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James Lambers

Dr. James Lambers

Full Professor


My current research is on spectral methods for time-dependent variable-coefficient PDE; simulation of gas injection processes for enhanced oil recovery, in collaboration with Margot Gerritsen at Stanford; and denoising of images via nonlinear diffusion, in collaboration with Patrick Guidotti at UC Irvine.

  • PHD - Stanford University (2003)
  • MS - Stanford University (1994)
  • BS - Purdue University (1991)

Undergraduate Courses:
MAT 102 (Brief Applied Calculus)
MAT 280 (Calculus IV with Analytic Geometry)
MAT 285 (Introduction to Differential Equations I)
MAT 460/560 (Numerical Analysis I)
MAT 461/561 (Numerical Analysis II)

Graduate Courses:
MAT 610 (Numerical Linear Algebra)
MAT 721 (Mathematics For Scientific Computing II)
MAT 772 (Numerical Analysis for Computational Science)
MAT 773 (Signal Analysis for Computational Science)

  • Convergence analysis of Krylov subspace spectral methods for reaction-diffusion equations, J. Sci. Comput., 2019, 10.1007/s10915-018-0824-5
  • Modeling of first-order photobleaching kinetics using Krylov subspace spectral methods, Comput. Math. Appl., 2018, 10.1016/j.camwa.2017.10.019
  • Solution of nonlinear time-dependent PDEs through componentwise approximation of matrix functions, J. Comput. Phys., 2016, 10.1016/
  • Solution of time-dependent PDE through rapid estimation of block Gaussian quadrature nodes, Linear Algebra Appl., 2015, 10.1016/j.laa.2014.07.009
  • Image restoration with a new class of forward-backward-forward diffusion equations of Perona-Malik type with applications to satellite image enhancement, SIAM J. Imaging Sci., 2013, 10.1137/120882895
  • Effective Course Design
  • Society for Industrial and Applied Mathematics
  • American Mathematical Society

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Areas of Expertise

Numerical analysis