
 
UPCOMING: WORKSHOP ON MACHINE LEARNING FOR SCIENCE AND ENGINEERING
 
ABOUT US
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.
 
MISSION
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.
 
RECENT NEWS AND NOTES
 

May 16, 2023 — New lecture series on the Ethics of Artificial Intelligence posted under Educational Resources [ VIEW ]
 

May 10, 2023 — The research team of PI Aditya Nair and collaborator Floris van Breugel received the Department of Defense DEPSCoR award for their project on Cluster‐based Estimation and Control of Turbulent Aeroelastic Flows. Both Nair and van Breugel are faculty at partner institute University of Nevada, Reno. [ VIEW ]
 

May 1, 2023 — Registration is now open for the Machine Learning for Science & Engineering workshop taking place June 27-28. This workshop brings together members of the AI Institute in Dynamic Systems with the goal of the continued development of teams whose focus is to develop the core mathematical architectures as well as domain applications. [ VIEW ]
 

March 24, 2023 — Journal article co-authored by Institute PI Scott McCalla featured in several news outlets. McCalla is faculty at partner institute Montana State University. Read the research article here. [ VIEW ]
 
MORE NEWS & NOTES [ VIEW ]
 
OUR INTEGRATION OF DATA, METHODS, EDUCATION AND APPLICATIONS
 

 
 
University of Washington
101 Wilson Annex
Box 352137
Seattle, WA 98195
101 Wilson Annex
Box 352137
Seattle, WA 98195
Funded by the National Science Foundation
