Degrees:
Ph.D., Purdue Univ.
M.S., Purdue Univ.
B.S., Peking Univ., Beijing, China
Dr. Lina Ma received a B.S at Beijing University, China, specializing in scientific and engineering computation. She continued her graduate study at Purdue University where she was advised by Professor Jie Shen. Her research topics focused on scientific computing and numerical analysis. She received her M.S degree in financial mathematics in 2013, followed by a Ph.D. in applied mathematics in 2014. She worked as a research associate at Penn State University from 2014 to 2017, where she expanded her research areas and worked on many interesting topics in applied math. Her research interests are developing faithful computational models and efficient algorithms for problems arising from many areas in applied sciences, including fluid dynamics, math-biology, electro-magnetic models, and stochastic models.
Dr. Ma is delighted to join the Trinity faculty and appreciates a liberal arts setting. She enjoys teaching mathematics and encourages students' involvement both inside and outside the classroom. She actively engages students in the learning process, and is eager to share her thoughts and experience. She also welcomes students' participation in research. She believes that the training process of understanding the problem, learning necessary skills, trying to solve the problem, and presenting ideas, is great preparation for future careers in all disciplines.
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Differential equations
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Numerical methods
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Financial mathematics
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Applied mathematics
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Scientific computing and numerical analysis
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Numerical PDE and modeling
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Coarse-grained models
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Spectral methods
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Electromagnetic and acoustic scattering
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Spherical harmonics analysis
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- Cheng, T., Ma, L., and Shen, J., 2020 An efficient numerical scheme for a 3Dspherical dynamo equation, Journal of Comp. & App Math, 370(2020).
- Ma, L., Li, X. and Liu, C., 2018 Coarse-graining Langevin dynamics using reduced-order techniques, Journal of Comp. Phys, 10.1016(2018).11.035.
- Ma, L., Li, X. and Liu.C., 2017 FDT-Consistent Approximation of the Langevin Dynamics Model, Comm. Math. Sci, 15(4), 1171-1181.
- Ma, L., Shen, J., Wang, L.L. and Yang, Z., 2017. Wavenumber explicit analysis for time-harmonic Maxwell equations in a spherical shell and spectral approximations. IMA Journal of Numerical Analysis, p.drx014.
- Ma, L., Chen, R., Yang, X. and Zhang, H., 2017. Numerical Approximations for Allen-Cahn Type Phase Field Model of Two-Phase Incompressible Fluids with Moving Contact Lines. Communications in Computational Physics, 21(3), pp.867-889.
- Ma, L., Li, X. and Liu, C., 2016. The derivation and approximation of coarse-grained dynamics from Langevin dynamics. The Journal of Chemical Physics, 145(20), p.204117.
- Ma, L., Li, X. and Liu, C., 2016. From generalized Langevin equations to Brownian dynamics and embedded Brownian dynamics. The Journal of Chemical Physics, 145(11), p.114102.
- Hu, L., Ma, L. and Shen, J., 2016. Efficient Spectral-Galerkin Method and Analysis for Elliptic PDEs with Non-local Boundary Conditions. Journal of Scientific Computing, 68(2), pp.417-437.
- Ma, L., Shen, J. and Wang, L.L., 2015. Spectral approximation of time-harmonic Maxwell equations in three-dimensional exterior domains. International Journal of Numerical Analysis & Modeling, 12(2).
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- NSF Computational Mathematics, DMS-1913229: Consistent Multi-Scale Treatments of Ion Transport in Biological Environments.
- Excellence in Teaching Award, Department of Mathematics, Purdue University, 2013
- Excellence Graduate Award, School of Mathematical Sciences, Peking University, 2007
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