The U.S. National Science Foundation today 11 new artificial-intelligence research institutes, including one led by the 91探花. These institutes are part of a $220 million investment spanning seven research areas in AI. Each institute will receive about $20 million over five years.

The will focus on fundamental AI and machine learning theory, algorithms and applications for real-time learning and control of complex dynamic systems, which describe chaotic situations where conditions are constantly shifting and hard to predict.

“The engineering sciences are undergoing a revolution that is aided by machine learning and AI algorithms,” said institute director , a 91探花professor of applied mathematics. “This institute brings together a world-class team of engineers, scientists and mathematicians who aim to integrate fundamental developments in AI with applications in critical and emerging technological applications.”

Researchers know the basic physics principles behind dynamic systems, which include situations such as turbulence or how the body recovers from an injury. But these scenarios are often happening on multiple timescales at once and can be a combination of many types of physics, making it hard for researchers to understand exactly what’s going on.

“My favorite dynamic system is turbulence,” said institute associate director , a 91探花associate professor of mechanical engineering. “We literally live and breathe inside of a working fluid, and so do nearly all of our machines. But because of the multiscale complexity of the fluid, which involves a cascade of increasingly smaller eddies, we still have an incredibly hard time predicting what fluids will do outside of idealized and controlled settings.”

The overall goal of this institute is to integrate physics-based models with AI and machine learning approaches to develop data-enabled efficient and explainable solutions for challenges across science and engineering.

“Some of our specific questions include: Can we develop better machine-learning technologies by baking in and enforcing known physics, such as conservation laws, symmetries, etc.?” Brunton said. “Similarly, in complex systems where we only have partially known or unknown physics 鈥� such as neuroscience or epidemiology 鈥� can we use machine learning to learn the ‘physics’ of these systems?”

In addition to research, the institute will be focused on training future researchers in this field throughout the education pipeline. Some examples include: partnering with high school programs that focus on AI-related projects and creating a post-baccalaureate program that will actively recruit and support recent college graduates from underrepresented groups, United States veterans and first-generation college students with the goal of helping them attend graduate school.

“The institute will provide massive open-source educational materials that include lectures, data and code packages for advancing and empowering AI,” Kutz said. “Importantly, we will provide AI ethics training for all involved in the institute. We will also make this training available to the community at large, thus enforcing a disciplined approach to thinking about AI and its implications for our emerging societal concerns around data, data privacy and the ethical application of AI algorithms.”

For this institute, the 91探花is partnering with several regional institutions 鈥� the University of Hawaii at M膩noa, Montana State University, the University of Nevada Reno, Boise State University, the University of Alaska Anchorage and Portland State University 鈥� as well as with Harvard University and Columbia University.

“We are so excited to bring together a critical mass of amazing and innovative researchers from across the U.S. to really move the needle in developing machine learning technology for physical and engineering dynamic systems,” Brunton said. “We also have a deep connection with industry partners, such as Boeing, which provides us with an incredible opportunity to make sure that we are focused on important and relevant problems and that our technology will actually be used.”

Additional 91探花researchers who are part of this institute are lead researcher , assistant professor of mechanical engineering; , professor of electrical and computer engineering; , professor of biostatistics; and , a research associate professor of chemical engineering.

“I’m glad to see this substantial investment going to one of our state’s premier research institutions,” said U.S. Sen. Patty Murray, D-Wash. “As the 91探花 and other research institutions in our state continue to lead on artificial intelligence, this investment will be critical to ensuring that the state of Washington remains a leader in innovation, research and scientific achievement. I’ll keep fighting for important federal investments like this one to move this work forward.”

The 91探花is also , the AI EDGE Institute, which is led by Ohio State University. The goal of this institute is to design future generations of wireless edge networks that are highly efficient, reliable, robust and secure.

