Computational Sciences and Informatics (CSI)
School of Computational Sciences
600/SYST 500 Quantitative Foundations for
Computational Sciences (3:3:0). Not applicable to the
48-hour course total for the CSI Ph.D. Prerequisites: MATH
213 and 214. Accelerated review of mathematical tools for
scientific applications and analysis. Topics include
vectors and matrices; differential and difference equations;
linear systems; Fourier, Laplace, and Z-transforms and
probability theory.
601 Computational Science Tools I
(1:1:0). Not applicable to the 48-hour course total for the CSI Ph.D.
Prerequisites: A year of college calculus and a course in
computer programming. Introduction to basic tools in
computational science. Covers UNIX, editors, LaTeX, HTML, and
graphics. Emphasizes application and use rather than
theory. Substantial portion of instruction is delivered via a
distance-learning web interface.
602 Computational Science Tools II
(1:1:0). Not applicable to the 48-hour course total for the CSI Ph.D.
Prerequisites: CSI 601 and knowledge of matrix
algebra. Introduction to basic tools in computational science.
Covers MATLAB, MAPLE, and GNUPlot. Emphasizes
application and use rather than theory. Substantial portion of
instruction is delivered via a distance-learning web interface.
603 Introduction to Scientific Programming I
(1:1:0). Not applicable to the 48-hour course total for the CSI
Ph.D. Prerequisite: CSI 601 or permission of
instructor. Introduction to programming in C or Fortran. Emphasizes
application and languages rather than theory. Features
a combination of lecture and lab. Assignments are
completed via a distance-learning web interface.
604 Introduction to Scientific Programming II
(1:1:0). Not applicable to the 48-hour course total for the CSI
Ph.D. Prerequisites: CSI 601 and 603 or permission of
instructor. Introduction to programming in an
object-oriented language such as C++. Features a combination of
lecture and lab.
605 Software Construction Tools for Scientists
(1:1:0). Not applicable to the 48-hour course total for the CSI
Ph.D. Prerequisites: CSI 601, 603, 604 or programming
experience with C, C++, or Fortran and familiarity with the
UNIX operating system; or permission of
instructor. Introduction to the tools commonly used for software
construction and development. Covers revision control,
debuggers, profilers, Makefiles, and regular expressions. Designed
for students who wish to develop moderate to large
software systems and need an introduction to the basic tools used
in construction.
606 Scientific Graphics and Visualization Tools
(1:1:0). Not applicable to the 48-hour course total for the CSI
Ph.D. Prerequisite: CSI 601 or permission of
instructor. Introduction to the use of scientific visualization tools for
data analysis. Use of specific packages will be taught on a
rotating basis. Packages include PV-WAVE, S-Plus,
SV, XMGR, and the pnm tools.
607 Database Tools for Scientists
(1:1:0). Not applicable to the 48-hour course total for the CSI Ph.D.
Prerequisites: CSI 601 and 602 or permission of
instructor. Introduction to database tools. Teaches the student how to
deal
with the relation model, on which database packages
like Oracle are based. Under this language, database
design concepts, table operations, triggers, sequences, and
introduction to simple query language (SQL) will be covered.
610 Introduction to Computational Sciences
(3:3:0). Not applicable to the 48-hour course total for the CSI
Ph.D. Prerequisites: CSI 601, 602, 603, 604, 605, and 700
or permission of instructor. Covers advanced numerical
methods, computer architecture, and scientific software
development. Includes software design, construction,
and validation techniques commonly used in industry.
Also serves as an introduction to high-performance computing.
612 Physical Chemistry of Solids
(3:3:0). Prerequisites: MATH 113, 114, 213, PHYS 260 or 266, CHEM 331
and 332. An advanced course of physical chemistry for
first year graduate students with emphasis on solid-state
materials. It covers advanced chemical thermodynamics,
kinetics, diffusion, and solid-state reactions in different
classes of materials, including metals, ionic crystals, and
semiconductors. Computer applications to modeling
solid-state reactions are also included.
630 Bioinformatics I (3:3:0). Prerequisites: General
chemistry, general physics, organic chemistry, and
calculus. Intensive review of those aspects of organic chemistry
and biochemistry necessary to begin research in
bioinformatics and to enter graduate courses in biology. Covers
covalent bonding, quantum mechanical basis of bond
formation, three-dimensional structure of molecules, reaction
mechanisms, catalysis, polymers, enzymes, thermodynamic
and kinetic foundations, metabolic pathways, and sequence
and structure of macromolecules.
631 Bioinformatics II (3:3:0). Prerequisites:
Bioinformatics I, general chemistry, general physics, organic
chemistry, calculus, or permission of
instructor. Intensive review of those aspects of biochemistry, molecular biology,
and cell biology necessary to begin research in
bioinformatics and to enter graduate courses in biology. Covers cell
structure, intracellular sorting, cellular signaling (i.e.,
receptors), cytoskeleton, cell cycle, DNA replication, transcription,
and translation.
632 Bioinformatics III: Global Ecology IV
(3:3:0). Prerequisites: General chemistry, general physics,
introductory statistics, and calculus. Intensive review of
ecology necessary to begin research in bioinformatics and in
global change. Covers basic principles of physiological
ecology, population dynamics, dynamics of ecological
communities and ecosystems, biogeography, biological diversity,
and the dynamics of the biosphere, including the effects of
life on the atmosphere, oceans, and solid surfaces.
639 Ethics in Scientific Research
(3:3:0). An examination of ethical issues in scientific research. Begins with
a reflection on the purpose of scientific research and
review of the foundational principles used for evaluating
ethical issues. The course will equip students with skills for
survival in scientific research through training in moral
reasoning and teaching of responsible conduct. Students
will discuss current ethical issues in research and will learn
to apply critical thinking skills to the design, execution,
and analysis of experiments. Important issues include, for
example, the use of animals and humans in research,
ethical standards in the computer community, and research
fraud. In addition, currently accepted guidelines for behavior
in areas such as data ownership, manuscript preparation,
and
conduct of persons in authority may be presented and
discussed in terms of relevant ethical issues.
654 Data and Data Systems in the Physical
Sciences (3:3:0). Prerequisite: Competency in programming at
the level of CSI 601-607 or permission of
instructor. This course introduces the student to data issues associated with
modern physical sciences. Specifically, it examines data
access, formats, browsing, analysis, visualization and
data information systems in federated environments.
