INFORMATION TECHNOLOGY
CARC 316
704-687-6374
http://www.coit.uncc.edu
Degree
Ph.D.
Coordinator
Dr. Zbigniew W. Ras
Graduate
Faculty
Gail-Joon Ahn, Assistant Professor
C. Michael Allen, Professor
M. Maureen Brown, Assistant Professor
Keh-Hsun Chen, Associate Professor
Bei-Tseng
W. Douglas Cooper, Professor
Christopher Craighead, Assistant Professor
Teresa Dahlberg, Assistant Professor
Essam El-Kwae, Assistant Professor
Jianping Fan, Assistant Professor
John Gretes, Professor
Mirsad Hadzikadic, Associate Professor
Alice Johnson, Assistant Professor
Moutaz Khouja, Associate Professor
Ram Kumar, Associate Professor
Junsheng Long, Associate Professor
Zbigniew Michalewicz, Professor
Taghi Mostafavi, Associate Professor
John O’Malley, Assistant Professor
Kayvan Najarian, Assistant Professor
Joseph Quinn, Professor
Zbigniew Ras, Professor
Stephanie Robbins, Associate Professor
Cem Saydam, Professor
Min Shin, Assistant Professor
Mike Smith, Assistant Professor
Antonis Stylianou, Associate Professor
Kalpathi Subramanian, Associate Professor
William J. Tolone, Assistant Professor
Robert Wilhelm, Associate Professor
A. Barry Wilkinson, Professor
Susan Winters, Assistant Professor
Xintao Wu, Assistant Professor
Wei-Ning Xiang, Associate Professor
Jing Xiao, Associate Professor
Yuliang Zheng, Professor
Adjuncts
Ilieva Ageenko, Assistant Professor
Bruce Anderson, Assistant Professor
Alicja Wieczorkowska, Assistant Professor
Program
of Study
The Ph.D. in Information Technology program is interdisciplinary and offers opportunities for students to develop advanced competencies in a number of IT related fields. Students, in cooperation with faculty advisors, design flexible programs of study tailored to address individual career goals.
Students who aspire to academic research can benefit from a strong research faculty of international stature and exposure to practical applications of their specialties. Others seeking employment in industry, commerce, or government are afforded the opportunity to participate in high-quality applied research. The program is also well suited to those interested in pursuing a teaching career. Students may familiarize themselves with recent advances in educational technology and can design a broad-based program of study.
Additional
Admission Requirements
Admission is competitive. Preference is given to applicants with strong credentials and appropriate undergraduate and/or professional preparation. Specific admission requirements for the program include:
1) A baccalaureate degree in a related field.
2) Excellent GRE or GMAT scores.
3) Working knowledge of two high level programming languages at the level achieved by a one semester college course in each language.
4) Evidence of skills at the level of a college course in at least 3 of the following areas:
Applicants whose native language is not English must score at least 550 in the Test of English as a Foreign Language (TOEFL). In addition, they will be required to take an English Proficiency Examination before beginning the first semester of study. Students who do not pass this examination must successfully complete ENGL 1100 (English as a Foreign Language) with a grade of B or higher.
Only complete applications will be considered. The applicant must state how each requirement is satisfied and include all supporting documentation.
Highly qualified individuals who do not meet all the prerequisites may be admitted with a clear agreement to complete them.
Further documentation to support the application may include: evidence of scholarly and creative activity, including publication list; awards; results in national or international contests related to information technology, and the like.
Degree Requirements
To earn the Ph.D., students must complete at least 72 post baccalaureate credit hours. This will include at least 54 hours of course work beyond the bachelor's degree and 18 hours of dissertation research credit. A limited amount of transfer credit is allowed (see below for details).
Students are expected to excel in all course work.
Graduation requirements mandate that students must achieve a minimum grade
point average of 3.0. Receiving more than two C grades or a grade of U in any
course will result in termination of the student's enrollment in the program.
In this case, the student may not take any further graduate course work without
being readmitted to the program. Readmission to the program requires approval
of the Dean of the
Requirements
for Admission to Ph.D. Candidacy
1) Appointment
of an Advisory Committee of at least four faculty members. The Advisory
Committee must be approved by the Doctoral Committee. In addition, the
2) Completion of the comprehensive examinations (see below).
