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Pepperdine | Seaver College
David M. Strong Faculty Profile

David M. Strong

Professor of Mathematics
Natural Science Division, Seaver College
RAC 116

Education

  • PhD in Applied Mathematics, University of California Los Angeles, 1997
  • MS in Applied Mathematics, University of California Los Angeles, 1994
  • BS in Mathematics, Brigham Young University, 1992, Summa Cum Laude Distinction

 

  • K. Anderson, A. Burt, W. Cousins, B. Hancock, D. Strong. "A Sinkhorn-Knopp Fixed Point Problem," Pi Mu Epsilon Journal, to appear.
  • D. Strong, J.-F. Aujol, T. Chan. "Scale recognition, regularization parameter selection, and Meyer's G norm in total variation regularization," Multiscale Modeling and Simulation, Vol. 5 (2006), pp. 273 -303.
  • D. Strong. "An Applet and On-line Tutorial for the Jacobi, Gauss-Seidel and SOR Methods," Journal of Online Mathematics and its Applications, Vol. 5 (2005).
  • D. Strong and T. Chan, "Edge-preserving and Scale-dependent Properties of Total Variation Regularization," Inverse Problems, Vol. 19 (2003), pp. 165 -187.
  • D. Strong, "Why it Might Seem That Christmas is Coming Early This Year," The College Mathematics Journal, Vol. 32 (2001), pp. 376 - 377.
  • Tooma Grant for Undergraduate Research, 2010
  • National Science Foundation CURM Grant for Undergraduate Research, 2008 - 2009
  • Pepperdine Research Fellow, Multiple years
  • Pepperdine Dean's Research Fund, Multiple years
  • MAA Project NExT Mentor for New Math Faculty, 2000-2001
  • UCLA Department of Mathematics Distinguished Teaching Award, 1999
  • GAANN Graduate Fellowship, 1992 - 1997
  • Valedictorian, BYU College of Physical and Mathematical Sciences, 1992
  • Society Member: SIAM (Society for Industrial and Applied Mathematics), MAA (Mathematical Association of America), AMS (American Mathematical Society)
  • National Committee Member: MAA Committee on Undergraduate Research

Topics

  • Creation and Effective Use of Mathematical Software
  • Image Processing
  • Undergraduate Research
  • Numerical Linear Algebra

Courses

  • Linear Algebra
  • Numerical Analysis
  • Differential Equations
  • Mathematics for Business Students