Illustrative examples are used from the physical sciences,
including astronomy and space sciences; Earth sciences;
Earth observing and other fields of physics; as well as
model output data and associated special issues. The student
is introduced to some mathematical techniques that are
particularly important for large databases, including
principal component analysis, dimensional reduction, etc.
655/PHYS 575 Introduction to Physics and
Chemistry of the Atmosphere (3:3:0). Prerequisites: PHYS 305
and 262. Introduction to basic physical and chemical
processes that operate in Earth's atmosphere. Emphasizes
those concepts that provide a global description of the
current atmospheric state and those processes that relate to
global change and atmospheric evolution. Covers
equilibrium structure, radiative transfer models, thermodynamics
of various atmospheric layers, and the various
processes defining these layers.
656/EVPP 652/GEOG 570 The Hydrosphere
(3:3:0). Prerequisites: Two semesters of calculus (partial
differential equations recommended) or permission of
instructor. The components and transfer processes within the
hydrosphere. The hydrosphere consists of the aqueous
envelope of Earth, including the oceans, lakes, rivers, snow, ice,
glaciers, soil moisture, ground water, and atmospheric
water vapor. Students get an understanding of the various
components of the hydrosphere, their spatial and
temporal distributions, the physics of the transfer processes for
redistribution, and an appreciation of the role of water in
sustaining life and influencing the global and regional
energy and mass balance.
657/GEOL 601/GEOG 671 The Lithosphere
(3:3:0). Prerequisite: graduate standing.
A global-scale overview of the lithosphere, the solid nonliving Earth, its
materials, cycles, plate tectonic and geomorphic processes, and
history, including interactions with and history of the
hydrosphere, atmosphere, and biosphere, and methods of
analysis. Students who have taken this course will be able to
understand the materials, features, and landforms of solid
Earth, and the processes by which they formed.
660/ASTR 535 Space Instrumentation and
Exploration (3:3:0). Prerequisites: PHYS 262, MATH 213 or
equivalent, or permission of instructor. Survey of the
instruments, devices, and methods used for space and planetary
exploration. Covers remote sensing of Earth and other solar
system bodies. Planned manned and unmanned missions
by United States and other countries.
661/ASTR 530 Astrophysics (3:3:0).
Prerequisites: PHYS303, 305, 308; MATH 214. Survey of
contemporary astrophysics. Topics include physical concepts, stellar
spectra, Hertzsprung-Russell diagram, stellar atmospheres,
stellar structure, interstellar matter, stellar evolution,
high-energy phenomena, hydrodynamical processes in
astrophysics, accretion disk formation, and shock formation.
672/STAT 652 Statistical Inference
(3:0:0). Prerequisites: STAT 544 or permission of instructor.
Critical aspects of probability, random variables and distributions,
characteristic functions, and stochastic convergence. Optimal
estimation, maximum-likelihood estimation, asymptotic
theory, Bayesian methods, likelihood-ratio tests, statistical
decision theory, sequential methods.
678/STAT 658 Times Series Analysis and
Forecasting (3:0:0). Prerequisites: STAT 544 or CSI 672, or
permission of instructor. Modeling stationary and
nonstationary processes, autoregressive, moving average and mixed
model processes, hidden periodicity models, properties of
models, autocovariance functions, autocorrelation
functions, partial autocorrelation function, spectral density
functions, identification of models, estimation of model
parameters, and forecasting techniques.
685 Fundamentals of Materials Science
(3:3:0). Prerequisite: Undergraduate degree in physics, chemistry,
materials, electrical or mechanical engineering, or
related sciences, or permission of instructor. Covers
fundamental concepts, methods, and applications of materials
science. Also covers structure of modern materials (metallic
alloys and compounds, ceramic materials, semiconductors,
polymers, and nanostructured materials), materials
properties (mechanical, thermal, and electric), experimental
methods of materials characterization, application of computers
in materials science, and elements of materials design.
687/PHYS 512 Solid State Physics and
Applications (3:3:0). Prerequisite: PHYS 502 or
equivalent. Covers crystal structures, binding, lattice vibrations, the free
electron model, metals, semiconductors and semiconductor
devices, superconductivity, and magnetism.
700/MATH 685 Numerical Methods (3:3:0).
Prerequisites: MATH 214, 203, and some programming
experience. Covers computational techniques for the solution of
problems arising in science and engineering. Algorithms
are developed for the treatment of typical problems in
applications, with special emphasis on the types of data
encountered in practice. The course covers theoretical
development, as well as implementation, efficiency, and accuracy
issues in using algorithms and interpreting the results. When
applicable, computer graphical techniques are used to
enhance interpretation of results.
701 Foundations of Computational Science (3:3:0).
Prerequisites: Competency in UNIX and programming at
the level of CSI 601-604, CSI 700, or permission of
instructor. Covers the mapping of mathematical models to
computer software, including all aspects of the development of
scientific software, such as architecture, data structures,
advanced numerical algorithms, languages,
documentation, optimization, validation, verification, and software
reuse. Examples in bioinformatics, computational biology,
computational physics, and global change demonstrate
scientific advances enabled by computation. Class
projects involve working in teams to develop software that
implements mathematical models, using the software to
address important scientific questions, and conducting
computational experiments with it.
702 High-Performance Computing (3:3:0).
Prerequisites: CSI 700 and CSI 701, or permission of
instructor. Hardware and software associated with high-performance
scientific computing. Computer architectures, processor
design, programming paradigms, parallel and vector
algo
rithms. Emphasis on the importance of software
scalability in science problems.
703 Scientific and Statistical Visualization (3:3:0).
Prerequisite: STAT 554 or CS 652, or permission of
instructor. Covers visualization methods used to provide new
insights and intuition concerning measurements of natural
phenomena and scientific and mathematical models. Presents
case study examples from a variety of disciplines to
illustrate what can be done. Topics include human perception
and cognition, an introduction to the graphics laboratory,
elements of graphing data, representation of space-time
and vector variables, representation of 3-D and higher
dimensional data, dynamic graphical methods, and virtual
reality. Students are required to work on a visualization
project. Software tools on the Silicon Graphics workstation
are emphasized, but other workstations and software may
be used for the project.
