MSU's CCS Researcher, Luan, Equates NSF Funding into Environmental, Biological Systems Solutions
July 5, 2023
Vu Thai Luan
Photo by Megan Bean
A Mississippi State University faculty member in the Department of Mathematics and Statistics is confronting real-world problems with funding from two National Science Foundation grants, using math to address issues ranging from weather events to computational biology.
Assistant Professor Vu Thai Luan, a member of MSU's Center for Computational Sciences
, this summer earned his second NSF award—a three-year, $226,073 grant—for developing new mathematical methods to provide efficient solutions for complex systems while maintaining computational efficiency.
His current grant builds on a previous $130,749 NSF-funded project, awarded in 2020 to on develop effective numerical methods for solving differential equations that arise in multi-physical systems involving numerical analysts, meteorologists and computer scientists.
"A prominent example is in weather prediction and climate modeling, which require solving primitive equations to predict the behavior of the atmosphere, oceans, land surface and ice. These multi-physics problems pose significant computational challenges due to the presence of multiple time scales, where different processes occur at different rates. Inspired by this, I am developing advanced time integration methods that can provide fast and reliable solutions for large-scale simulations of complex systems," Luan said.
"Both of these NSF projects cover fascinating research topics in computational and applied mathematics, with applications that have real-life significance," he continued. "These interdisciplinary partnerships have revealed a common need for efficient algorithms to speed up their simulations."
Luan, an MSU faculty member since 2019, said in many science and engineering applications, there is a high demand for fast and accurate computational methods that can simulate complex multi-physical processes and their interactions occurring at a wide range of spatial and time scales or high frequencies.
"I hope our new methods can be applied to problems in numerical weather prediction, ocean modeling, visual computing, and molecular dynamics simulations. Indeed, we have published some interesting results in real-time simulation of elastodynamics systems," he said.
A native of Vietnam, Luan earned his 2014 Ph.D. from the University of Innsbruck, Austria. He received a bachelor's degree in 2005 from Hanoi National University of Education in Vietnam, followed by a master's degree from HUS—Vietnam National University in 2007. From 2008 to 2010, Luan worked at IOIT, Vietnam Academy of Science and Technology.
By Sarah Nicholas