Fall
2009 Courses
Registration for fall classes begins March and will continue through September
11, 2009. New students
to the program can begin their registration for fall beginning in late
July. Registration forms are available online. This
page contains links to course descriptions, course outlines (syllabi) and
faculty homepages.
Class
recording begins on August 31, 2009.
|
Course
Number |
Course
Name |
Instructor |
Delivery
Format
|
|
BIOENGINEERING |
|
BME
520/420
|
Advances Med Diag – Machine Intelligence
|
Prof. Walker Land
|
Internet |
|
BME
525
|
The Finite Element Method with Applications to
BioMedical Problems
|
Prof.
Jacques Beaumont |
Internet |
|
COMPUTER SCIENCE |
|
CS
533 |
Information Retrieval |
Prof.
Michal Cutler |
Internet |
|
CS
555 |
Introduction
to Visual Information Processing
|
Prof.
LiJun Yin |
Internet |
|
CS
580Z |
Introduction
to the Mainframe: z/VM Basics |
Prof.
Merwyn Jones |
Internet |
| ELECTRICAL
AND COMPUTER ENGINEERING |
|
EECE 506
|
Mathematical Methods in EE
|
Prof. David Klotzkin |
Internet |
|
EECE
521 |
Digital
Signal Processing |
Prof. Mark
Fowler |
Internet |
|
EECE
530/474 |
Electro-Optics |
Prof. Vladimir
Nikulin |
Internet |
|
EECE 531 |
Electro-Magnetic Field Theory |
Prof. James
Constable |
Internet |
|
EECE
545 |
Digital
Communication Systems |
Prof. Edward
Li |
Internet |
|
EECE 552 |
Computer
Architecture Design |
Prof. Qing Wu |
Internet |
|
EECE
574 |
CMOS VLSI
Circuit Design Architectures
|
Prof. Qinru
Qiu |
Internet |
|
EECE 680B |
Convex
Optimization for EE & COE
|
Prof. Eva
Wu |
Internet |
| SYSTEMS
SCIENCE AND INDUSTRIAL ENGINEERING |
|
SSIE 501
|
Introduction to Systems Science
|
Prof. Eileen Way
|
Internet |
|
SSIE
505 |
Introduction
to Applied Probability and Statistics |
Prof.
Vilem Vychodil |
Internet |
|
SSIE
510 |
Enterprise Systems Engineering |
Prof. Krishnaswami Srihari |
Internet |
|
SSIE 525
|
Principles of Systems Engineering
|
Prof. Robert Emerson |
Internet |
|
SSIE 537 |
Industrial & Systems Engineering in Health Care |
Prof. Mohammad
Khasawneh |
Internet |
|
SSIE 562
|
Reliability
|
Prof. Susan Lu
|
Internet |
|
SSIE 615
|
Advanced Supply Chains
|
Prof. Nagen Nagarur |
Internet |
|
SSIE 631
|
Foundations of Neural Networks
|
Prof. Sarah
Lam |
Internet |
|
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|
|
BME 420/520 -
Advances Med Diag - Machine Intelligence,
Prof. Walker Land - 3 cr.
Develops and implements new
medical diagnostic algorithms using concepts derived from
statistical learning and computational intelligence theory.
Emphasis is placed on intelligent diagnosis derived from analog
and digital medical, tissue and microarray images, using second
opinion Computer Aided Diagnostic (CAD) software. Prerequisites:
ISE 261 or MATH 327, MATH 304.
Course Syllabus
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|
BME 525 - The Finite Element Method with Applications to
BioMedical Problems,
Prof. Jacques Beamont - 3 cr.
Review of the equations
governing conservation of mass, momentum, and energy, with
examples of application in Biology. A general presentation of
the finite element method for the solution of linear and
non-linear partial differential equations. Generation of a basis
function suitable for the approximation of the solution of a
differential equation. Formulation of elementary equations at
the basis of the numerical implementation. Formulation and
assembling of the matrix system. Numerical integration of the
elementary equations. Mesh nodes ordering for the optimization
of the matrix properties. Matrix storage schemes. Matrix
factorizations suitable for the numerical solution of various
finite element systems. Matrix pre-conditioning. The solution of
large sparse matrix systems produced by the application of the
finite element method. Explicit and implicit time integration.
The time discontinuous version of the finite element method.
Treatment of nonlinear systems. Parallel implementation with the
Message Passing Interface library. Prerequisites: Calculus I,
II, III, Linear algebra and Differential equations, or
equivalent to these courses.