709 Topics in Computational Sciences and
Informatics (3:3:0). Prerequisites: Admission to Ph.D. program
and permission of instructor. Covers selected topics in
computational sciences and informatics not covered in
fixed-content computational sciences and informatics courses.
May be repeated for credit as needed.
710 Scientific Databases (3:3:0). Prerequisite: INFS
614 or equivalent, or permission of
instructor. Study of database support for scientific data management. Covers
requirements and properties of scientific databases,
data models for statistical and scientific databases, semantic
and object-oriented modeling of application domains,
statistical database query languages and query optimization,
advanced logic query languages, and case studies such as
the human genome project and Earth-orbiting satellites.
711/CHEM 633 Chemical Thermodynamics and
Kinetics (3:3:0). Prerequisites: CHEM 331 and
332. Advanced study of thermodynamics and kinetics. Covers
application of kinetics to the elucidation of reaction mechanisms,
and application of statistical thermodynamics to the theory
of elementary reaction rates.
712/CHEM 728 Introduction to Solid Surfaces
(3:3:0). Prerequisite: CHEM 422 or
equivalent. Introduction to the properties of solid surfaces. Includes gas absorption
isotherms, surface area measurement techniques, real and
clean surfaces, physisorption and chemisorption, methods of
gas absorption and desorption, measurement of heats of
adsorption, desorption kinetics, electron spectroscopies
and their surface sensitivities, instrumentation needed, and
principles of vacuum technology.
713/CHEM 732 Quantum Chemistry (3:3:0).
Prerequisite: CHEM 332. Illustration of the fundamental
concepts of quantum mechanics with applications to
chemical systems, including atomic and molecular electronic
structure and properties, molecular symmetry, and
intermolecular forces.
714 Spectroscopy and Structure (3:3:0).
Prerequisite: CHEM 332. Covers quantum mechanics of the
interaction of atoms and molecules with electromagnetic radiation.
Also covers modern spectroscopic methods as applied to
the elucidation of molecular structure and dynamics.
719 Topics in Computational Chemistry
(3:3:0). Prerequisite: Permission of
instructor. Covers selected topics in computational chemistry not covered in
fixed-content
computational chemistry courses. May be repeated for
credit as needed.
720 Fluid Mechanics (3:3:0). Prerequisites: CSI 700,
780, or permission of instructor. Covers basic and advanced
fluid mechanics and the continuous hypothesis to define
fluids. Introduces tensor analysis; Euclidean and Lagrangian
representation of fluid flow; Laplace's equation; the
continuity equation; Navier-Stokes equations; the
Bernoulli theorem and Crocco's form of the equations; steady
and unsteady flows; potential, incompressible, and
compressible flows; gravity and sound waves; gas dynamics;
and viscous flows.
721 Computational Fluid Dynamics I
(3:3:0). Prerequisites: Course in partial differential equations such
as MATH678 or equivalent, knowledge of linear algebra
at the level of MATH 603 or CSI 740/MATH 625,
coding experience in FORTRAN or C, or permission of
instructor. Covers fundamentals of computational fluid dynamics,
including spatial and temporal approximation techniques
for partial differential equations, solution of large systems
of equations, data structures, solvers of the
Laplace/full potential equation, and simple Euler solvers. Two
major projects are included: a Laplace solver and a 2-D
Euler solver on unstructured grids. Students are expected to
write their own codes.
722 Computational Fluid Dynamics II
(3:3:0). Prerequisite: CSI 721 or permission of instructor.
Covers some of the more advanced topics in computational fluid
dynamics, including high-resolution schemes for
hyperbolic PDEs, advanced Euler solvers, Navier-Stokes solvers,
grid generation, adaptive mesh refinement, efficient use
of supercomputing hardware, and future trends. Projects
include topics in grid generation and adaptive
refinement. Students are expected to write their own codes.
723 Fluid Mechanics II (3:3:0). Prerequisites: CSI
720 or permission of instructor. Covers gas dynamics,
shock waves, the method of characteristics, boundary layer
flows, instabilities, and turbulence modeling. Special topics
include biological, non-Newtonian, and free surface
flows; aeroelasticity; and magneto-hydrodynamics.
729 Topics in Continuum Systems (3:3:0).
Prerequisite: Permission of instructor. Covers selected topics in the
computational aspects of continuum systems not covered
in fixed-content courses in dynamical systems. May be
repeated for credit as needed. Possible topics that may
be considered are smooth-particle hydrodynamics,
radiation hydrodynamics, algorithms for continuum systems,
adaptive grids for continuum computations, spectral
methods in computational fluid dynamics, algorithms for
concurrent machines, formation of high-energy particle jets
in astrophysical applications, application to Earth
atmospheric problems, and flow considerations in molten materials.
730 Biological Sequence Analysis
(3:3:0). Prerequisites: Competency in programming at the level of CSI
601-607, familiarity with molecular biology and cell biology at
the level of CSI 631, or permission of
instructor. Covers fundamental methods for the analysis of nucleic acid and
protein sequences, including pairwise alignment,
multiple alignment, database search methods, profile searches,
and phylogenetic inference. Also covers probabilistic
tools, including hidden Markov models and their
associated optimization algorithms. Provides survey and analysis
of current software tools.
731 Protein Structure Analysis (3:3:0).
Prerequisites: Course work in molecular biology, biochemistry, and
introductory computer programming, or permission of
instructor. A survey of the computational methods for the
analysis, classification, and prediction of three-dimensional
protein structures. Covers theoretical approaches, techniques,
and computational tools for protein structure analysis.
Topics include protein geometry and topology,
three-dimensional structure databases, protein modeling, and engineering.
732 Genomics (3:3:0). Prerequisites: General
biology, programming experience, CSI 700 or equivalent, CSI
730, or permission of instructor. A survey of computational
tools and techniques used to study whole genomes. Explores
the biological basis of genome analysis algorithms.
Lecture topics include genome mapping, comparative
genomics, and functional genomics.
734 Computational Neurobiology (3:3:0).
Prerequisites: CSI 631 or equivalent and ordinary differential
equations, or permission of instructor. Intense review of
neurobiology for graduate students interested in studying how nerve
cells integrate and transmit signals, and how behavior
emerges from the integrated actions of populations or circuits
of nerve cells. Covers electrical and biochemical
properties of single neurons, and electrical and chemical
communication between neurons. Emphasis is on mathematical
descriptions and computational techniques used to study
and understand neurons and networks of neurons.