3) Successful defense of the dissertation proposal.
Assistantships
Teaching and research assistantships are available on a competitive basis.
Transfer
Credit
In accordance with rules of the
To receive transfer credit, students must file a written
request and submit all necessary documentation to the Ph.D. coordinator. The
Ph.D. coordinator will evaluate the application and make recommendations to the
Doctoral Committee for final approval. In general, courses taken in Computer
Science, and many courses taken in a
Comprehensive
Examinations
IT Core Examination
All students must pass the core IT examination based on the Information Technology Core, which includes:
ITCS 8160 Database Systems Design and Management (3)
INFO 8100 Research Methodologies (3)
One of the following:
INFO 8200 Information Systems Development (3)
ITCS 8112 Software Systems Design and Implementation (3)
One of the following:
ITCS 8150 Intelligent Systems (3)
ITCS 8166 Computer Communications and Networks (3)
INFO 8300 Business Telecommunications (3)
The core examination is offered in fall and spring semesters. Students must notify the Ph.D. coordinator in writing during the first two weeks of the semester in which s/he wishes to take the exam.
The core examination may be taken at most twice, at different semesters. The second failure will result in termination of the student’s enrollment in the PhD program.
Area examination
Each student must pass an area examination. The area examination will be based on a body of courses, consisting of at least two related courses, chosen by the student and approved by both the student's Advisory Committee and the Doctoral Committee.
Students must notify the Ph.D. coordinator in writing during the first two weeks of the semester in which s/he wishes to take the exam. The notification must include the proposed set of courses the exam is to cover, and the faculty who have consented to draft the exam.
The area examination may be taken at most twice, at different semesters. The second failure will result in termination of the student's enrollment in the Ph.D. program.
Ph.D.
Candidacy
Each student must present and defend a Ph.D. dissertation proposal. The exam will be conducted by the student's Advisory Committee and will be open to the Ph.D. IT faculty and students. At the discretion of Advisory Committee, the defense may include questions that cover student's program of study and background knowledge in the area of the proposal.
A doctoral student advances to Ph.D. candidacy after the dissertation proposal has been successfully defended.
The second failed defense of a dissertation proposal will result in termination of the student's enrollment in the Ph.D. program.
Dissertation
The student must complete a research program approved by the
student's dissertation advisor that yields a high quality, original and
substantial piece of research. The Ph.D. dissertation describes this research
result. The dissertation defense, where the dissertation is presented, is open
to the public. A written copy of the dissertation must be made available to the
Ph.D. IT Doctoral Committee, to each member of the Advisory Committee, and to
the UNC Charlotte Library at least three weeks before the public defense. The
date of the public defense must be publicly announced at least three weeks
prior to the defense. The student must present the dissertation and defend it
in a manner accepted by the Advisory Committee. The dissertation will be graded
as pass/fail by the Advisory Committee and must be approved by the Dean of the
The failed defense of a dissertation will result in termination of the student's enrollment in the Ph.D. program.
Residency
Requirements
The student must satisfy the residency requirement of one continuous full-time year (i.e., two consecutive semesters with the student being enrolled for at least nine graduate credit hours in each semester) after being admitted to the Ph.D. degree program.
Tuition
Waivers
Out of state tuition waivers are available, on a competitive basis, to full time students with financial assistantships from UNC Charlotte.
Research
Opportunities/Experiences
Students may participate in many of the on-going research projects occurring at UNC Charlotte.
Courses In Information Technology - Doctoral
(Computer Science, Software and
Information Systems, Business Information Systems and Operations Management)
Students can also
select graduate level courses in other disciplines e.g.
