STECH 443
704-687-6374
http://www.coit.uncc.edu
Degree
Ph.D.
Program
Director
Dr. Keh-Hsun Chen
Graduate
Faculty
Gail-Joon Ahn, Assistant Professor
Tiffany Barnes, Assistant Professor
Keh-Hsun Chen, Professor
Bei-Tseng
W. Douglas Cooper, Professor
Teresa Dahlberg, Associate Professor
Abdullah Dasci, Assistant Professor
Jianping Fan, Assistant Professor
Mirsad Hadzikadic, Associate Professor
Larry Hodges, Professor
Hoon Kang, Assistant Professor
Moutaz Khouja, Professor
Ram Kumar, Associate Professor
Seok-Won Lee, Assistant Professor
Zhaoyu Liu, Assistant Professor
Zbigniew Michalewicz, Professor
Taghi Mostafavi, Associate Professor
Kayvan Najarian, Assistant Professor
Baba Prasad, Assistant Professor
Anita Raja, Assistant Professor
Zbigniew Ras, Professor
William Ribarski, BoA Endowed Professor
Stephanie Robbins, Associate Professor
Cem Saydam, Professor
Min Shin, Assistant Professor
Mike Smith, Assistant Professor
Antonis Stylianou, Associate Professor
Chandrasekar Subramaniam, Assistant Professor
Kalpathi Subramanian, Associate Professor
William J. Tolone, Associate Professor
Yongge Wang, Assistant Professor
Yu Wang, Assistant Professor
Zachary Wartell, Visiting Assistant Professor
A. Barry Wilkinson, Professor
David Wilson, Assistant Professor
Susan Winter, Assistant Professor
Xintao Wu, Assistant Professor
Wei-Ning Xiang, Professor
Jing Xiao, Professor
Yuliang Zheng, Professor
Adjuncts
Ilieva Ageenko, Assistant Professor
Bruce Anderson, Assistant Professor
Alicja Wieczorkowska, Assistant Professor
PH.D. IN INFORMATION TECHNOLOGY
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. It is a truly multidisciplinary program staffed with multidisciplinary faculty. Faculty from Computer Science (http://www.cs.uncc.edu), Software & Information Systems (http://www.sis.uncc.edu), and Business Information Systems & Operations Management (http://www.belkcollege.uncc.edu/iom) Departments form its core. Students, in cooperation with faculty advisors, design flexible programs of study tailored to address individual career goals.
Students who aspire to academic research and teaching 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.
Admission
Requirements
Admission is competitive. Preference is given to applicants with strong credentials and appropriate academic and/or professional preparation. Specific admission requirements for the program include:
1) A baccalaureate degree.
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:
a. Statistics,
b. Differential and Integral Calculus,
c. Discrete Math.,
d. Linear Algebra.
5) Applicants whose native language is not English must score at least 557 (PBT) or 220 (CBT) 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.
6) A one-page essay that addresses the following:
a. the applicant’s motivation,
b. area(s) of research interest, and
c. specifically how the programming language and coursework requirements are satisfied.
7) Three letters of reference from professionals working in the applicant’s field of interest, at least two of which must be from faculty members.
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. Only applications that are complete by the deadline will be considered.
Highly qualified individuals who do not meet all the prerequisites may be admitted with a clear agreement to complete them.
Application
Deadlines
Application deadlines are in accordance with UNC Charlotte graduate school deadlines. However, to ensure full consideration for financial support, applications must be received by September 1st for spring admission and February 15 for fall admission.
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). In general, courses taken in the
Students are expected to excel in all course work.
Graduation requirements mandate that students must achieve a minimum grade
point average of 3.0 to graduate. Receiving more than two C grades or a grade
of U in any course will result in a suspension from the program. In this case,
the student may not take any further graduate course work without being
reinstated to the program. Reinstatement 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 for the Information Technology Doctoral Program (henceforth Doctoral
Committee). In addition, the
2) Completion of the comprehensive examinations (see below).
3) Successful defense of the dissertation proposal.
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 Program Director.
Comprehensive
Examinations
IT Core Examination
All students must pass the core IT examination based on the Information Technology Core, which includes:
INFO8100 Research Methodologies (3)
One of the following:
ITCS8160 Database Systems (3)
INFO8201 Data and Knowledge Management in Business (3)
One of the following:
INFO8202 Business Information Systems: Analysis, Design, and Management (3)
ITCS8112 Software Systems Design and Implementation (3)
One of the following:
ITCS8150 Intelligent Systems (3)
ITCS8166 Computer Communications and Networks (3)
INFO8204 Business Data Communications (3)
The core examination is offered in fall and spring semesters. Students must submit Core Exam registration form to the Program Director during the first two weeks of the semester in which they wish to take the exam.
