Lin Mu

Dr. Lin Mu is an Associate Professor in the Department of Mathematics at the University of Georgia. She holds a Ph.D. in Mathematics from the University of Arkansas at Little Rock (2012), and M.S. and B.S. degrees from Xi'an Jiaotong University (2009 and 2006). Her research focuses on applied mathematics, numerical analysis, and scientific computing, with emphasis on numerical methods for PDEs, computational fusion plasma physics, porous media flow, and high-performance computing. She has secured major grants from the Department of Energy (DOE) and National Science Foundation (NSF), including leadership roles in RF-plasma-material interactions simulations and fluid solvers for porous media. Dr. Mu has published extensively (77+ papers, 2,273 Google citations) and received awards like the 2023 Fred C. Davison Early Career Scholar Award.

• Education:
  • Ph.D., Mathematics, University of Arkansas at Little Rock (2009–2012)
  • M.S., Mathematics, Xi'an Jiaotong University (2006–2009)
  • B.S., Mathematics, Xi'an Jiaotong University (2002–2006)
• Research Interests: Development of stable numerical schemes for PDEs, error analysis, computational fusion physics, high-dimensional simulations, and HPC applications.

Her work bridges theoretical mathematics and real-world engineering challenges, particularly in plasma physics simulations and porous media modeling. Current grants include DOE-funded projects on RF-plasma-material interactions (2023–2026) and NSF support for fluid solvers in complex geometries (2023–2026).

Awards:

• 2023 Fred C. Davison Early Career Scholar Award
• 2020 Ralph E. Powe Junior Faculty Enhancement Award

Teaching: Regular courses include MATH 4500/6500, MATH 2700, MATH 8500/8505, and MATH 8550. She actively mentors doctoral students in applied math and scientific computing.

Labs/Teams: Leads research in numerical methods and HPC at UGA, collaborating with institutions like Oak Ridge National Laboratory. Her work supports interdisciplinary fusion energy and environmental modeling initiatives.