
 
UPCOMING: WORKSHOP ON COMMON TASK FRAMEWORKS FOR SCIENCE AND ENGINEERING
(Virtual) February 14-15, 2023 [ VIEW ]
 
UPCOMING: WORKSHOP ON MACHINE LEARNING FOR SCIENCE AND ENGINEERING
Seattle, WA (Hybrid) June 26-28, 2023
 
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 thrusts: fundamentals, applications, and education.
WELCOME REMARKS: [ View ]
WELCOME REMARKS: [ View ]

RECENT NEWS AND NOTES
 

AWARD: Li Na (Harvard)
Congratulations to Li Na, winner of the Manfred Thomas Medal for outstanding contributions a young researcher and/or engineer under the age of 40 to the field of systems and control. [VIEW ]
 

PRESS: COLUMBIA ENGINEERING ROBOTICISTS DISCOVER ALTERNATIVE PHYSICS [VIEW ]
July 25, 2022 — Columbia University press article sponsored by the College of Engineering featuring the AI for physics modeling by Lipson.
 

PRESS: A ROBOT LEARNS TO IMAGINE ITSELF [VIEW ]
July 13, 2022 — Columbia University press article sponsored by the College of Engineering featuring the AI for physics modeling by Lipson.
 

PRESS: AI FOR ENGINEEING [VIEW ]
June 13, 2022 — University of Washington press article sponsored by the College of Engineering featuring the work AI Institute and the leadership of Brunton, Kutz and Manohar.
 
 
 
OUR INTEGRATION OF DATA, METHODS, EDUCATION AND APPLICATIONS
 

 
Funded by the National Science Foundation
 

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