Teaching

Students have the right to know the history of the topic we are teaching: the origin of the theory (where and why it begins), the future of the subject (where it will go) and more importantly, its impact to their life.

Before taking my courses, you would also like to know more about teaching style.

Here let me share my pros and cons in the course MATH1853 (A compulsory course of big class size for Engineering students)

  • Pros and cons 2012-13
  • Pros and cons 2013-14
  • Pros and cons 2014-15
  • Pros and cons 2016-17
  • Pros and cons 2017-18

    The followings are my pros and cons in four courses MATH3905, MATH3408, MATH4602 (small class size for Mathematics students) and a project type course MATH3999

  • Pros and cons 2013-14
  • Pros and cons 2013-14
  • Pros and cons 2014-15
  • Pros and cons 2017-18

    My teaching interests are mainly in mathematical modeling, queuing systems, matrix computations, stochastic process, numerical algorithms and simulation.

  • MATH 1001 FUNDAMENTAL CONCEPTS OF MATHEMATICS.

  • MATH 2408 COMPUTATIONAL METHODS AND DIFFERENTIAL EQUATIONS WITH APPLICATIONS.

  • MATH 2603 PROBABILITY THEORY.

  • MATH 2905 QUEUING THEORY AND SIMULATION.

  • MATH 3602 SCIENTIFIC COMPUTING.

  • MATH 2999 GUIDED STUDY.

  • MATH1853 LINEAR ALGEBRA, PROBABILITY AND STATISTICS.

  • MATH 3999 MATHEMATICS PROJECT.

    Books for Students

    The followings are suggested books for students if they want to do research or project with me.

    Linear Algebra and Its Applications

  • Introduction to linear algebra (2003) Gilbert Strang. Wellesly, MA : Wellesley-Cambridge Press. [Main Library 512.5 S89 i]
  • Linear algebra and its applications (2006) Gilbert Strang. Belmont, CA : Thomson, Brooks/Cole. [Main Library 512.5 S89]

    Iterative Methods

  • Iterative solution methods (1994) Owe Axelsson. Cambridge University Press, Cambridge [Main Library 511.42 A96]
  • Iterative methods for optimization (1999) C.T. Kelley. Philadelphia, Pa. : SIAM [Main Library 519.3 K29 i ]
  • Matrix iterative analysis (2000) Richard S. Varga. Berlin : Springer. [Main Library 511.7 V29 m]

    Matrix Theory and Computation

  • Matrix computations (1989) Gene H. Golub and Charles F. Van Loan. Johns Hopkins University Press. [Main Library 512.9434 G62]
  • Matrix analysis (1985) Roger A. Horn and Charles R. Johnson. Cambridge University Press. [Main Library 512.9434 H81]

    Computations with Markov Chain

  • Numerical methods for structured Markov chains (2005) D.A. Bini, G. Latouche, B. Meini. Oxford University Press. [Main Library 519.233 B6]
  • Matrix-geometric solutions in stochastic models : an algorithmic approach (1981) Marcel F. Neuts. Johns Hopkins University Press. [Main Library 519.233 N49]
  • Introduction to the numerical solution of Markov chains (1994) W.J. Stewart. N.J, Princeton University Press.

    Stochastic Manufacturing Systems

  • Stochastic models of manufacturing systems (1993) John A. Buzacott and J. George Shanthikumar. Englewood Cliffs, N.J. : Prentice Hall. [Main Library 658.5 B99]
  • Manufacturing systems engineering (1994) Stanley B. Gershwin. Englewood Cliffs, N.J. : PTR Prentice Hall. [Main Library 658.5 G38]

    Stochastic Models in Biology

  • An introduction to stochastic processes with applications to biology (2003) Linda J.S. Allen. Upper Saddle River, N.J. : Pearson/Prentice Hall. [Main Library 519.23 A427 i]
  • Genomic signal processing (2007) Ilya Shmulevich and Edward R. Dougherty. Princeton, N.J. : Princeton University Press. [Main Library 572.865 S55]

    Credit Risk Modeling

  • An Introduction to Credit Risk Modeling (2003) Christian Bluhm, Ludger Overbeck, Christoph Wagner, Chapman & Hall/CRC. [Main Library 658.880151 B65]
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