Computational
Math
Option
(CMO)
The
Computational
Mathematics
Option
(CMO),
has
been
offered
since
the
2001
Fall
Semester.
A student
who
meets
the
requirements
of the
CMO
will
receive,
in addition
to the
master
degree,
a certificate
signed
by the
Dean
of the
College.
Two
new
courses,
MATH
6377,
entitled
"Basic
Tools
for
the
Applied
Mathematician,"
and
MATH
6378,
"Basic
Scientific
Computing,"
have
been
approved
at the
University
level
and
are
offered
since
the
20022003
Academic
Year.
These
courses
provide
a rapid
and
intense
introduction
to advanced
mathematical
and
computational
topics
used
in applied
mathematics.
The
requirements
for
the
MSAM,
Computational
Mathematics
Option,
are
as follows.
 Successful
completion
(C
or
higher)
of
MATH
6370;6371:
Numerical
Analysis,
and
MATH
6377;6378:
Basic
Tools
for
the
Applied
Mathematician;
Basic
Scientific
Computing.
 Successful
completion
(C
or
higher)
of
at
least
6
credit
hours
of
courses
selected
from:
MATH
6366:
Optimization,
MATH
6372:
Numerical
Ordinary
Differential
Equations,
MATH
6374:
Numerical
Partial
Differential
Equations,
MATH
6376:
Numerical
Linear
Algebra,
MATH
7374:
Mathematical
Theory
of
Finite
Element
Methods,
MATH
7396:
Selected
Topics
in
Numerical
Analysis.
 Completion
of
6
more
elective
course
hours
from
disciplines
that
use
or
develop
scientific
computational
techniques.
These
hours
must
be
at
the
senior
level
or
higher
and
must
be
approved
by
the
Director
of
Graduate
Studies.
The
students
are
encouraged
to
choose
electives
from
departments
outside
of
Mathematics.
 Completion
of
a
tutorial
project
under
the
supervision
of
a
faculty
member,
MATH
6315;7315:
Master's
Tutorial.
For
more
detailed
information
on CMO,
please
contact
Dr.
Pan:
pan@math.uh.edu
Financial
Math
Option
(FMO)
The
Financial
Mathematics
Option
(FMO)
was
initiated
in 2002
Fall
Semester.
A student
who
meets
the
requirements
of the
FMO
will
receive,
in addition
to the
master
degree,
a certificate
signed
by the
Dean
of the
College.
To
be admitted
to the
program,
a student
must
have
completed
a bachelor's
degree
with
a 3.0
GPA
over
the
last
60 hours
of all
course
work
and
should
have
a good
background
in mathematics.
A student
need
not
have
majored
in mathematics
to be
admitted.
It is
expected,
however,
that
the
student
has
completed
at least
9 hours
of mathematics
at the
junior
or senior
level,
preferably
in courses
such
as advanced
linear
algebra,
advanced
calculus,
differential
equations,
or optimization.
When
these
requirements
are
not
met,
students
may
be admitted
to the
program
on a
conditional
basis
subject
to the
completion
of MATH
3334
(Advanced
Multivariate
Calculus),
MATH
4377
(Advanced
Linear
Algebra),
MATH
4331
(Introduction
to Real
Analysis),
with
a grade
of B
or higher
(these
9 hours
will
not
be counted
as a
part
of the
30hour
requirement).
In lieu
of the
above,
a student
may
take
MATH
6377
(Basic
Tools
for
Applied
Mathematician).
Again,
the
3 hours
will
not
be counted
as a
part
of the
30hour
requirement).
Applicants
with
graduate
degrees
in science,
mathematics,
economics,
or engineering
will
be admitted
by recommendation
of the
Committee
on FMO,
and
with
the
approval
of the
Director
of Graduate
Programs
in the
Department.
All
pertinent
regulations
set
forth
in the
Graduate
Studies
Bulletin
and
the
Bulletin
of the
College
of Natural
Sciences
and
mathematics
must
be observed.
The
requirements
for
the
M.S.
degree
in Applied
Mathematics,
Financial
Mathematics
Option,
are
as follows.

Completion
of
a
minimum
of
30
credit
hours
(with
a
3.0
GPA
overall
and
no
more
than
3
grades
at
or
below
C+).

