Caroline HaddadAssociate Professor ofMathematics |
South 330D 1 College Circle Geneseo, NY 14454 585-245-5475 haddad@geneseo.edu |
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Caroline Haddad has been a member of the Geneseo faculty since 1995.
COURSES TAUGHT AT SUNY GENESEO
SERVICE COURSES and LOWER LEVEL MAJORS COURSES
UPPER LEVEL MAJORS COURSES MATH 326 Differential Equations MATH 332 Linear Programming and Operations Research MATH 333 Linear Algebra MATH 345 Numerical Analysis MATH 371 Complex Analysis MATH 382 Intro to Wavelets and Their Applications
GRADUATE COURSES MATH 421 Foundations of Calculus MATH 433 Applied Matrix Techniques MATH 475 Applied and Computational Mathematics
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Faculty Information
Education
- Ph.D., Mathematics, Rensselaer Polytechnic Instititute
- M.S., Applied Mathematics, Rensselaer Polytechnic Instititute
- B.S., Mathematical Physics, Binghamton University
Employment
- I previously taught at Middlebury College on a Two-year Visiting Position. I have been employed at SUNY Geneseo since then.
Publications
- Haddad, C., Cholesky Factorization, Encyclopedia of Optimization, 2nd edition, Kluwer Academic Press, 2008
- Haddad, C.N., Habetler, G.J. , Projective Algorithms for Solving Complementarity Problems, Int'l. J. Math. & Math. Sci., Vol 29, 2, 99-113, 2002.
Affiliations
- Member of MAA
- Member of SIAM
- Honorary Member of Golden Key National Honor Society
- Member of ILAS
- Member of Opt-Net
My Classes
Math 222:
Calculus II
- Derivatives and antiderivatives of the transcendental functions, methods of integration, applications of definite integrals, sequences, improper integrals, and series. Prerequisites: MATH 221. Offered every semester
Math 332:
Linear Programming &Oper Resch
- The course introduces the student to the techniques for the formulation and solution of linear programming problems and their corresponding dual problems. It is intended to be a broad overview of deterministric linear programming and operations research. Topics to be covered include the Simplex Method, the Dual Simplex Method, Sensitivity Analysis, Network Optimization Methods, (Deterministic) Dynamic Programming, Game Theory and Branch and Bound Methods for Integer Programming. Additional topics may be selected from the Cutting Plane Methods for Integer Programming, the Transportation Problem, the Assignment Problem, Graphs and Networks, the Network Simplex Method, the Ellipsoid Algorithm and the Critical Path Method when time permits. Prerequisites: MATH 222, MATH 233,one of MATH 237 or MATH 239, one of CSCI 119 or CSCI 120 or permission of instructor. Offered spring, even years
Math 433:
Applied Matrix Techniques
- Many models can be formulated as a system of linear equations. The main emphasis of this course is to investigate a number of models that can be solved using matrix techniques and linear algebra. Applications may include, but are not limited to, Least Squares Fitting of Data, Markov Chains, and Population Growth Models. Prerequisites: A course in Elementary Linear Algebra.