These 11 new AI institutes are building on the first round of seven AI institutes funded in 2020, and expand the reach of these institutes to include a total of 40 states and Washington D.C.聽In addition to the UW-led institute, the state of Washington will also house the , led by Washington State University. The institute鈥檚 goal is to use AI to tackle some of agriculture鈥檚 biggest challenges related to labor, water, weather and climate change.

“The state of Washington is already a leader in artificial intelligence,鈥� said U.S. Sen. Maria Cantwell, D-Wash. “From the 91探花’s Tech Policy Lab that studies the grand challenges around artificial intelligence to Washington State University’s work in precision agriculture, we are more than ready for these two grants to help us understand more artificial intelligence applications.聽The 91探花will work in the area of complex systems to improve fields like manufacturing, and WSU will work on improvements in farming.”

The AI Institute for Dynamic Systems is partially funded by the U.S. Department of Homeland Security.

For more information, contact Kutz at kutz@uw.edu and Brunton at sbrunton@uw.edu.

, an associate professor of mechanical engineering and a data science fellow with the eScience Institute, was nominated by the Army Research Office in the Army Research Laboratory.

Brunton is a mechanical engineer whose research focuses on data-driven modeling and control of complex systems, such as studying how turbulent fluids behave. Brunton was nominated for his work on using machine learning to develop efficient models that accurately describe the complexities of fluid mechanics. These models will then be used in part for designing better aircraft and more efficient energy systems.

, an assistant professor of physics and faculty member with the Clean Energy Institute, was nominated by the Air Force Office of Scientific Research.

Chu was nominated for his research on high-temperature superconductivity and materials with unique properties emerging from the laws of quantum mechanics, the probability-based rules that govern the behavior of matter at the subatomic level. These materials could revolutionize telecommunications and other fields. Chu uses strain tuning, a method he developed, to deform the 3D crystalline structure of materials and probe them for exotic combinations of quantum-level properties for applications in the laboratory, industry and beyond.

, an assistant professor of epidemiology and faculty member at the Fred Hutchinson Cancer Research Center, was nominated by the U.S. Department of Health & Human Services.

Lindstr枚m is a genetic epidemiologist with an interest in understanding how genetics contributes to common complex diseases, such as cancer. She was nominated for her work investigating the shared genetic origin of different types of cancer, using genetic data on more than 500,000 individuals. Her research will inform future study designs and help identify global biological mechanisms that underlie cancer development and progression.

, an assistant professor of chemical engineering and faculty member with the Center on Human Development & Disability and the Molecular & Engineering Sciences Institute, was nominated by the U.S. Department of Health & Human Services.

Nance’s research focuses on developing nanotechnology-based therapeutics to treat diseases and injuries to the brain. Using a combination of tissue imaging techniques, nanotechnology approaches and data science tools, she models the conditions present in different brain microenvironments 鈥� information needed to streamline the development of more effective and more precise nanoscale therapeutics to repair and protect the core of our central nervous system.

, an associate professor of environmental and forest sciences, was nominated by the National Science Foundation.

Prugh is a wildlife ecologist whose research explores interactions among species and the response of wildlife communities to global change. Prugh was nominated for her work that looks at the effects large carnivores have on smaller carnivores, particularly as animal distributions change rapidly worldwide. As part of this project, Prugh is the impacts gray wolves have on coyotes and bobcats as wolves naturally recolonize Washington state.

, currently an assistant professor of computer science and engineering, also received a PECASE. Cheung, who was nominated by the U.S. Department of Energy, will join the faculty at the University of California, Berkeley later this summer.

In addition, , a chief engineer at the , received a PECASE. Schneider, who is also a 91探花affiliate associate professor of electrical and computer engineering, was nominated by the U.S. Department of Energy.

The PECASE was established in 1996 to recognize the contributions that scientists and engineers have made to STEM fields, as well as education, leadership and public outreach. Participating federal departments and agencies nominate scientists for consideration. Final awards are coordinated by the Office of Science and Technology Policy within the Executive Office of the President.

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