ITCS 8010. Topics in Computer
Science. (3) Prerequisite: consent of the department. Topics in computer
science selected to supplement the regular course offerings. May be repeated
for credit as topics vary. (On demand)
ITCS 8050. Topics in Intelligent
Systems. (3) Prerequisite: consent of the department. Topics in
intelligent systems selected to supplement the regular course offerings. May be
repeated for credit as topics vary. (On
demand)
ITCS 8080. Topics in Computer Engineering. (3) Prerequisite: consent of the department Topics in computer engineering selected to supplement the regular course offerings. May be repeated for credit as topics vary. (On demand)
ITCS 8107. Formal Languages and Automata. (3) Prerequisites: one semester of discrete structures or consent of the department. Detailed study of abstract models for the syntax of programming languages and information processing devices. Languages and their representation; grammars; finite automata and regular sets; context-free grammars and pushdown automata; Chomsky Hierarchy; closure properties of families of languages; syntax analysis. (On demand)
ITCS 8110. Topics in Programming Languages and Compilers. (3) A continuation of material in ITCS 5128 with emphasis on advanced aspects of optimization, data flow analysis, and error discovery. (On demand)
ITCS 8111. Evolutionary Computation.
(3) Prerequisite: ITCS 8114 or consent of the department. General
introduction to optimization problems. Optimization techniques: hill climbing,
simulated annealing, evolution strategies, genetic algorithms. Evolution
programming techniques. (On demand)
ITCS 8112 Software Systems Design
and Implementation. (3) Prerequisite: consent of the department.
Introduction to the techniques involved in the planning and implementation of
large software systems. Emphasis on human interface aspects of systems.
Planning software projects; software design process; top-down design; modular
and structured design; management of software projects; testing of software;
software documentation; choosing a language for software system. This course is
cross listed with ITIS 8112. (Fall,
Spring)(Evenings)
ITCS 8114. Algorithms and Data
Structures. (3) Prerequisite: full graduate standing. Introduction to
techniques and structures used and useful in design of sophisticated software
systems. Records; arrays; linked lists; queues; stacks; trees; graphs; storage
management and garbage collection; recursive algorithms; searching and sorting;
graph algorithms; time and space complexity. (Odd, Fall) (Spring) (Evenings)
ITCS 8115. Advanced Topics in
Algorithms and Data Structures. (3) Prerequisite: ITCS 8114 or
equivalent. Continuation and extension of ITCS 6114. String matching;
seminumerical algorithms; probabilistic algorithms; parallel algorithms;
NP-completeness; computationally hard problems; approximation algorithms. (On demand)
ITCS 8120. Computer Graphics. (3)
Prerequisite: full graduate standing or consent of the department. Introduction
to the design and implementation of interactive graphics systems. Raster and
vector display systems, I/O devices; graphics primitives and their attributes;
raster algorithms and clipping; 2D/3D geometric transformations; 3D viewing and
projections; hierarchical and procedural models; surface representation; color
and lighting models; rendering algorithms; global illumination and texture
mapping. (Fall) (Evenings)
ITCS 8130 Advanced Computer Graphics. (3) Prerequisites: ITCS 8120 or equivalent, or consent of department. Implicit and parametric representation; cubic surfaces; advanced reflection models; global illumination models - ray tracing, radiosity; shadow algorithms, texture mapping; volumetric modeling and rendering techniques; animation; advanced modeling techniques; particle systems, fractals. (On demand)
ITCS 8132. Modeling and Analysis of
Communication Networks. (3)
Prerequisite: A course in communication networks, or consent of the department.
The objective of this course is to develop an understanding of modeling and
analysis techniques for communication systems and networks. The intent is to
enable the student to understand how to comparatively analyze the cost and
performance impact of network architecture and protocol design decisions.
Modeling techniques for analytical analysis, simulation based analysis, and
measurement based analysis will be presented. Concepts covered include
validation/verification of models, workload characterization, metric selection,
presentation and interpretation of results. A semester long analysis project
will be undertaken. (On demand)
ITCS 8134. Digital Image Processing. (3) Prerequisite: full graduate standing or consent of the department. Cross-listed as ECGR 6118. Image perception; image types/applications; image restoration and enhancement; edge/boundary detection; image transformation; image segmentation; statistical and syntactical pattern recognition; image information measures and compression. (Even, Spring) (Evenings)
ITCS 8140. Data Visualization. (3) Prerequisite: full graduate standing or consent of department. Emphasis on the methodology and application of data visualization to scientific and engineering data; data types and models; visualization methods; volume visualization; scalar, vector and tensor fields; multi-variate visualization; visualization systems and model; visualization applications; visualization software and hardware; research issues and future trends. (Odd, Spring)(Evenings)
ITCS 8144. Operating Systems Design. (3) Prerequisite: ITCS 8114 or consent of department. Introduction to features of a large-scale operating system with emphasis on resource-sharing environments. Computer system organization; resource management; multiprogramming; multi-processing; file systems; virtual machine concepts; protection and efficiency. (Even, Spring) (Evenings)
ITCS 8148. Advanced Object-Oriented
Systems. (3) Prerequisites: ITCS 8112 or equivalent. This course focuses
on issues related to the design, implementation, integration, and management of
large object-oriented systems. Topics include: object models, object modeling,
frameworks, persistent and distributed objects, and object-oriented databases.