735 Computational Neuroscience Systems
(3:3:0). Prerequisites: CSI 734 (previously or concurrently), CSI
630, CSI 631, or permission of instructor. Overview of
the nervous system and biological neural networks.
Includes learning and memory, sensory systems, and motor
systems. Stresses design and application of computational
models. Students are required to propose and design a
computational model that addresses some open issue in neuroscience.
739 Topics in Bioinformatics (3:3:0).
Prerequisite: Permission of instructor. Selected topics in
bioinformatics not covered in fixed-content bioinformatics courses.
May be repeated for credit as needed.
740/MATH 625 Numerical Linear Algebra
(3:3:0). Prerequisites: MATH 203 and some programming
experience. Covers computational methods for matrix systems;
theory and development of numerical algorithms for the
solution of linear systems of equations, including direct and
iterative methods; analysis of sensitivity of system to
computer round off; and solution of least squares problems
using orthogonal matrices. Also covers computation of
eigenvalues and eigenvectors, singular value decomposition,
and applications.
741/ECE 721 Nonlinear Dynamical Systems
(3:3:0). Prerequisites: Knowledge of linear algebra, advanced
calculus, and differential equations. Contemporary topics
in the field of nonlinear dynamical systems are illustrated
in mathematical models from the natural sciences and
engineering. Traditional qualitative analysis of difference
and differential equations provides the background for
understanding chaotic behavior when it occurs in these
models. Topics include stability of equilibria and periodic
orbits, bifurcation theory, Hamiltonian systems, Lyapunov
exponents, and chaotic attractors.
742/MATH 687 The Mathematics of the Finite
Element Method (3:3:0). Prerequisite: MATH 446 or 685, or
per
mission of instructor. The finite element method is a
commonly used technique for developing numerical
approximations to problems involving ordinary and
partial differential equations. This course develops the
underlying mathematical foundation for the method, examines
several specific types of finite elements, analyzes the
convergence rates and approximation properties of the method, and
uses it to solve a number of important equations. Students
develop their own codes and are expected to complete
independent projects.
744 Linear and Nonlinear Modeling in the
Natural Sciences (3:3:0). Prerequisite: Permission of
instructor. Develops the tools of mathematical modeling while
carrying out numerical simulations of the models. Examples
from across the sciences are considered throughout the
course. Topics include basic issues (models, simplification,
linearity, and nonlinearity), dimensionless parameters,
dimensional analysis, models involving differential
equations, examples from population growth and chemical
kinetics, models involving partial differential equations,
diffusion, transport, nonlinearity and shocks, probabilistic
modeling, perturbation methods, extrapolation, and an
introduction to stability.
745 Mathematical Tomography (3:3:0).
Prerequisite: MATH 675. Covers physical principles of tomography;
the Radon transform in Euclidean space; inversion
formulas; the Radon transform on distributions; integral
geometry and generalized Radon transforms; the Radon
transform on symmetric spaces; and applications to CAT, PET,
radar imaging, and synthetic aperture radar.
746 Wavelet Theory (3:3:0). Prerequisites: Knowledge
of convolution and Fourier transforms of sequences;
some familiarity with Hilbert space theory helpful but not
required; knowledge of a scientific programming
language. Study of the theory and computational aspects of
wavelets and the wavelet transform. Emphasizes computational
aspects of wavelets, defining the Fast Wavelet Transform
in one and two dimensions and developing the
appropriate numerical algorithms, then develops the theory of
wavelet bases on the real line, discussing multi-resolution
analysis, splines, time-frequency localization, and wavelet packets.
748/MATH 629 Symbolic Computation
(3:3:0). Prerequisites: Undergraduate degree in a scientific
discipline, and a course in abstract algebra. Provides the
mathematical and computational background for computational
algebraic geometry and its applications. Includes notions
of algebra, geometry, algorithms, the concept of
Groebner bases, automatic theorem proving, and serial and
parallel algorithms and their complexity. Topics are related to
applications in engineering and computer science. Students
are expected to complete projects.
749 Topics in Computational Mathematics
(3:3:0). Prerequisite: Permission of instructor.
Selected topics in computational mathematics not covered in
fixed-content computational mathematics courses. May be repeated
for credit as needed.
750 Earth Systems and Global Changes
(3:3:0). Prerequisite: Course in ecology, environmental geology,
atmospheric physics, or permission of
instructor. Introduction to the global system interactions responsible for
global environmental change. Discusses the natural causes of
past and present global changes, how human activities
affect these global system changes, and the ecological and
hu
man consequences of these global changes. Topics
include climate and hydrological systems, global warming,
deforestation, ozone depletion, ecological system dynamics,
introduction to climate and global change monitoring,
satellite instrumentation and calibration, and model predictions.
751 Introduction to Physical Climate System
(3:3:0). Prerequisites: CSI 755 or permission of instructor.
Provides the student with a modern understanding of the
system of ocean, atmosphere, and land based on
fundamental physical laws. Describes the current climate and the
physical processes by which climate is maintained. Covers
theoretical models of the general circulation of the
atmosphere including both the time mean and transient
behavior. Describes the basics of ocean circulation and
interactions between the ocean and atmosphere. Reviews the role
of the stratosphere and its interactions with the
troposphere, the role of land processes in modulating climate, and
gives a brief review of past climate change.
752 Physical and Dynamical Oceanography
(3:3:0). Prerequisite: CSI 751 or permission of instructor.
Introduction to the climatology and dynamics of the
oceans. Covers the nature of seawater, heat, and salt budgets;
the general circulation of the ocean, including the Gulf
Stream and thermohaline circulations; dynamics of
wind-driven ocean circulation; and the processes influencing
biological and chemical behavior.
753 Observations of the Earth and its Climate
(3:3:0). Prerequisites: CSI 660 or an introductory remote
sensing course; environmental science, space science, physics,
or chemistry undergraduate background; or permission
of instructor. Provides the requisite material to
understand techniques of remote sensing and other observational
methods as applicable to Earth science and global change.
