institute's efforts toward inclusion, we have updated our website with accessibility in mind using the Web Accessibility Evaluation Tool (WAVE).


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New Courses
June 21, 2023 — Check out the new lecture series on data-driven models for unsteady fluid flows and a miniseries on observability theory under Educational Resources


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Key Personnel Update
June 13, 2023 — The AI Institute in Dynamic Systems is excited to officially welcome Assistant Professor Chrisy Xiyu Du to the team at University of Hawai'i at Mānoa as well as Assistant Research Professor Bree Cummins and Assistant Professor John Smith to the team at Montana State University.




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University of Washington
101 Wilson Annex
Box 352137
Seattle, WA 98195


The AI Institute in Dynamic Systems is one of the National Artificial Intelligence Research Institutes funded by the National Science Foundation (NSF), Award Number 2112085.
Information on the AI institutes is available at

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