The core examination may be taken twice in different semesters. A student who fails the core exam twice will be terminated from the Ph.D. 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 they wish 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 twice in 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 proposal defense 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 the 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
Each 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 and its
results. The dissertation defense is a public presentation. 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
A student who fails the defense of a dissertation twice will be terminated from the Ph.D. program.
Residency
Requirements
Each 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.
Assistantships
Teaching and research assistantships are available on a competitive basis.
Tuition
Waivers
Out-of-state tuition remissions and in-state tuition grants are available, on a competitive basis, to full time students with graduate 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
(ITCS), Software and Information Systems (ITIS), Business Information Systems
and Operations Management (INFO & OPER))
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. (Even, Spring) (Evenings)
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. (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; techniques 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 8226. Bioinformatics. (3) Prerequisites: Graduate standing. Topics include: Brief Review of molecular biology, proteins and their classifications, DNA, RNA, and using microarrays and gene chips for sequencing;
review of computational techniques for bioinformatics,
expectation maximization, Bayesian classifiers, dynamic programming,
information theory and entropy analysis, Markov chain models, and neural
networks; computational techniques for local and multiple sequence alignment;
application of Markov chains in finding genes; using information theory to
estimate binding sites, start Codon prediction; RNA
secondary structure prediction; computational techniques for protein function
prediction; Advanced signal processing techniques in feature extraction from
protein sequences. (On demand) (Evenings)
ITCS 8265. Advanced Topics in Knowledge Discovery in Databases. (3) Continuation and extension of ITCS 8162. Information visualization in data mining and knowledge discovery, predictive data mining, mining of multimedia sources, mining of unstructured data, distributed data mining, mining of Web data/information, mining complex types of data, mining of biotechnology data, applications and trends in data mining. (On demand)
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 8130. Software Requirements Engineering for Information Systems. (3) Pre-requisite: Full graduate standing, or consent of the Department. Introduction to requirement engineering methodologies. Topics include: requirements elicitation, specification, and validation; structural, informational, behavioral, security, privacy, and computer user interface requirements; scenario analysis; application of object-oriented methodologies in requirements gathering; spiral development models; risk management models; software engineering maturity model. (On demand)
ITIS 8140. Software Testing and Quality Assurance. (3) Prerequisite: ITIS 6112 or consent of the Department. Methods for evaluating software for correctness, and reliability including code inspections, program proofs and testing methodologies. Formal and informal proofs of correctness. Code inspections and their role in software verification. Unit and system testing techniques, testing tools and limitations of testing. Statistical testing, reliability models. Software engineering maturity model. (On demand)
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; techniques 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, middleware, 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 8230. Information Infrastructure Protection. (3) Prerequisite: 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) (Evening)
ITIS 8240. Applied Cryptography. (3) Prerequisite: Full graduate standing or consent of the department. This course provides students with an understanding of modern cryptographic techniques, algorithms and protocols that are of fundamental importance to the design and implementation of security critical applications. The course not only covers standard cryptographic techniques, but also exposes students to the latest advances in applied cryptography. Topics include secret and public key ciphers, stream ciphers, one-way hashing algorithms, authentication and identification, digital signatures, key establishment and management, secret sharing and data recovery, public key infrastructures, and efficient implementation. (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 8201. Data and Knowledge Management in Business. (3) Prerequisite: MBAD 6121 or consent of the department and admission to the Ph.D. program in IT. An overview of the business approach to identifying, modeling, retrieving, sharing, and evaluating an enterprise's data and knowledge assets. Covers the organizational, technological and management perspectives. (Fall)
INFO 8202. Business Information Systems: Analysis, Design, and Management. (3) Prerequisites: MBAD 6121 or consent of the department. Examination of managerial issues associated with the study of business processes and the development of supporting information systems. Emphasis on the application of appropriate methodologies, techniques, and tools to analyze, design, and implement business information systems. Study of relevant IS project management and quality assurance techniques. (Yearly)
