Left to right: Pritom Roy, Xuan Gu, Nailah Rawnaq, Irina Afanasyeva, James Burton, Ryan Holley
The eighth annual meeting of the SIAM Central States Section was held on Oct. 7-8 on the campus of the University of Nebraska-Lincoln. Since its foundation in 2014, the SIAM-CSS has served SIAM members in eight central U.S. states: Arkansas, Colorado, Iowa, Kansas, Mississippi, Missouri, Nebraska and Oklahoma.
Four doctoral students in mathematics and two master students in statistical and analytics received travel awards to attend and present their research at the SIAM-CSS annual meeting. The students Irina Afanasyeva, James Burton, Xuan Gu, Ryan Holley, Nailah Rawnaq and Pritom Roy of the Department of Mathematical Sciences are advised by Tulin Kaman, associate professor and the Lawrence Jesser Toll Jr. Endowed Chair in the Department of Mathematical Sciences.
Afanesyeva’s research focuses on the effects of turbulence inflow models on wind loads, which is a collaborative project with Panneer Selvam, University Professor in the Department of Civil Engineering at the U of A.
Burton’s research focuses on the development of massively parallel, block-structured adaptive mesh refinement front tracking method, which is a collaborative project with Ann Almgren, a senior scientist and department head of the Applied Mathematics Department in the Applied Mathematics and Computational Research Division at Lawrence Berkeley National Laboratory.
Gu’s research is on the development of physics-informed and computationally efficient machine learning algorithms for fluid flows, which is a joint work with Xiao Liu, associate professor at the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, and Kevin Jin, associate professor in the U of A Department of Computer Science and Computer Engineering. This project has been supported by Chancellor’s Fund for Innovation and Collaboration since 2021.
Holley’s research is on the development of numerical algorithms to describe the evolution of turbulent mixing at the interface of two fluids due to the hydrodynamic instabilities, which are of great interest in a variety of scientific and engineering problems, such as astrophysical and high-energy-density applications.
Rawnaq’s and Roy’s research focuses on the use of the convolutional neural network-based medical image segmentation and the improvements of the existing machine learning interpretable prediction models for cancer diagnostics.
Kaman’s Computational and Applied Mathematics (CAM) research group at the U of A involves the development of computational models and efficient, accurate numerical algorithms to predict the behavior of complex systems.
About SIAM: Society for Industrial and Applied Mathematics (SIAM) is an international community of over 14,000 individual members. Almost 500 academic, manufacturing, research and development, service and consulting organizations, government, and military organizations worldwide are institutional members. SIAM was incorporated in 1952 as a nonprofit organization to convey useful mathematical knowledge to other professionals who could implement mathematical theory for practical, industrial, or scientific use. Since then, SIAM’s goals have remained the same. SIAM fosters the development of applied mathematical and computational methodologies needed in various application areas. Applied mathematics, in partnership with computational science, is essential in solving many real-world problems. Through publications, research and community, the mission of SIAM is to build cooperation between mathematics and the worlds of science and technology.