This course is cross-listed with ITIS 8112 (Spring)(Alternate
Years)(Evenings)
ITCS 8150. Intelligent Systems. (3)
Prerequisites: full graduate standing or consent of the department. To
introduce core ideas in AI. Heuristic versus algorithmic methods; problem
solving; game playing and decision making; automatic theorem proving; pattern
recognition; adaptive learning; projects to illustrate theoretical concepts. (Fall) (Evenings)
ITCS 8153. Neural Networks. (3) Prerequisites: ITCS 8114 . Topics include: Basic notions and models of artificial neural nets; single layer neural classifiers; multilayer one-way neural nets; single layer feedback networks; neural models of associative memory; self organizing neural nets; translation between neural networks and knowledge bases; applications of neural networks (Even, Fall) (Evenings)
ITCS 8154. Heuristic Search. (3) Prerequisite: ITCS 8150. Heuristics and problem representation; heuristic-search procedures; formal properties and performance analysis of heuristic methods; game-searching strategies and heuristic programming; search with probabilities; knowledge-guided search. (On demand)
ITCS 8155. Knowledge-Based Systems.
(3) Prerequisite: ITCS 8162 or consent of the department. Knowledge
systems; knowledge discovery; association rules; query languages and
operational semantics; decision systems; cooperative and collaborative systems;
tree structured information systems; tree structured query languages; flexible
query answering; chase algorithm based on rules; local and global ontologies;
action rules; optimization problems for query answering systems. (Even, Spring) (Evenings)
ITCS 8156. Machine Learning. (3) Prerequisite: ITCS 8150 or consent of the department. Machine learning methods and techniques including: acquisition of declarative knowledge; organization of knowledge into new, more effective representations; development of new skills through instruction and practice; and discovery of new facts and theories through observation and experimentation. (On demand)
ITCS 8157. Visual Databases. (3)
Prerequisites: ITCS 8160 or equivalent. Topics include: Representation of
visual content, querying visual databases, content-based interactive browsing
and navigation, system architecture, similarity models, indexing visual
databases, data models and knowledge structures, image retrieval by similarity,
and video retrieval by content. (Even,
Fall)( Evenings)
ITCS 8158. Natural Language
Processing. (3) Prerequisite: ITCS 8150. Principles, methodologies, and
programming methods of natural language processing including foundations of
natural language understanding, namely: lexical, syntactic, and semantic
analysis, discourse integration, and pragmatic and morphological analysis. (On demand)
ITCS 8160. Database Systems. (3)
Prerequisite: ITCS 8114 or consent of the department. Introduction to
principles of database design, and survey of alternative database organizations
and structures. Logical database organization; schemas; subschemas; data
description languages; hierarchical, network, and relational databases;
database management systems; normal forms. (Fall,
Spring)(Evenings)
ITCS 8161. Advanced Topics in
Database Systems. (3) Prerequisite: ITCS 8160 or equivalent.
