Video produced by UK Research Communications. To view captions for this video, push play and click on the CC icon in the bottom right-hand corner of the screen. If using a mobile device, click on the “thought bubble” in the same area LEXINGTON, Ky. (Feb. 4, 2026) — Today’s most powerfu l supercomputers can answer big scientific questions. However, managing large amounts of data presents a major obstacle. That challenge is the focus of the work by Xin Liang, Ph.D., assistant professor in the Department of Computer Science in the University of Kentucky Stanley and Karen Pigman College of Engineering. Liang recently received the prestigious National Science Foundation (NSF) Faculty Early Career Development (CAREER) Award with $500,000 over five years for his research. Liang helps scientists work more efficiently with massive datasets across fields such as climatology, cosmology and topography. “I work with actual scientific applications from a lot of disciplines,” Liang said. “There are many advanced supercomputers today and they are generating a large amount of the data.” Transferring files can take hours or days, slowing research and limiting how quickly scientists can learn from their results. Liang’s project explores “polymorphic data,” an approach that allows researchers to view and use different versions of the same data as their needs change. Instead of downloading the full, highly detailed dataset, scientists can start with a simpler version. “Polymorphic data means that we will have our data presented in different form from the perspective of researchers and the users,” Liang said. “Basically, if you want to use it for visualization to just specify a low accuracy, then we will provision the data at a lower accuracy with a much less data movement.” This method helps researchers move faster while still giving them access to high-quality data when it matters most. “This will in turn accelerate the entire procedure,” Liang said. “Meanwhile, if you would like more accurate data for publishing or deeper research, we also have the flexibility to deliver the data in much higher accuracy to meet your needs. This kind of dynamic or adaptive nature of processing data gives researchers the opportunity to finish their task in shorter time.” The NSF CAREER award supports both Liang’s research and his teaching, helping train future computer scientists to rethink how large scientific datasets are managed. “I’m really excited about this project and its practical use and the link with real applications,” said Liang. “This will really make a difference for society.” The CAREER Award is one of the “most prestigious awards in support of the early career-development activities of those teacher-scholars who most effectively integrate research and education within the context of the mission of their organization,” according to NSF. This material is based upon work supported by the National Science Foundation under Award Number 2442627. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The post NSF CAREER award supports faster, smarter use of massive scientific data appeared first on The Lexington Times. ...read more read less