Surveys methodologies and their applications, including
a systematic study of how each part of the
electromagnetic spectrum is used to gather data about Earth. Describes
limitations imposed by satellite engineering, sensor
limitations on data gathering, and a survey of data reduction
specific to remote sensing applications. Also covers current
research issues, including examples pertaining to the
atmosphere, land masses, and oceans. Includes discussions of
current efforts by agencies such as NASA and NOAA to
provide integrated data gathering and dissemination systems.
754 Earth Observing/Remote Sensing Data and
Data Systems (3:3:0). Prerequisite: CSI 753 or permission
of instructor. Covers how to access and apply Earth
observations/remote sensing data for Earth system science
research and applications. Major topics are data formats,
analysis and visualization tools, and data applications. The
course covers combining innovative information technology
techniques and Earth science data to set up online data
centers for web users to be able to access data through the web.
755/PHYS 676 Introduction to Atmospheric
Dynamics (3:3:0). Prerequisite: M.S. in physics or mathematics,
or permission of instructor. Covers the basic conservation
laws of mass, momentum, and energy, and a scaling analysis
of the equation of motion and the thermodynamic
equation. Balanced flows in the atmosphere (e.g., the geotropic
wind and its vertical shear, and the thermal wind
relationship) are discussed. Concepts of circulation and vorticity;
the role of the atmospheric boundary layer in mass,
momentum, and energy transfer; synoptic scale motions; and
the
role of gravity and Rossby waves in controlling the
general circulation of the atmosphere are also discussed.
756 Numerical Methods for Climate Modeling
(3:3:0). Prerequisites: CSI 752 or CSI 755 or equivalent, or
permission of instructor. The foundation and theory of
computational methods for atmosphere and ocean
modeling, with special emphasis on the finite-difference and
spectral methods. Topics include accuracy, consistency,
convergence and stability; time stepping schemes; nonlinear
computational stability; energy and enstrophy conserving
schemes for the momentum equations; staggered and
curvilinear grids; alternate vertical coordinate systems; implicit
and split-explicit barotropic mode solution; pressure
gradient errors and vorticity constraints; spectral methods for
atmospheric models; treatment of model physics.
757 Techniques and Algorithms in Earth Observing
and Remote Sensing (3:3:0). Prerequisite: CSI 753 or
permission of instructor. Covers retrieval, analysis, and
application of geophysical parameters derived from
remotely sensed data for Earth system research and
applications. Includes theory of visible/infrared and microwave
remote sensing, heritage sensors, sensor calibration, retrieval
algorithms, validation, and error estimates.
758 Visualization and Modeling of Complex
Systems (3:3:0). Prerequisite: Permission of
instructor. Covers elements of modeling and analysis of Earth and space
sciences data and systems. Concentrates on both
sample projects and student-initiated projects as a means of
using visualization and graphical analysis techniques as they
apply to the modeling of complex data sets and systems.
Several different analysis and visualization packages are
used. Spacecraft data sets from the Naval Research
Laboratory (NRL) Backgrounds Data Center and other NRL data
sets are available for course projects. A perusal of data sets
from the World Wide Web is also possible. Modeling and
analysis are accompanied by appropriate readings from the
current literature.
759 Topics in Earth Systems and Global Changes
(3:3:0). Prerequisite: Permission of
instructor. Covers selected topics in Earth systems and global changes not covered in
fixed-content Earth systems/global changes courses. May
be repeated for credit as needed.
761/ASTR 761 N-Body Methods and Particle
Simulations (3:3:0). Prerequisites: PHYS 613/CSI 780
and CSI700 or permission of instructor. Covers particle
methods as a tool in solving a variety of physical systems.
Emphasizes the study and development of the numerical
results and visualization of these results in complex physical
systems. Applications and projects include stellar and
galaxy dynamics, smoothed particle hydrodynamics, plasma
simulations, and semiconductor device theory algorithms
on parallel and vectorized systems.
763 Statistical Methods in Space Sciences
(3:3:0). Prerequisite: ASTR 530 or permission of instructor.
Covers statistical and data analysis methods applicable to
problems in space science, remote sensing, and astrophysics.
Includes parametric and nonparametric hypothesis testing,
parameter estimation, correlation analysis, time series
analysis, spatial analysis, and image reconstruction. Emphasizes
the imperfect nature of actual data sets and hypothesis.
Examples are drawn from current space science research.
764/ASTR 764 Computational Astrophysics
(3:3:0). Prerequisite: ASTR 530. Covers statistical mechanics
concepts important in astrophysics. Presents unified
approach to particle acceleration and interaction theory based
on analytical and numerical analysis of Boltzmann
and Liouville equations. Discusses computational methods
relevant to particle transport problems, with emphasis
on Fokker-Planck and Monte Carlo solution techniques.
Applications from space sciences include studies of cosmic
ray acceleration, photon comptonization, particle transport
in the near-Earth environment, energy transport in stellar
atmospheres, and self-gravitating system dynamics.
765/ASTR 765 High-Energy and Accretion
Astrophysics (3:3:0). Prerequisite: PHYS 502, ASTR 530, PHYS
613/CSI 780, or permission of instructor. Overview of the
field of atomic and nuclear physics. Covers nuclear reactions
of use to high-energy astrophysics; radiation processes
in cosmic plasmas, emphasizing quantum mechanical
calculations; stellar evolution and nucleosynthesis;
computational models of stellar evolution; binary stars and accretion
disks; numerical models of the structure of accretion disks;
compact stars, white dwarfs, neutron stars, and black
holes; acceleration processes and cosmic rays; interstellar
medium and propagation of cosmic rays; high-energy processes
in the center of galaxies; and ground- and space-based
techniques and observations.
766/ASTR 766 Relativity and Cosmology
(3:3:0). Prerequisites: ASTR 530 and MATH 314, or permission of
instructor. Covers special relativity, four-dimensional
space-time, general relativity, non-Euclidean geometries,
geodesic and field equations, test of general relativity
theory, black holes, cosmic background radiation,
thermodynamic considerations in cosmology, and cosmological models.
769/ASTR 769 Topics in Space Sciences (3:3:0).
Prerequisite: Permission of instructor.
Selected topics in space sciences not covered in fixed-content space
sciences courses. May be repeated for credit as needed.
771/STAT 751 Computational Statistics (3:3:0).