Continuation of ITCS 6160. Topics include deductive databases; semantic query
processing; intelligent and cooperative query languages; distributed databases;
active databases; heterogeneous databases, multimedia databases; data and
knowledge interchange; multidatabase systems; very large databases. (Odd, Spring)(Evenings)
ITCS 8162. Knowledge Discovery in Databases. (3) Prerequisite: ITCS 8160 or consent of the department. The entire knowledge discovery process is covered in this course. Topics include: setting up a problem, data preprocessing and warehousing, data mining in search for knowledge, knowledge evaluation, visualization and application in decision making. A broad range of systems, such as OLAP, LERS, DatalogicR+, C4.5, AQ15, Forty-Niner, CN2, QRAS, and discretization algorithms are covered. (Fall) (Evenings)
ITCS 8163. Data Warehousing. (3) Prerequisite: ITCS 8160 or equivalent. Topics include: use of data in discovery of knowledge and decision making; the limitations of relational databases and SQL queries; the warehouse data models: multidimensional, star, snowflake; architecture of data warehouse and the process of warehouse construction; data consolidation from various sources; optimization; technizues for data transformation and knowledge extraction; relations with enterprise modeling. (Odd, Spring) (Evenings)
ITCS 8164. Design and Implementation of Online Management Information Systems. (3) Prerequisites: ITCS 8114 or consent of the department. The fundamental concepts and philosophy of planning and implementing an on-line computer system. Characteristics of on-line systems; hardware requirements; modeling of on-line systems; performance measurement; language choice for on-line systems; organization techniques, security requirements; resource allocation. (On demand)
ITCS 8165. Coding and Information
Theory. (3) Prerequisite: knowledge of probability theory. Information
theory; coding theory; Shannon's theorem; Markov process; channel capacity;
data transmission codes; error correcting codes; data compression; data
encryption. (Odd, Fall)(Evenings)
ITCS 8166. Computer Communications
and Networks. (3) Introduction
to the concepts of communication networks; Types of networks; wired and
wireless media; communication architectures; network protocols; coding and
modulation; multiplexing and multiple access; error and flow control; routing;
Internet Protocols; transport protocols; Assignments include implementation and
analysis of network protocols (Fall)
(Evenings).
ITCS 8170. Logic for Artificial
Intelligence. (3) Prerequisite: ITCS 8150 or consent of the department.
Introduction to basic concepts of logic for artificial intelligence, including
declarative knowledge, inference, resolution, nonmonotonic reasoning,
induction, reasoning with uncertain beliefs, distributed information systems,
intelligent information systems, planning and intelligent- agent architecture. (On demand)
ITCS 8171. Logic Programming. (3) Prerequisite: ITCS 8150 or consent of the department. Prolog programming language; programming techniques in Prolog; foundations of logic programming including computability of Horn clause logic, completeness of resolution principle, complexity of unification algorithms, and verification of logic programs; principles of implementing logic programming systems; selected topics from applications of logic programming to expert systems, intelligent database systems, and/or natural language processing. (On demand)
ITCS 8175. Computability and
Complexity. (3) Prerequisite: consent of the department. Study of
computability, unsolvability, computational complexity. Concept of effective
computability; recursive functions; mathematical models of computation;
universal Turing machines; unsolvable problems; time and space complexity of
computations; NP-completeness problems; subrecursive hierarchies. (On demand)
ITCS 8181. Switching and Automata Theory. (3) Prerequisite: consent of the department. Topics include sets, relations, lattices, Boolean algebras; functional decomposition and symmetric functions; threshold logic; multiple-valued logic; fault detection and fault tolerant design; finite state machines, incompletely specified machines, minimization; state identification and fault detection experiments; finite state recognizers. (On demand)
ITCS 8182. Advanced Computer
Architecture. (3) Prerequisite: ITCS 5141. Survey of existing and
proposed architectures; pipelined, dataflow, restructurable, and supercomputer
architectures. Multicomputer and multi- processor architectures. Impact of VLSI
on architecture. (Odd, Fall) (Evenings)
ITCS 8183. Computer Arithmetic. (3) Prerequisite: consent of the department. Principles, architecture, and design of fast two operand adders; multioperand adders, standard multipliers, and dividers. Cellular array multipliers and dividers. Floating point processes, BCD, and excess three adders, multipliers, and dividers. (On demand)
ITCS 8184. Fault Tolerant Digital
Systems. (3) Prerequisite: ITCS 5141. Design and analysis of fault
tolerant digital systems including design techniques, qualitative and
