U of A researchers creating AI infrastructure with NSF award
The MESA artificial intelligence platform quickly compiles relevant data for any research topic, freeing up hundreds of hours spent collecting documents.
The National Science Foundation awarded $4.6 million to researchers from the University of Arizona and University of New Mexico developing a data storage platform that leverages artificial intelligence. The project aims to avoid wasting time combing through massive amounts of data by using an AI agent to scour metadata for published research on virtually any topic and deliver results in minutes.
UNM’s Tyson Swetnam, associate professor of computer science, heads the project, called Multidisciplinary Environment for Scientific Advancement, or MESA. U of A collaborators include David Ebert, chief AI and data science officer; Barney Maccabe, professor and associate dean of research in the College of Information Science; and Lei Cao, assistant professor of computer science.
“We’re helping define the national infrastructure for AI-enabled scientific research,” said Ebert, also Computer Science Engineering Endowed Innovation Chair and professor in the School of Electrical, Computing and Software Engineering.
MESA is part of the NSF’s $83 million national investment in integrated data systems and services, focused on supporting researchers to discover, access, share and analyze large volumes of scientific data.
U of A will receive $2.1 million over two years to develop MESA’s user interface and a cloud-based storage apparatus that hosts datasets from NSF-funded national research labs. AI agents built into the platform search raw data, images and videos to find files most relevant to users’ requests.
“It will help researchers be more effective, make discoveries more efficiently and optimize their workflows,” said Ebert.