Prerequisites: STAT 544, 554, and 652. Covers the basic
computationally intensive statistical methods and related
methods, which would not be feasible without modern
computational resources. Covers nonparametric density estimation
including kernel methods, orthogonal series methods and
multivariate methods, recursive methods,
cross-validation, nonparametric regression, penalized smoothing splines,
the jackknife and bootstrapping, computational aspects of
exploratory methods including the grand tour,
projection pursuit, alternating conditional expectations, and
inverse regression methods.
773/STAT 663 Statistical Graphics and Data
Exploration (3:3:0). Prerequisite: Three hundred-level course
in statistics; STAT 554 strongly recommended.
Exploratory data analysis provides a reliable alternative to
classical statistical techniques, which are designed to be the
best possible when stringent assumptions apply. Topics
include graphical techniques such as scatter plots, box plots,
parallel coordinate plots, and other graphical devices;
re-expression and transformation of data; influence and leverage;
and dimensionality reduction methods such as projection pursuit.
775/OR 719/STAT 719 Computational Models of
Probabilistic Reasoning (3:3:0). Prerequisites: STAT 652 or
664, or permission of instructor. Introduction to theory
and methods for building computationally efficient
software
agents that reason, act, and learn environments
characterized by noisy and uncertain information. Covers
methods based on graphical probability and decision models.
Students study approaches to representing knowledge
about uncertain phenomena, and planning and acting under
uncertainty. Topics include knowledge engineering, exact
and approximate inference in graphical models, learning
in graphical models, temporal reasoning, planning, and
decision-making. Practical model building experience is
provided. Students apply what they learn to a
semester-long project of their own choosing.
776/IT 746 Stochastic Calculus (3:3:0).
Prerequisites: STAT 652; ECE 630 or 632; or permission of
instructor. Introduction to modern theory of stochastic calculus.
Covers stochastic integrals, martingales, counting
processes, diffusion processes, and Ito-type processes in
general. Applications of these methods to engineering, biology,
and economics are considered in some detail.
777 Principles of Knowledge Mining
(3:0:0). Prerequisites: INFS 614 or equivalent, or permission of
instructor. A presentation of principles and methods for
synthesizing task-oriented knowledge from computer data and
prior knowledge, and presenting it in human-oriented forms,
such as symbolic descriptions, natural language-like
representations, and graphical forms. Topics include
fundamental concepts of knowledge mining, methods for target
data generation and optimization, statistical and symbolic
approaches, knowledge representation and visualization,
and new developments such as inductive databases,
knowledge generation languages, and knowledge scouts.
778/IT 776 Real Analysis and Statistics
(3:3:0). Prerequisites: STAT 652; ECE 620, 621, or 630; or permission
of instructor. Advanced calculus and linear algebra
needed for doctoral work in statistics and related fields.
Covers topology, vector spaces, matrices, continuity,
differentiation, sequences and series of real numbers and real-valued
functions, Riemann and Riemann-Stieltjes integrals, and
multidimensional calculus. Presents applications in
probability and statistics, including response surface methodology.
779 Topics in Computational Statistics
(3:3:0). Prerequisite: Permission of
instructor. Selected topics in computational statistics not covered in fixed-content
computational statistics courses. May be repeated for credit as needed.
780/PHYS 613 Computational Physics and
Applications (3:3:0). Prerequisites: PHYS 510; FORTRAN, C, or
C++ programming; or permission of instructor. PHYS 502
or equivalent recommended. Study of diverse physical
systems with emphasis on modeling and simulation.
Development of numerical algorithms and application of numerical
methods to gain understanding of the mechanisms and
processes taking place in the physical system. Several projects
are undertaken, which are drawn from such areas as
atomic and molecular interactions, molecular dynamics,
quantum systems, chaos, percolation, random walks, and
aggregation mechanisms.
781 Plasma Science (3:3:0). Prerequisite: PHYS 513
or PHYS 722/CSI 785, PHYS 711/CSI 782/CHEM 730; or permission of
instructor. Study of ionized matter, theory, and some computation with application to
astrophysics, industrial plasma processing, magnetosphere, and
ionosphere problems. Vlasov and fluid equations are
derived and applied in plasma science, including the study of
plasmas with and without magnetic fields.
782/PHYS 711 Statistical Mechanics (3:3:0).
Prerequisites: PHYS 502 and 613 or permission of instructor.
Covers microcanonical, canonical, and grand canonical
ensembles and fluctuations, Fermi-Dirac and Bose-Einstein
statistics, the ideal monatomic gas and diatomic gas, the
Liouville equation, equipatition of energy, crystals, imperfect
gases, kinetic theory, quantum statistics, and transport processes.
783/PHYS 736 Computational Quantum Mechanics
(3:3:0). Prerequisites: PHYS 502 and PHYS 613/CSI
780, or permission of instructor. Study of the fundamental
concepts of quantum mechanics from a computational
point of view, review of systems with spherically
symmetric potentials, many electron-atom solutions to
Schroedinger's equation, electron spin in many-electron systems,
atomic structure calculations, algebra of many-electron
calculations, Hartree-Fock self-consistent field method,
molecular structure calculations, scattering theory
computations, and solid-state computations.
784/PHYS 732 Quantum Mechanics (3:3:0).
Prerequisite: PHYS 502 or permission of
instructor. Study of the fundamental concepts of quantum mechanics, time
evolution, Schroedinger and Heisenberg formalism,
harmonic oscillators, propagators, Feynman path integrals,
rotations and angular momentum, angular momentum
eigenvalues and eigenstates, Bell's inequality, symmetries,
conservation laws, degeneracy, perturbation theory, WKB
methods, and scattering theory.
785/PHYS 722 Electromagnetic Theory
(3:3:0). Prerequisites: PHYS 513 and PHYS 613/CSI 780, or
permission of instructor. Advanced study of electric and
magnetic fields. Topics include electrostatic fields,
magnetostatic fields, boundary-value problems in field theory,
multipoles, simple radiating systems, relativistic electrodynamics,
and radiation by moving charges.
786 Molecular Dynamics Modeling (3:3:0).
Prerequisite: PHYS 613/CSI 780 or CHEM 633/CSI 711, or
permission of instructor. Introduction to simulation methods used
in the physical chemistry sciences. Covers
computational approaches to modeling molecular and condensed
matter systems, including interatomic and molecular
potentials, molecular dynamics, time averages, ensemble
distributions, numerical sampling, thermodynamic functions,
response theory, transport coefficients, and dynamic structure.