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|
|
CS 533 - Information Retrieval, Prof. Michal Cutler - 3 cr,
Indexing and data
structures for storing and searching the index. Boolean,
statistical, inference nets and knowledge-based models.
Thesaurus construction. Query expansion. Natural
language and linguistic techniques. Evaluation.
Distributed information retrieval. Information integration
and fusion. Dissemination of information. Summeries,
themes and reading tours. Hypertext. Internet tools.
Intellligent agents. Digital libraries.
Prerequisite: CS 333 - Algorithms.
Course Syllabus
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|
CS 555 -
Introduction To Visual Information Processing,
Prof.
LiJun Yin
- 3 cr.
The
course focuses on fundamental topics, including visual
information acquisition, representation, description,
enhancement, restoration, transformations and compressions,
and reconstruction from projections. The second focus is on
Computer Science applications, including algorithms
developed in applications such as statistical and syntactic
pattern recognition, robotic vision, multimedia indexing,
visual data mining, and bio-informatics. Prerequisite: CS
333.
Course
Syllabus
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|
CS 580Z -
Introduction to the Mainframe: z/VM,
Prof.
Merwyn Jones
- 3 cr.
The
course will provide students with the background knowledge
and skills necessary to begin using the basic functions and
features of z/VM. Course Objectives: After
completing this course, the students will understand:
The Series z Hardware concept and the History of the
mainframe. Virtualization technology and how this is
exploited by z/VM. The operating systems that can run
as guest systems under z/VM. The different components
of z/VM. The z/VM control program and its commands.
The interactive environment under z/VM, CMS and its
commands. z/VM planning and administration. The
networking capabilities of z/VM and how to implement it.
The tools to monitor the performance of z/VM and guest
operating systems. The REXXTM programming
language and CMS Pipelines. The z/VM security
capabilities and issues. Prerequisite: CS
333.
Course
Syllabus
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|
| ELECTRICAL
AND COMPUTER ENGINEERING |
|
EECE 506 - Mathematical Methods in Electrical Engineering,
Prof. David Klotzkin - 3 cr.
Selected topics in the advanced
engineering mathematics, with special focus on their
electrical engineering applications. Topics include ordinary
and partial differential equations, Laplace transform, Fourier
transform, linear algebra, matrix theory, numerical methods,
complex analysis, optimization, probability and statistics.
Prerequisites: calculus and differential equations.
Course Syllabus
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EECE
521 -
Digital Signal Processing,
Prof. Mark Fowler -
3
cr.
Advanced
topics in digital signal processing Bandpass signals and
bandpass sampling, DFT-based processing, multi-rate
processing and filterbanks, andom signals and spectrum
estimation.
Prerequisites: EECE 402 - Signal Processing or
equivalent and MATH 327 or ISE 261 - or equivalent.
Course
Syllabus
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|
|
EECE 530/474 -
Electro-Optics, Prof. Vladimir Nikulin - 3 cr.
Electro-optic devices and systems. Blackbody, LED and
laser sources, photodetectors, modulators, fiber optics,
Fourier optics. Design of electro-optic systems.
Lecture portion meets with EECE 474.
Prerequisites: EECE 323 - Electromagnetics or equivalent.
Course
Syllabus
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|
EECE 531 -
Electro-Magnetic Field Theory, Prof. James
Constable - 3 cr.
|
EECE 545
- Digital Communication Systems,
Prof. Edward Li
- 3 cr.
Transmission of information in digital form; coding;
packets; error detection, correction; carriers; multipath
and intersymbol interference, spread spectrum.
Prerequisites: EECE 377 - Communications or equivalent.
Course
Syllabus
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EECE 552
- Computer Architecture Design,
Prof. Qing Wu
- 3 cr.
Computer architectures, virtual memory organization,
input-output, microprogramming, multiprocessor systems,
memory hierarchies, pipelined architecture, RISC machines,
fault-tolerant machines.
Prerequisites: EECE 352 - Computer Organization and
Microprocessors or equivalent.
Course
Syllabus - Fall 2007
Syllabus posted
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EECE 574 -
CMOS VLSI Circuit Design Architectures,
Prof. Qinru Qiu - 3 cr.
The MOS transistor, circuit characterization and performance
estimation. CMOS logic and structured design:
electrical design of logic circuits, clocking strategies,
and design rules. CMOS systems and RISC architectures. Prerequisites:
EECE 351 - Digital Logic Design or equivalent
Course
Syllabus
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|
EECE
680B -
Convex Optimization for EE & COE,
Prof. Eva Wu - 3 cr.