Completion
of
the
following
courses
with
a
grade
of
C
or
higher:
MATH
6382,
6383:
Probability
and
Mathematical
Statistics
MATH
6366,
6367:
Optimization
(linear
programming,
nonlinear
programming,
stochastic
programming,
dynamic
programming
and
optimal
control,
some
experience
in
use
of
computer
software
for
numerical
optimization)

Completion
of
the
following
two
courses
in
the
core
of
finance
mathematics
MATH
63XX:
Mathematical
Finance
in
Discrete
Time
MATH
63XX:
Mathematical
Finance
in
Continuous
Time

Completion
of
two
more
courses
from
the
following
list:
MATH
6397:
Numerical
Method
for
PDE
*MATH
63XX:
Special
Topics
in
Mathematical
Finance
(The
subject
varies
from
semester
to
semester;
possible
topics:
Value
at
Risk,
RealOption
Valuations,
Valuation
of
Energy
Derivatives,
and
Energy
Risk
Management)
*MATH
73XX:
Time
Series
Analysis
*MATH
73XX:
Computational
Statistics
(Markov
Chains
Monte
Carlo,
and
Bayesian
Statistics)
*MATH
73XX:
Numerical
Methods
in
Finance
*MATH
73XX:
Econometrics
of
Financial
Markets
Other
MATH
courses
at
6000
level
or
higher
with
the
approval
of
the
FMO
Program
Director
FINA
7320:
Fixed
Income
Securities
FINA
8388:
Seminars
in
Financial
Management
I
ECON
7331:
Econometrics
I

Completion
of
a
Master's
Tutorial
Project
under
the
supervision
of
a
Mathematics
Department
faculty
member.
This
project
must
be
germane
to
financial
mathematics
and
could
be
done
as
a
summer
internship
in
collaboration
with
a
sponsoring
company.
The
student
is
required
to
complete
the
tutorial
courses
MATH
6315
and
7315
as
well
as
prepare
a
final
Project
Report.
The
report
must
be
approved
by
the
student's
tutorial
supervisor
and
be
submitted
to
the
Director
of
Graduate
Studies
for
the
purpose
of
departmental
review.
The
student
will
be
encouraged
to
rewrite
the
report
for
submission
to
a
professional
journal
for
possible
publication.
A
student
who
is
actively
engaged
in
risk
management
in
a
firm
is
encouraged
to
apply
the
experience
in
the
conduct
of
the
tutorial
project.
For
more
detailed
information
on FMO,
please
contact
Dr.
Kao:
edkao@math.uh.edu.
Computational
Science
Initiative
(CSIUH)
The
Computational
Sciences
Initiative
at the
University
of Houston
(CSIUH)
is an
interdisciplinary
graduate
certificate
program
aimed
at promoting
advanced
research
and
education
in the
Computational
Sciences,
including
numerical
algorithms,
high
performance
parallel
computing,
numerical
modelling
and
simulation
with
applications
in Sciences,
Engineering
and
other
disciplines
in which
computation
plays
an integral
role.
A
Computational
Sciences
Certificate
of Completion
at the
University
of Houston
is available
to graduate
degree
candidates
in one
of the
participating
departments
 Biochemistry,
Chemical
Engineering,
Computer
Science,
Electrical
Engineering,
Finance,
Geosciences,
Mathematics,
and
Physics
 and
who
have
selected
an independent
research
project
(thesis
or dissertation)
in which
there
is a
significant
computational
component.
Course
Requirements
Requirements
for award
of the
Masters
Certificate
of Completion
include
a total
of 9 hours
(with
grades
of B or
higher)
from the
approved
list of
CSIUH
electives
(including
at least
3 hours
from outside
their
home department)
and earns
a Masters
degree
from UH.
The Doctoral
Certificate
of Completion
is awarded
when a
student
completes
12 hours
(with
grades
of B or
higher)
from the
approved
list of
electives
(including
6 hours
from outside
their
home department)
and earns
a Doctoral
degree
from UH.
Students
must meet
all requirements
of their
home department.
At least
one member
from the
Associated
Faculty
Committee
must be
on a student's
research
committee.
Prerequisites
Students
entering
this program
should
have at
least
a Bachelor's
degree
in engineering,
computer
science,
mathematics,
statistics,
or a scientific
discipline.
Students
from other
disciplines
will also
be considered
on a case
by case
basis,
but the
following
prerequisites
are strongly
recommended
for those
students:

One
year
of
general
college
physics
or
chemistry.

One
year
of
differential/integral
calculus,
a
course
in
multivariable
calculus,
a
course
in
differential
equations,
and
a
course
in
linear
algebra.

