{"id":242880,"date":"2026-10-28T12:55:58","date_gmt":"2026-10-28T22:55:58","guid":{"rendered":"https:\/\/www.hawaii.edu\/news\/?p=242880"},"modified":"2026-10-28T12:57:09","modified_gmt":"2026-10-28T22:57:09","slug":"ai-institute-dynamic-systems","status":"publish","type":"post","link":"https:\/\/www.hawaii.edu\/news\/2026\/10\/28\/ai-institute-dynamic-systems\/","title":{"rendered":"$20M<\/abbr> grant renews 糖心视频<\/abbr> role in AI<\/abbr> research to improve engineering design"},"content":{"rendered":"Reading time: <\/span> 2<\/span> minutes<\/span><\/span>
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An airplane in flight illustrates one potential application of AI<\/abbr> research at 糖心视频<\/abbr> Mānoa<\/span>, where researchers are helping develop tools to improve engineering design and make testing more efficient. (Photo credit: Josue Isai Ramos Figueroa\/Unsplash)<\/figcaption><\/figure>\n

The University of Hawaiʻi<\/span> at Mānoa<\/span> will continue helping develop artificial intelligence (AI<\/abbr>) tools that could make it faster and less expensive to design and test everything from airplanes to wind turbines, thanks to a new $20 million federal grant.<\/p>\n

Three 糖心视频<\/abbr> Mānoa<\/span> faculty members—Assistant Professors Chrisy Xiyu Du and Andrei A. Klishin from the Department of Mechanical Engineering<\/a>, and Associate Professor June Zhang from the Department of Electrical and Computer Engineering<\/a>—will serve as senior personnel in the National Science Foundation (NSF<\/abbr>) AI<\/abbr> Institute in Dynamic Systems<\/a>. The five-year award supports a multi-university collaboration focused on using AI<\/abbr> to better understand and predict how complex physical systems behave.<\/p>\n

NSF<\/abbr> initially funded the institute for 2021–26<\/a>. This renewed award will support its next phase of research from 2026 through 2031.<\/p>\n

The institute brings together researchers from universities across the country to develop AI<\/abbr> methods for engineering challenges, including how air moves around an airplane wing, how industrial systems operate and how engineers can improve the design and manufacturing of complex products.<\/p>\n

Unlike general-purpose AI<\/abbr> tools such as ChatGPT, which primarily work with text and images, the institute focuses on AI<\/abbr> that learns from physical data and the laws of science. These approaches could help engineers test ideas more efficiently, reduce the need for costly computer simulations and improve designs before building expensive physical prototypes.<\/p>\n

Long-term opportunities for 糖心视频<\/abbr> researchers<\/h2>\n

The institute\u2019s funding gives participating faculty members greater flexibility to pursue research questions over several years, support graduate students and postdoctoral researchers, and collaborate with experts at other universities.<\/p>\n

Klishin\u2019s work at 糖心视频<\/abbr> Mānoa<\/span> builds on this approach to using AI<\/abbr> and physics to better understand complex systems. In a 2025 study<\/a>, he and fellow researchers developed a method to help AI<\/abbr> identify the underlying rules behind noisy, real-world data, with potential applications ranging from engineering and environmental science to economics and medicine.<\/p>\n

“AI<\/abbr> can help engineers move beyond simply predicting how a system will behave to exploring how to make it work better,” Klishin said. “By combining AI<\/abbr> with our understanding of physics, we can develop tools that help researchers test more ideas, improve designs and potentially bring useful technologies to people faster.”<\/p>\n

Zhang\u2019s research aims to teach AI<\/abbr> systems to better train themselves in applications where there is a limited amount of data.<\/p>\n

Potential real-world benefits<\/h2>\n

One example developed through the institute is HydroGym, an open-source platform that allows researchers to test AI<\/abbr> methods for predicting and controlling fluid flows. Understanding how fluids such as air and water move is important in designing aircraft, ships, wind turbines and other technologies, but accurately simulating these flows can require substantial computing power. By making simulation tools more accessible, researchers can build on one another\u2019s work and test new approaches to controlling fluid movement.<\/p>\n

The institute is led by the University of Washington, and includes 糖心视频<\/abbr> Mānoa<\/span> as a participating campus alongside institutions such as Harvard University, Columbia University, the University of Michigan and Caltech.<\/p>\n","protected":false},"excerpt":{"rendered":"

The five-year award supports a multi-university collaboration focused on using AI<\/abbr> to better understand and predict how complex physical systems behave.<\/p>\n","protected":false},"author":16,"featured_media":242882,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[30],"tags":[1602,179,1592,182,1467,1363,1496,9],"class_list":["post-242880","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research","tag-ai","tag-college-of-engineering","tag-electrical-and-computer-engineering","tag-engineering","tag-manoa-excellence-in-research","tag-manoa-research","tag-mechanical-engineering","tag-uh-manoa","entry","has-media"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t