Includes stochastic simulations such as Brownian
motion, Langevin dynamics, Monte Carlo methods and
random walks, and an introduction to cellular automata.
787 Computational Materials Science
(3:3:0). Prerequisites: PHYS 512/CSI 687 and PHYS 736/CSI 783,
or permission of instructor. Covers selected topics in the
computational aspects of condensed matter, such as
methods of electronic structure calculations, surface science,
molecular clusters, lattice dynamics, nanomaterials,
semiconductors, superconductivity, quantum Hall effect,
magnetism, Hubbard model, mesoscopic systems, and liquids.
788/PHYS 728 Simulation of Large-Scale
Physical Systems (3:3:0). Prerequisites: PHYS 613/CSI 780
and CSI 700, or permission of instructor. Study of diverse
large-scale physical systems, with emphasis on the modeling
and simulation of these multifaceted systems. Several
projects are undertaken, which are drawn from such areas as
many-body dynamics, atmospheric structure and dynamics,
high-temperature plasmas, stellar structure, hydro
dynamical systems, galactic structure and interactions, and cosmology.
789/PHYS 780 Topics in Computational Physics
(3:3:0). Prerequisite: Permission of instructor.
Selected topics in computational physics not covered in fixed-content
computational physics courses. May be repeated for credit
as needed.
792/EVPP 792/GEOG 792 Seminar in Earth
Systems Science (2:2:0). Prerequisites: Fifteen graduate
credits including CSI 655, 656, and 657. A seminar for Earth
systems science graduate students who have backgrounds
in Earth's major systems. Intended to be a capstone
experience. Seminars will be presented by faculty and
students. Topics will vary from semester to semester.
796 Directed Reading and Research
(1-6:0:0). Prerequisite: Permission of
instructor. Reading and research on a specific topic in computational sciences and
informatics under the direction of a faculty member. May be
repeated as necessary.
798 Research Project (3:0:0). Prerequisites: Twelve
graduate credits and permission of instructor. Project chosen
and completed under the guidance of a graduate faculty
member, resulting in an acceptable technical report.
799 Master's Thesis (1-6:0:0).
Prerequisites: Twelve graduate credits and permission of
instructor. Project chosen and completed under the guidance of a graduate faculty
member, resulting in an acceptable technical report
(master's thesis) and oral defense. Graded S/IP.
850 Atmosphere-Ocean Interactions
(3:0:0). Prerequisites: CSI 752 or CSI 755 or equivalent, or permission
of instructor. This course will provide students with a
comprehensive observational and mechanistic
understanding of the El Niño and the Southern Oscillation (ENSO)
phenomena. Topics will include: observations and theories
of the seasonal and interannual changes in the ocean
circulation and temperature, and interactions with the
atmosphere; equations of motion and theories of wind-driven
circulation; mixed layer observations and theories;
mid-latitude and equatorial ocean waves; interannual variability
and atmosphere-ocean coupling; and tropical oceanography
and meteorology.
851 Land-Climate Interaction (3:0:0).
Prerequisites: CSI 751 or CSI 755 or equivalent, or permission of
instructor. This interdisciplinary course provides students with a
detailed description of the surface energy and water
balance over land, and radiative and turbulent transfer. Students
will be introduced to numerical techniques for modeling
the land surface and associated applications in weather,
climate, and hydrologic forecasting and simulation. The
course includes hands-on experience with land surface models
in a computer laboratory, in which students will perform
sensitivity experiments that provide practical
understanding to reinforce theoretical concepts. The course also
includes reading and review of seminal journal papers in the
field, exposing students to contemporary research.
852 Geophysical Fluid Dynamics (3:3:0).
Prerequisite: CSI 755 or permission of instructor.
Introduction to geophysical fluid dynamics, the study of rotating
stratified flows. Covers hydrostatics, the equations of motion,
gravity wave dynamics and stratified flow, effects of
rotation, mid-latitude dynamics, the Rossby number and
quasi-geostrophic expansion, the beta plane approximation,
and equatorial Kelvin and Rossby waves.
854 Computing and Communication Systems for
Earth Observing (3:3:0). Prerequisite: CSI 754 or
permission of instructor. In-depth study of computing and
communications systems, with emphasis on performance issues
and capacity for sustaining modern Earth observing
systems. Covers functional breakdown of ground receiving
stations, international communications standards for space data
telemetry (such as CCSDS) and their impact on data
fidelity and processing, and instrumentation for ground
stations and trade-off between on-board versus ground station
processing. Also discussed are computer system
performance appreciation and computing systems limitations;
implications of data product levels and standards for
processing, input/output, and storage requirements; and
applications of high performance computing, storage hierarchies,
and parallel input/output concepts and systems for
speeding data access and processing.
855 Predictability of Weather and Climate
(3:0:0). Prerequisites: CSI 755 or equivalent, or permission of
instructor. This course covers the fundamental aspects of
the predictability of weather and climate. Basic theorems
on the divergence of trajectories in phase space and the
fundamental periodicity properties of the flow are
illustrated using simple dynamical models. The paradigms of
turbulence, barotropic/baroclinic instability and optimal
linear growth are explored to describe fundamental error
growth mechanisms. Examples from real weather forecasting
systems will be examined. Predictability of time averages
will be studied with simple dynamical models, as well as
experiments using complex General Circulation Models
and historical data analysis. The roles of the boundary
conditions of sea surface temperature and soil moisture will
be emphasized.
856 Ocean Circulation Theory (3:0:0).
Prerequisites: CSI 752 or CSI 755 or equivalent, or permission of
instructor. The theory of the large scale circulation of the
world's oceans. The topics covered will be the Sverdrup theory
for large scale horizontal circulation, the role of friction
and nonlinearity; western boundary layer dynamics;
Quasi-geostrophic theory for stratified flow, geostrophic contours
and potential vorticity homogenization; theory of the
ventilated thermocline; abyssal circulation.
873 Computational Learning and Discovery
(3:0:0). Prerequisites: CS 580 or equivalent, or permission of
instructor. This course presents modern ideas, theories,
and methods for computational learning and discovery,
along with relevant applications. Application areas include
medical diagnosis, earth science data analysis, and
neuronal modeling. The course will include a background
elucidation of fundamental concepts in computational
learning, addressing in particular discovery of equations, theory
of causality, and comparison with biological and
cognitive models. Students will have an opportunity to make
presentations on topics of their research interest, and to work
on projects involving state-of-the art systems.