quantitative methods of evaluation, and available fault tolerant digital
systems. (On demand)
ITCS 8186. Application Specifics
System Design and Simulation. (3) Prerequisite: ITCS 5141 or equivalent,
or consent of the department. Project oriented course on techniques and
methodology in design and development of special purpose systems valuable for
business, healthcare, and industrial community; course content include system
specifications, interface structure and data communication, interconnection
architecture, and techniques for testing and debugging. (Fall) (Even years)
ITCS 8220. Pattern Recognition. (3) Prerequisites: Graduate standing. Topics include: Pattern pre-processing and feature extraction (entropy minimization, orthogonal expansion, Fourier expansion, Karhunen-Loeve expansion, PCA); linear decision functions; orthogonal and non-orthogonal systems of functions; pattern classification by distance functions (Nearest Neighbor, K-means, ISODATA); pattern classification by likelihood functions (Bayesian classifiers, estimation of probability density function); trainable classifiers (LMSE, Perceptron, multi-layer perceptrons, fuzzy classifiers); stochastic processes; classification on categorical attributes. (Odd, Fall) (Evenings)
ITCS 8222. Biomedical Signal Processing. (3) Prerequisites: Graduate standing. Topics include: Fundamental techniques in processing, analysis, feature extraction, and classification of complex signals; origin and processing techniques for biomedical signals, including ECG, ENG, EEG, MEG, ERG, EMG, respiratory signals, blood sound, and pressure signals. (On demand)
ITCS 8224. Biomedical Image Processing. (3) Prerequisites: Graduate standing, and Math 2164 or its equivalent. Topics include: Review of image processing and pattern recognition (2-D Fourier transforms, 2-D Wavelet transform, denoising of medical images); origin and processing of X-ray images; CT images; MRI images; ultrasonic images; PET images; thermal images; electrical impedance images; cross-registration between images of different source; stereotactic neurosurgery; stereotactic radiosurgery/radiotherapy; robot-assisted surgery. (Odd, Spring) (Evenings)
ITCS 8267. Intelligent Information
Retrieval. (3) Prerequisites: ITCS 8114 or consent of the department.
Topics include: definition of the information retrieval problem, modeling the
information retrieval problem, evaluation of information retrieval, query
languages and operations, text processing, indexing and searching, parallel and
distributed information retrieval, user interface and visualization, multimedia
information retrieval, and information retrieval applications. (Even, Spring) (Evenings)
ITCS 8690. Computer Science Seminar. (3) Prerequisites: at least 18 graduate ITCS/ITIS hours and consent of department. Experience for the advanced Ph.D. student on current problems of computer design and application. (May be used by a student or small group of students to work with a professor on a topic of mutual interest. May be used to give a course on a topic announced in advance.) (On demand)
ITIS 8112. Software System Design and Implementation. (3) Prerequisite: consent of the department. Introduction to the techniques involved in the planning and implementation of large software systems. Emphasis on human interface aspects of systems. Planning software projects; software design process; top-down design; modular and structured design; management of software projects; testing of software; software documentation; choosing a language for software system. This course is cross listed with ITCS 8112. (Fall) (Spring) (Evenings).
ITIS 8148. Advanced Object-Oriented
Systems. (3) Prerequisites: ITIS 8112 or equivalent. This course focuses
on issues related to the design, implementation, integration, and management of
large object-oriented systems. Topics include: object models, object modeling,
frameworks, persistent and distributed objects, and object-oriented databases.
This course is cross-listed with ITCS 8112 (Spring)(Alternate
Years)(Evenings)
ITIS 8156. Computer-Aided
Instruction. (3) Prerequisite: consent of the department. History of
CAI; study of current CAI systems; development of man-machine dialogue;
programming tools for CAI; information structures for computer-oriented
learning. Advantages/disadvantages/costs of CAI. (On demand)
ITIS 8163. Data Warehousing. (3) Prerequisite: ITCS 8160 or equivalent. Topics include: use of data in discovery of knowledge and decision making; the limitations of relational databases and SQL queries; the warehouse data models: multidimensional, star, snowflake; architecture of data warehouse and the process of warehouse construction; data consolidation from various sources; optimization; technizues for data transformation and knowledge extraction; relations with enterprise modeling. This course is cross listed as ITCS 8163. (Odd, Spring) (Evenings)
ITIS 8164. Online-Info Systems. (3)
Prerequisites: ITCS 6114 or consent of the department. The fundamental concepts
and philosophy of planning and implementing an on-line computer system.