Basics of convex analysis. linear, quadratic, and
semi-definite programs, duality theory. Interior-point,
cutting-plane, and ellipsoid methods. Matlab-based tool for
convex optimization. Applications of convex optimization to
fields in electrical and computer engineering.
Course
Syllabus
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| SYSTEMS
SCIENCE AND INDUSTRIAL ENGINEERING |
|
SSIE
501 - Introduction to Systems Science,
Prof. Eileen Way - 3 cr.
Course will include the following:
a general characterization of systems science as a field of
study; intellectual roots, philosophical assumptions, and
historical development of the field; an overview of fundamental
systems concepts, principles, and laws; and a survey of
application areas of systems science and its implications for
other fields of study.
Course Syllabus
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SSIE
505 - Applied Probability and Statistics,
Prof. Vilem
Vychodil - 3 cr.
Basic
concepts in probability and statistics required in the modeling
of random processes and uncertainty. Bayes' formula.
Bayesian statistics, independent events; random variables
and their descriptive statistics; distribution functions;
Bernoulli, Binomial, Hyper geometric, poisson, normal, exponential,
gamma. Weibull and multinomial distributions; Chebyshev's
theorem; central limit theorem; joint distributions; hypothesis
testing; contingency tables, goodness of fit, non-parametric
statistics, regression and correlation. Prerequisite: one year of calculus.
Course
Syllabus
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|
SSIE 510 -
Enterprise Systems Engineering,
Prof. Krishnaswami Srihari
- 3 cr.
Manufacturing has become increasingly critical to standard
of living and competitive market position. Little has
really been published and analyzed as to the underlying
science of manufacturing. Course studies the
manufacturing literature and the manufacturing process and
investigates the underlying principles that govern
manufacturing.
Prerequisites: SSIE 505 - Introduction to Applied
Probability and Statistics or equivalent
Course
Syllabus
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|
SSIE
525 -
Principles of
Systems Engineering ,
Prof. Nadiye Erdil
- 3 cr.
Basic principles of systems engineering
applied in transforming client requirements into an
operational system. Topics cover the full system life cycle:
planning, integrated product/process development, system
architecture and design, modeling, requirements analysis,
development, integration, test and evaluation. Specialized
concepts involved in engineering complex systems are
reinforced through case studies and student exercised.
Prerequisite: graduate standing or consent of instructor.
Course
Syllabus
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|
SSIE
537 - Industrial and Systems Engineering in Health Care,
Prof. Mohammad Knasawneh - 3 CR.
Introduction to health systems
and health care delivery. The application of industrial and
systems engineering principles to continuous process
improvement in the health care domain will be studied.
Concepts that will be addressed will include, but not be
limited to, process mapping, optimization, scheduling, lean
and flexible systems, quality enhancement, simulation,
supply chain management, inventory control, and information
management. Prerequisite: Graduate standing in the
department or permission of the instructor
Course
Syllabus
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SSIE 562 - Reliability, Prof. Susan Lu -
3 cr.
Reliability networks, failure mode and effect analysis,
apportionment, fault trees and human reliability.
Prerequisites: SSIE 561 and probability and statistics, or
consent of department chair.
Course
Syllabus
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SSIE
615 - Advanced Supply Chains, Prof.
Nagan Nagarur -
3 cr. Course deals with
modeling of supply chains, concentrating on production and
operations. Quantitative models will be developed and
analyzed to study the benefits of information sharing, joint
planning, and coordination among the various components of a
supply chain. Strategic uses of information and various
strategies of supply chains, like appropriate contacts,
component commonality, and postponement will be covered. The
material will also include service industry, and designing
and managing globally dispersed entities. A major activity
would be students working in teams, and identifying relevant
problems and developing models to study them. Prerequisites:
SSIE 515 and/or SSIE 520 or instructor consent.
course
Syllabus
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SSIE 631 -
Foundations of Neural Networks,
Prof.
Sarah Lam -
3 cr.
Covers theory
and practical applications of artificial neural networks.
Neural networks are a broad class of computing mechanisms
with active research in many disciplines, including all
types of engineering, physics, psychology, biology,
mathematics, business, medicine and computer science.
Emphasizes the practical use of neural networks for
industrial problems such as pattern recognition, predictive
models, pattern classification, optimization and clustering.
Topics include learning rules, paradigms and validation.
Prerequisites: SSIE 505 or equivalent and SSIE 520.
course
Syllabus
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