876/IT 876 Measure and Linear Spaces
(3:3:0). Prerequisite: IT 776/CSI 778 or permission of instructor.
Covers measure theory and integration, convergence theorems,
and the theory of linear spaces and functional analysis,
including normed linear spaces, inner product spaces,
Banach and Hilbert spaces, Sobelev spaces, and reproducing
kernels. Topics include wavelets, applications to
stochastic processes, and nonparametric functional inference.
877/IT 877 Geometric Methods in Statistics
(3:3:0). Prerequisite: STAT 751 or permission of
instructor. Develops the foundations of geometric methods for
statistics. Topics include n-dimension Euclidian geometry;
projective geometry; differential geometry, including
curves, surfaces, and n-dimensional differentiable manifolds;
and computational geometry, including computation of
convex hulls, tessellations of two-, three-, and n-dimensional
spaces, and finite element grid generation. Examples include
applications to scientific visualization.
888 Topics in Quantum Systems (3:3:0).
Prerequisite: PHYS 736/CSI 783 or PHYS 732/CSI 784, or
permission of instructor. Covers selected topics in quantum systems
in physics and chemistry not covered in fixed-content
courses in quantum mechanics. May be repeated for credit
as needed. Possible topics are new spectroscopic
methods, density functional theory, energy transfer and
fluorescence, nuclear magnetic resonance, Mossbauer spectroscopy,
advanced computational considerations in atomic
and/or molecular structure, nuclear scattering theory,
quantum considerations in condensed matter problems, and
quantum gravity.
898 Research Colloquium in Computational
Sciences and Informatics (1:1:0). Presentations in specific
research areas in computational sciences and informatics by
School of Computational Sciences faculty and staff members,
and professional visitors. May be repeated for credit;
however, a maximum of three credits of CSI 898, 899, and 991
may be applied toward the Ph.D.
899 Colloquium in Computational Sciences and
Informatics (1:1:0). Presentations in a variety of areas
of computational sciences and informatics by School
of Computational Sciences faculty and staff members,
and professional visitors. May be repeated for credit;
however, a maximum of three credits of CSI 898, 899, and 991
may be applied toward the Ph.D.
909 Advanced Topics in Computational Sciences
and Informatics (3:3:0). Prerequisite: Permission of
instructor. Covers selected topics in computational sciences
and informatics not covered in fixed-content courses. May
be repeated for credit as necessary.
972/IT 972 Mathematical Statistics I
(3:3:0). Prerequisite: STAT 652 or
equivalent. Focuses on the theory of estimation. Principles of estimation are explored,
including the method of moments, least squares, maximum
likelihood, and maximum entropy methods. Methods of
minimum variance unbiased estimation are covered in detail.
Other topics include sufficiency and completeness of
statistics, Fisher information, Cramer-Rao bounds,
Bhattacharyya bounds, asymptotic consistency and distributions,
statistical decision theory, minimax and Bayesian decision
rules, and applications to engineering and scientific problems.
973/IT 973 Mathematical Statistics II
(3:3:0). Prerequisite: CSI 972. Continuation of CSI 972. Concentrates
on the theory of hypothesis testing. Topics include
characterizing the decision process, simple versus simple
hypothesis tests, Neyman Pearson Lemma, uniformly most
powerful tests, unbiasedness of tests, invariance of tests,
randomized tests, and sequential tests. Applications of the
testing principles are made to situations in the normal
distribution family and to other families of distributions.
976/IT 976 Statistical Inference for Stochastic
Processes (3:3:0). Prerequisite: CSI 776 or permission of
instructor. Covers the modern theory of parameter estimation
and hypothesis testing for stochastic processes, counting
processes with random intensities, and solutions to
stochastic differential equations driven by martingales.
Applications to engineering, biology, and economics are considered.
978/IT 978 Statistical Analysis of Signals
(3:3:0). Prerequisites: STAT 544 and 658 or
equivalent. Advanced course in the analysis of discrete- and continuous-time
signals using methods of stochastic differential equation
and time series. Familiarity with the methods of harmonic
analysis and times series modeling is presumed. Topics
include state-space modeling and eigen-value processing,
nonlinear modeling of signals, non-Gaussian stochastic
process structure, detection and estimation of vector-valued
signals, robust signal detection, and array processing and
target tracking.
979/IT 979 Advanced Topics in Computational
Statistics (3:3:0). Prerequisite: Permission of
instructor. Covers selected topics in computational statistics not covered
in fixed-content computational statistics courses. May be
repeated for credit as needed.
986 Advanced Topics in Large-Scale Physical
Simulation (3:3:0). Prerequisite: Permission of
instructor. Covers simulation of physical systems not covered in
fixed-content physical simulation courses. May be repeated for
credit as needed.
991 Seminar in Scientific Computing
(1:1:0). Considers selected topics in a specific area of computational
sciences and informatics either not covered in fixed-content
courses or as an extension of fixed-content courses. Format
for presentation is that of a seminar with student
participation. May be repeated for credit; however, a maximum
of three credits of CSI 898, 899, and 991 may be applied
toward the Ph.D.
996 Doctoral Reading and Research
(1-6:0:0). Prerequisites: Admission to doctoral program and permission
of instructor. Reading and research on a specific topic in
computational sciences and informatics under the direction
of a faculty member. May be repeated as needed.
998 Doctoral Dissertation Proposal
(1-12:0:0). Prerequisite: Permission of
advisor. Covers development of a research proposal under the guidance of a dissertation
director and the doctoral committee. The proposal forms the
basis for the doctoral dissertation. This course may be
repeated as needed; however, no more than a total of 24 credits
in CSI 998 and 999 may be applied toward satisfying
doctoral degree requirements. Out of the 24-hour total, no
more than 12 credits of CSI 998 may be applied.
999 Doctoral Dissertation (1-12:0:0).
Prerequisite: Admission to doctoral
candidacy. Involves doctoral dissertation research under the direction of the dissertation
director. May be repeated as needed; however, no more than a
total of 24 credits in CSI 998 and 999 may be applied
toward satisfying doctoral degree requirements.
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