Characteristics of on-line systems; hardware requirements; modeling of on-line
systems; performance measurement; language choice for on-line systems;
organization techniques, security requirements; resource allocation. (On demand)
ITIS 8167. Network and Information
Security. (3) Prerequisite: ITCS 6166 or equivalent. This course
examines the issues related network and information security. Topics include
concepts, security attacks and risks, security architectures, security policy
management, security mechanisms, cryptographic algorithms, security standards, security
system interoperation and case studies of the current major security systems. (Fall) (Evening)
ITIS 8177. System Integration. (3)
Prerequisite: ITIS 5166 and ITIS 5160, or equivalents. This course examines the
issues related to system integration. Topics include: data integration,
business process integration, integration architecture, middlewares, system
security, and system management. (Fall)
(Evening)
ITIS 8200. Principles of Information
Security and Privacy. (3) Prerequisite: consent of the department.
Topics include security concepts and mechanisms; security technologies;
authentication mechanisms; mandatory and discretionary controls; basic
cryptography and its applications; intrusion detection and prevention;
information systems assurance; anonymity and privacy issues for information
systems. (Fall, Spring) (Evening)
ITIS 8210. Access Control and
Security Architecture. (3) Prerequisite: ITIS 8200. This course
discusses objectives, formal models, and mechanisms for access control; and
access control on commercial off-the-shelf (COTS) systems. This course also
examines the issues related to security architectures and technologies for
authorization. Topics include cryptographic infrastructure, distributed systems
security architectures, Internet security architectures, network security
architectures and e-commerce security architectures. (Spring)
(Evening)
ITIS 8220. Information and System
Assurance. (3) Prerequisites: ITIS 8200. This course examines the issues
related to information and system assurance. Topics include security policy,
security threats/vulnerabilities/risks/incidents, assurance requirement,
assurance class, evaluation methods and assurance maintenance. (On demand)
ITIS 8342. Information Technology
Project Management. (3) Prerequisites: consent of the department.
Introduce the student to problems associated with managing information
technology projects involving, particularly, integration of systems,
development of client-specific solutions, and project justification. The course
will move beyond the classic techniques of project management and integrate
communication software/systems, multi-site, multi-client facilities projects,
cultural issues involved with managing interdisciplinary teams, and the effect
of rapid technological obsolescence on project justification, funding and
continuance. (Spring)
ITIS 8362. Information Technology
Ethics, Policy, and Security. (3) Prerequisites: HADM 6152 or MBAD 6121
or MPAD 6120. Management of Information technology involves understanding the
broader issues of ethics, Policy and Security. The growth in Internet usage and
E-commerce require IT professionals to consider issues pertaining to data
protection, regulation, and appropriate use and dissemination of information.
The course is designed to be team-taught by professionals in the field. (Fall)
INFO 8100. Information Systems
Research Methodologies. (3) Prerequisites: Graduate standing or
permission of the instructor. A study of statistical and research methods used
in information systems research. (Fall)
INFO 8120. Advanced Research
Methodologies (3). Prerequisites: INFO 8100 or consent of the
department. A study of advanced research methods used in business
administration and management information systems research. (On demand)
INFO 8200. Business Information
Systems: Analysis, Design, and Management. (3) Prerequisites: MBAD 6121
or consent of the department. This course integrates real-world concerns in
developing business information systems with research issues. Major topics
include the organizational value of information systems, selecting and
justifying information systems projects, alternative systems development
methodologies, Object-Oriented analysis and design and UML, CORBA and
middleware, Component-based development, Outsourcing, and IS project
management. (Spring)
INFO 8300. Business Data Communications (3) Prerequisites: MBAD 6121 or
consent of the department. This course integrates real-world
concerns in developing business data communications networks with technical and
research issues. Major topics include the fundamentals of data communications,
the regulatory environment, the OSI and other models of data communications,
LAN and WAN functions, and distributed applications. (On demand)
ITSC 8880. Individual Study. (3) Prerequisites: consent of department. With the direction of a faculty member, students plan and implement appropriate objectives and learning activities to develop specific areas of expertise through research, reading, and individual projects. May be repeated for credit. (On demand)
ITSC 8991. Doctoral Dissertation
Research. (0-9) Individual investigation culminating in the preparation
and presentation of a doctoral dissertation. (Fall, Spring, Summer)
ITSC 9999. Doctoral Degree Graduate Residence. (1) (Fall, Spring, Summer)