A
course
in
computer
programming
(either
FORTRAN,
C,
or
C++)
or
equivalent
experience.
Resources
Numerous
computational
resources
are available
to CSIUH
participating
students
at University
of Houston.
Among
them are
a 64 nodes
IBMSP2
parallel
machine,
a NECSX3
vector
supercomputer
and advanced
powerful
workstations
including
SGI Origin
2000.
Admission
Interested
students
should
access
the program's
web page
or contact
the CSIUH
office
to obtain
detailed
information
about
academic
requirements
and financial
support.
CSIUH
students
must be
enrolled
in a department
from which
they receive
their
degree.
In conjunction
with the
requirements
of the
home department,
the program
consists
of a common
core curriculum
and a
minimum
number
of approved
CSIUH
elective
courses.
Students
entering
CSIUH
may come
from a
variety
of backgrounds.
Admission
is based
on undergraduate
GPA, letters
of recommendation,
and GRE
scores.
Several
research
and teaching
assistantships
are available
through
the CSIUH
and through
the participating
departments
and colleges.
Information
about
the program,
including
application
materials,
can be
obtained
over the
Internet
at http://www.math.uh.edu/csiuh.html
or by
writing
to: Computational
Science
Program,
University
of Houston,
Department
of Mathematics,
Houston,
TX 772043476.
Approved
CSIUH
Elective
Courses
 Biochemical
and
Biophysical
Sciences
 BCHS
6206:
Advanced
Computational
Methods
in
Biochemistry
 Chemistry
 CHEM
6321:
Quantum
Chemistry
 CHEM
6322:
Statistical
Thermodynamics
 CHEM
7321:
Quantum
Mechanics
in
Chemistry
 CHEM
7322:
Scattering
Theory
 CHEM
7323:
Statistical
Mechanics
in
Chemistry
 CHEM
7333:
Design
and
Analysis
of
Chemical
Experiments
 Computer
Science
 COSC
6302:
Introduction
to
Logic
and
Computing
Machines
 COSC
6303:
Introduction
to
Numerical
Analysis
 COSC
6304:
Introduction
to
Structured
Programming
and
Analysis
 COSC
6320:
Data
Structures
and
Algorithms
 COSC
6350:
Software
Engineering
 COSC
6363:
Concurrent
Programming
 COSC
6364:
Numerical
Analysis
 COSC
6365:
Vector
Processing
 COSC
6374:
Parallel
Computations
 COSC
6377:
Computer
Networks
 COSC
6384:
RealTime
Systems
 COSC
7364:
Advanced
Parallel
Computations
 COSC
7366:
Advanced
Mathematical
Software
 COSC
7374:
Computer
Vision
 Engineering
 ENGI
6324
&
6326:
Reservoir
Simulation
I
&
II
 ENGI
6370:
Systems
Engineering:
Introduction
to
Systems
Modeling
and
Analysis
 ENGI
6371:
Systems
Engineering:
Systems
Optimization
and
Computational
Methods
 Chemical
Engineering
 CHEE
6330:
Computational
Methods
for
Chemical
Engineers
 Electrical
and
Computer
Engineering
 ELEE
6313:
Neural
Networks
 ELEE
6320:
KnowledgeBased
Systems
in
Electrical
Engineering
 ELEE
6325:
StateSpace
Control
Systems
 ELEE
6350:
Numerical
Solution
Methods
in
Electromagnetics
 ELEE
6364:
Digital
Image
Processing
 ELEE
6373:
Advanced
Computer
Architecture
 ELEE
6374:
Parallel
Numerical
Computing
 Mechanical
Engineering
 MECE
6345:
Hydrodynamic
Stability
 MECE
6351
&
6352:
Finite
Element
Analysis
in
Engineering
Sciences
I
&
II
 MECE
6353:
Introduction
to
Computational
Fluid
Dynamics
 MECE
6379:
Computer
Methods
for
Mechanical
Design
 Geosciences
 GEOL
6362:
Computer
Modeling
in
Geology
 GEOL
6391:
Modeling
of
Seismic
Data
 GEOL
6392:
Migration
of
Seismic
Data
 GEOL
7320:
Seismic
Velocity
 GEOL
7322:
Seismic
Inversion:
Current
Concepts
 GEOL
7341:
Geophysical
Data
Processing
 Mathematics
 MATH
6326
&
6327:
Partial
Differential
Equations
 MATH
6366
&
6367:
Optimization
and
Variational
Methods
 MATH
6370
&
6371:
Numerical
Analysis
 MATH
6374:
Numerical
PDE
 MATH
6376:
Numerical
Linear
Algebra
 MATH
6378:
Parallel
Scientific
Computing
 MATH
6382
&
6383:
Probability
Models
and
Mathematical
Statistics
 MATH
7324
&
7325:
Bifurcation
Theory
 MATH
7396:
Domain
Decomposition
Methods
with
Applications
 MATH
7398:
Iterative
Methods
for
Large
Scale
Problems
 Physics
 PHYS
6309
&
6311:
Advanced
Mechanics
 PHYS
6315
&
6316:
Quantum
Mechanics
 PHYS
7310:
Hydrodynamics
 PHYS
7381:
Hydrodynamic
Instabilitie
