PhD in Information Technology
IT Course Descriptions
IT course descriptions are also in the University Catalog Course listing at
IT 811/CS 811 Research Topics in Machine Learning and Influence (3:3:0).
Prerequisite: CS 680 and 681, or permission of instructor.
Presentation of unifying principles that underlie diverse methods,
paradigms, and approaches to machine earning and inference.
Reviews most known learning and inference systems, discusses strengths
and limitations, and suggests most appropriate areas of application.
Students get hands-on experience by experimenting with state-of-the-art
learning and inference systems, and working on projects tailored to research interests.
IT 821/SWE 821 Software Engineering Seminar (3:3:0).
Prerequisite: SWE 621.
Study of application of software engineering principles, design methods,
and support tools through real-life problems extracted from faculty and
industry projects. May be repeated with change in topic.
IT 822/CS 732 Software Maintenance and Reuse (3:3:0).
Prerequisites: CS/SWE 621 or equivalent, data structures,
principles of modern programming, and discrete mathematics;
or permission of instructor.
Perfective maintenance, reuse of software components and patterns,
evolving software systems, principles of object-oriented analysis
and development. Presents issues regarding technologies supporting
perfective software maintenance and reuse.
IT 823 Software for Critical Systems (3:3:0).
Prerequisite: SWE 620 and STAT 554.
Study of software for systems in which failure can be catastrophic.
Presents techniques to construct and analyze software for
critical applications and examination of inherent limitations of such
techniques, and interaction between techniques used during development
and behavior of software during operation. Topics include tolerance of
software faults, design redundancy, data redundancy, software safety,
formal methods, statistical testing, design for analyzability, and design
IT 824 Program Analysis for Software Testing (3:3:0).
Prerequisite: CS 540 or CS/SWE 637; or permission of instructor.
Different methods for analyzing software, primarily for purpose of testing.
Analysis techniques, specific algorithms, tools, and applications.
Goals are to explore current research issues, learn how to
build software analysis tools, and understand how these techniques
can be applied to software development activities.
Focuses on applications for testing software,
including automatic test data generation, object-oriented testing, and
testing client-server applications. Also considers analysis techniques
for other software-related activities such as maintenance, reuse,
object-oriented development, metrics, and optimization.
IT 825/SWE 825 Special Topics in Web-based Software (3:3:0).
Prerequisite: SWE 642.
Advanced topics in specifying, designing, modeling, developing, deploying, testing,
and maintaining software written as web applications and web services.
May be repeated with change in topic.
IT 844/ECE 749/CS 775 Pattern Recognition (3:3:0).
Prerequisite: ECE 549 or CS 580; or permission of instructor.
Covers Bayesian and statistical pattern recognition, neural network,
and statistical learning theory approaches for pattern recognition.
Topics include Bayes’ theorem, density approximation, multiplayer networks
and back propagation learning, pre-processing and feature extraction,
data and dimensionality reduction, function approximation and adaptive
kernel methods, clustering and self-selection, support vector machines,
support vector regression and support vector clustering, evolutionary
computation and genetic algorithms, and fuzzy systems. Emphasizes experimental
design, performance evaluation, and applications.
IT 860 Software Analysis and Design of Real-Time Systems (3:3:0).
Prerequisite: SWE 623.
Background for students who want to conduct research in software engineering
of real-time systems. Provides understanding of key real-time software system analysis,
design concepts and methods, and how they are used in developing large-scale,
real-time software systems. Also explores potential impact of emerging technologies.
Includes term project in design and analysis of complex, real-time software system.
IT 861 Distributed Database Management Systems (3:3:0).
Prerequisite: INFS 614 or equivalent.
Topics in include transaction management, concurrency control, deadlocks,
replicated database management, query processing reliability, and surveys
of commercial systems and research prototypes.
IT 862 Computer Security Models and Architectures (3:3:0).
Prerequisite: INFS 767 and 780.
Covers large-scale distributed systems, including cross-enterprise systems;
models for role-based and lattice-based access control; and delegated administration
with respect to formal and pragmatic criteria. Studies architectures to implement
these models based on public-key infrastructure, trusted servers, and other components.
IT 864 Scientific Databases (3:3:0).
Prerequisite: INFS 614.
Studies database support for scientific data management.
Covers requirements and properties of scientific databases;
data models for statistical and scientific databases; semantic and
object-oriented modeling of application domains; statistical database query languages
and query optimization; advanced logic query languages; and case studies
such as the human genome project and Earth orbiting satellite.
IT 865 Networks and Distributed Systems Security (3:3:0).
Prerequisite: INFS 612 or equivalent.
Detailed study of network and distributed systems security.
Reviews basic cryptography and threats and vulnerabilities in distributed systems.
Covers security services and confidentiality, authentication, integrity,
access control, nonrepudiation, and their integration in network protocols.
Topics also include key management, cryptographic protocols and their analysis;
access control, delegation, and revocation in distributed systems;
and security architectures, multilevel systems, and security management and monitoring.
IT 867 Intelligent Databases (3:3:0).
Prerequisite: INFS 760; or permission of instructor
Studies models and techniques that empower database systems with intelligent
and cooperative behavior, with emphasis on subjects such as knowledge-rich databases,
logic databases, epistemological queries, intentional answering, and knowledge discovery.
Topics include user interfaces, cooperative query interfaces, interactive query constructors,
graphical interfaces, and browsers; uncertainty representing, manipulating,
and retrieving uncertain, imprecise, or incomplete information; and formulating
and interpreting vague or incomplete queries.
IT 871 Statistical Data Mining (3:3:0).
Prerequisite: STAT 554 or 663; or permission of instructor.
Covers basic concepts, computational complexity, data preparation and
compression, databases and SQL, rule-based machine learning and probability,
density estimation, exploratory data analysis, cluster analysis and pattern
recognition, artificial neural networks, classification and regression trees,
correlation and nonparametric regression, time series, and visual data mining.
IT 875/CSI 803 Scientific and Statistical Visualization (3:3:0).
Prerequisite: STAT 554 or CS 651.
Presents visualization methods to provide new insights and intuition concerning
measurements of natural phenomena and scientific and mathematical models.
Presents case study examples from variety of disciplines. Topics include
human perception and cognition, introduction to graphics laboratory,
elements of graphing data, representation of space-time and vector variables,
representation of 3D and higher dimensional data, dynamicgraphical methods,
and virtual reality. Students required to work on visualization project.
Emphasizes software tools on Silicon Graphics workstation, but other workstations
and software may be used.
IT 950 Design and Management Aspects of Information Systems (3:3:0).
Prerequisite: INFS 790 or equivalent.
Impact of organizations and management of information systems (IS) and vice versa.
Topics include problems of introducing IS; effect on organizational, economic,
and political framework; participative design and new techniques for specification,
analysis, design, and implementation of IS; rapid prototyping and expert systems;
possible conflicts; methods in life-cycle management; and economic analysis.
IT 962 Advanced Topics in Computer Security (3:3:0).
Prerequisite: IT 862 or 865; or permission of instructor.
Current topics of advanced research. Content varies depending on faculty interests,
research developments, and student demand. Requires substantial student participation.
May include formal models for computer security, multilevel data models,
multilevel database management system architectures, secure concurrency control protocols,
distributed secure system architectures, integrity models and mechanisms, security policy,
and requirements analysis.