INFO 8203. Information Systems Economics, Strategy and Policy. (3) Prerequisite: MBAD 6121 or consent of the Department and admission to the Ph.D. program in IT. This course examines a collection of topics that deal with the strategic use of information systems (IS). These topics include Business Value of IS, Network Economics, use of IS for competitive advantage, IS Planning and policy setting, IS evaluation, selection and sourcing. (Fall)
INFO 8204. Business Data Communications. (3) Prerequisites: MBAD 6121 or consent of the department. Examination of the information communication requirements of business environments, the fundamentals of communication technology, and the application of the technology for solving business problems. Emphasis on understanding communication technologies to assess needs, plan for the introduction of hardware and software, and manage these communication systems. (Yearly)
INFO 8700. Advanced Topics in MIS. (3) Prerequisites: Consent of the department. Topics in MIS selected to supplement the regular course offerings. May be repeated for credit as topics vary. (On demand)
INFO 8800. Information Systems Research Seminar. (3) Prerequisites: INFO 8100, or consent of the department. A study of current research areas in MIS. (On demand)
INFO 8900. Directed Individual Study in Business Information Systems. (3) Prerequisites: Directed individual study and in-depth analysis of a special area of MIS. The course may be used to satisfy up to six semester hours of graduate credit requirements in the Ph.D. in IT degree program and may be repeated for credit provided a different area of study is undertaken each time. Permission of a member of the doctoral faculty who would direct the study and permission of the department must be secured before registering for the course. (On demand)
OPER 8122. Technology Enhanced Decision Making. (3) Prerequisites: MBAD 5141 and MBAD 5142 or equivalents. An analytical approach to the management process. Generalized models for decision making with major emphasis on application of the scientific method to management problems. (On demand)
OPER 8208. Supply Chain Management. (3) Prerequisites: MBAD 6141
or consent of the Department. Supply
chain management is concerned with all of the activities performed from the
initial raw materials to the ultimate consumption of the finished product. From
a broad perspective, the course is designed to examine the major aspects of the
supply chain: the product flows; the information flows; and the relationships
among supply chain participants. The course content is interdisciplinary in
nature and will cover a variety of topics such as supply chain information
technologies, supply chain design, strategic alliances between supply chain
participants and supply chain initiatives. (On
Demand)
ITSC 8110. Introduction to Information Technology Research. (3) Prerequisites: Good standing in the IT PhD Program. Information Technology has a wide range of research areas encompassing the fields of Business Information Systems, Bioinformatics, Computer Science, and Software and Information Systems. This seminar is intended to give IT PhD students a sound understanding of the different research areas in Information Technology. The seminar is to be taken during the first year of studies and is intended to be the gateway to the fields within Information Technology and will enable students to select the fields matching their interests early in their studies. Through attending weekly in-depth research presentations from faculty in all participating units in the PhD IT program and conducting literature surveys in areas of interest, students are expected to gain the knowledge they need to identify the areas of interest for themselves. (Fall)
ITSC 8123. Applied Management Science. (3) Prerequisite; MBAD
6122. Mathematical model building aimed at integrating methods and
applications. Overview of mathematical programming in
practice and a series of projects implementing models in business and the
public sector. (On demand)
ITSC 8141. Operations Management. (3) Prerequisite: MBAD 5141 and MBAD 5142 or equivalents. Design, operation, and control of service and manufacturing systems. Emphasis on using analytical tools for problem solving in process analysis and re-engineering, work-force management, materials and inventory management, aggregate planning, total quality management, and others (Fall, Spring)
ITSC 8142. Quality and Manufacturing Management. (3) Prerequisite:
MBAD 6141. Current issues and advances in operations management including
just-in-time inventory management, total quality management, continuous
improvement, flexible manufacturing systems, computer
integrated manufacturing systems, technology evaluation and selection, and
operations strategy. (On demand)
ITSC 8699. Graduate Research Seminar (1)
Prerequisites: Good standing in the IT PhD Program. This seminar is intended to
expose IT PhD students to current research in Information Technology through
attending weekly research presentations by other students, IT faculty, and
invited speakers. Each student is expected to give one or more presentations
for the Graduate Research Seminar before graduation. Students must sign up for and received credit for the Graduate Research
Seminar every semester that they are in the IT Ph.D. Program until they are
admitted to Ph.D. candidacy. It is graded on Pass/No Credit basis. ITSC
8110 students should not register
for ITSC 8699 for the same semester. (Fall,
Spring)
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 8990 Pre-dissertation Research (1~6) Prerequisites: Good standing in the IT PhD Program. Students conduct research in information technology under the direction of one or more IT PhD faculty. A major goal of this course is to prepare the student for the Qualifying Examination. May be repeated for credit. (Fall, Spring)
ITSC 8991. Doctoral Dissertation Research. (1-9) 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)