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Applied
mathematics involves applications of mathematical methods and techniques
to explore, and describe behavior of scientific, industrial, and engineering
phenomena. The applied mathematics program is interdisciplinary in
spirit. It is based on principles of mathematical continuous modeling,
computer simulation, linear programming, optimization, operations
research, bioinformatics, numerical methods, etc. The applied mathematics
program appeals to individuals who are interested in applying their
mathematical interests and skills to real-world problems.
Applicants
should have an undergraduate degree in Mathematics or its equivalent.
Candidates are expected to have approved undergraduate courses in
Multivariable calculus, Linear Algebra, Ordinary and Partial Differential
Equations, Numerical Analysis and Advanced Calculus. It is also
recommended to have some programming experience using a high level language
such as FORTRAN or C\C++, and/or a mathematical package such as Matlab
and Mathematica.
In addition
to the requirements of the Office of Graduate Studies, the Master of
Science degree in Applied Mathematics with Thesis, Option I, requires
1.
9 credits in core courses
·
MATE 6201,
Real Analysis
·
MATE 6672,
Numerical Mathematical Analysis
·
MATE 6677,
Partial Differential Equations
2.
9 credits from the following (area of
specialization)
·
MATE 5016,
Game Theory
·
MATE 5047, Intermediate
Differential Equations
·
MATE 5049,
Calculus of Variations
·
MATE 5055,
Vector Analysis
·
MATE 5056,
Tensor Analysis
·
MATE 5150,
Linear Algebra
·
MATE 6025,
Numerical Linear Algebra
·
MATE 6026,
Numerical Optimization
·
MATE 6035,
Topics in Operation Research I
·
MATE 6036,
Topics in Operations Research II
·
MATE 6045,
Optimization Theory
·
MATE 6262,
Real Variable II
·
MATE 6301,
Complex Variable
·
MATE 6530,
Differential Geometry
·
MATE 6622,
Topics in Complex Variable
·
MATE 6627,
Topics in Analysis I
·
MATE 6628,
Topics in Analysis II
·
MATE 6674,
Numerical Methods for Partial Differential Equations
·
MATE 6675,
Mathematics in Modern Science I
·
MATE 6676,
Mathematics in Modern Science II
·
MATE 6678,
Topics in Partial Differential Equations
3.
6 credits outside the area of specialization or
major. The requirement of a
minimum of two out-of-discipline courses is to ensure cross-disciplinary
breadth. The courses must be related to mathematics and should be chosen
in a coherent way. These should be of level 5000 or higher. It is
recommended that student chooses these courses with the help of their
advisor
·
6000 or
5000 level courses not listed in the area of specialization
·
6000 or
5000 level courses outside the Mathematics department
4.
2 credits in Seminar
·
MATE 6991,
Seminar (1 credit
)
·
MATE 6992,
Seminar (1 credit
)
5.
6 credits in Thesis
·
MATE 6999, ( 6 credits )
In addition, the candidate must
pass one qualifying exam from
·
Analysis
·
Numerical Analysis
·
Partial Differential
Equations
Option II: project option: the course and examination requirements
are similar to Option I, however the 6 Thesis credits must be replaced by
6 Project credits. An oral examination on the project is also required.
Option III, no project, no thesis: the student should approve a
minimum of 36 course credits:
·
A minimum
of 27 credits at graduate level
·
A minimum
of 21 credits in the area of specialization
·
A minimum
of 6 credits in courses related to, but outside the area of
specialization.
In addition the student must pass two (2) exams from
the above list.
List of faculty associated with this track and
their research interests
Robert Acar, (Numerical
Analysis, Partial Differential Equations, Inverse problems)
Julio Barety, (Fourier
Series, Abstract Harmonic Analysis)
Dennis Collins, (Mathematical
Physics of Quantum Theory, Differential Equations)
Omar Colón, (Discrete
Dynamic Systems, Discrete Mathematics, Combinatorics)
Daniel McGee, (Mathematical
Modeling, Applied Biostatistics)
Arturo Portnoy, (Analysis,
Differential Equations, Applied Mathematics)
Krzysztof Rozga, (Mathematical
Physics, Differential Geometry)
Robert Smith, (Statistics,
CAI, Stochastic Processes)
Lev Steinberg, (Mathematical
Modeling, Nonlinear Mechanics)
Alexander Urintsev, (Fluid
Dynamics, Stability, Symbolic Computation)
Pedro Vásquez, (Linear
and Nonlinear Programming, Scheduling, Neural Networks)
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