Computer Science and Engineering

College of Engineering

 

Chair Fillia Makedon

 

Web www.cse.uta.edu

Email info@cse.uta.edu

Phone 817.272.3785

Fax 817.272.3784

 

300 Nedderman Hall

Degrees / Certificates

Master’s Degrees

Computer Engineering, M.S.

Computer Science, M.S.

Software Engineering, M.SWEN.

Doctoral Degrees

Computer Engineering, B.S. to Ph.D.

Computer Engineering, Ph.D.

Computer Science, B.S. to Ph.D.

Computer Science, Ph.D.

Mathematical Sciences, Computer Science, Ph.D.

Graduate Faculty

Professor

Ishfaq Ahmad

Upendranath Chakravarthy

Gautam Das

Sajal Das

Chris Ding

Ramez Elmasri

Farhad Kamangar

Mohan Kumar

David Kung

Fillia Makedon

Lynn Peterson

Roger Walker

Gergely Zaruba

Associate Professor

Vassilis Athitsos

Hao Che

Leonidas Fegaras

Jean Gao

Heng Huang

Manfred Huber

Yu Lei

Chengkai Li

Donggang Liu

Yonghe Liu

Bob Weems

Matthew Wright

Assistant Professor

Christoph Csallner

Junzhou Huang

Gian-Luca Mariottini

Senior Lecturer

Darin Brezeale

Bahram Khalili

David Levine

James Mike O’Dell

Graduate Advisors

Ramez Elmasri

Computer Engineering, B.S. to Ph.D.

Computer Engineering, M.S.

Computer Engineering, Ph.D.

Computer Science, B.S. to Ph.D.

Computer Science, M.S.

Computer Science, Ph.D.

Software Engineering, M.SWEN.

Leonidas Fegaras

Computer Engineering, B.S. to Ph.D.

Computer Engineering, M.S.

Computer Engineering, Ph.D.

Computer Science, B.S. to Ph.D.

Computer Science, M.S.

Computer Science, Ph.D.

Software Engineering, M.SWEN.

Bahram Khalili

Computer Engineering, B.S. to Ph.D.

Computer Engineering, M.S.

Computer Engineering, Ph.D.

Computer Science, B.S. to Ph.D.

Computer Science, M.S.

Computer Science, Ph.D.

Software Engineering, M.SWEN.

James Mike O’Dell

Computer Engineering, B.S. to Ph.D.

Computer Engineering, M.S.

Computer Engineering, Ph.D.

Computer Science, B.S. to Ph.D.

Computer Science, M.S.

Computer Science, Ph.D.

Software Engineering, M.SWEN.

Department Information

Courses

 

Department Information

Objective

Admission

Continuation

Degree Requirements

 

Objective

The purpose of the graduate programs in Computer Science and Computer Science and Engineering is to facilitate the student's continued professional and scholarly development. The Master of Science (M.S.) programs are designed to extend the student's knowledge and emphasize a particular area of concentration. The Master of Software Engineering (M.SW.Engr.) program is designed to provide the student with the opportunity for professional development in the software engineering field. Students who have completed a bachelor's degree in CS, CSE wishing to pursue a doctoral degree may apply for admission in the B.S. to Ph.D. track. The admission requirements to this highly competitive track are the same as those for "advanced admission" (see Special Admissions Programs). The Doctor of Philosophy (Ph.D.) programs are designed to prepare the student to conduct research and development in an area of concentration.

Typical areas of concentration include

  1. Computer Systems: parallel processing, quality-of-service and resource management in distributed systems, scheduling and load balancing for parallel and distributed systems, tools for parallel programming, performance evaluation, fault-tolerant computing, interconnection networks, multimedia systems, real-time systems, memory system design;
  2. Intelligent Systems: neural networks, machine learning, planning, scientific visualization, pattern recognition, natural language processing, multi-agent environments, decision support;
  3. Software Engineering: requirements engineering, incremental delivery, conceptual modeling, scenario-based techniques, formal specifications, object-oriented software engineering, design methodologies, software testing, software maintenance, software re-engineering, software processes, real-time systems;
  4. Database: temporal databases, object-oriented databases, database models and languages, distributed database systems, indexing and hashing techniques, conceptual modeling, data security, logic and databases, query optimization, relational design theory, user interfaces, data repositories.
  5. Communications: networks, wireless communication, distributed computing, mobile computing, multimedia systems.

 

Admission

The CSE graduate admission committee bases its decision for graduate admission on the following criteria (in no specific order):

  1. An overall GPA of 3.0 or higher in undergraduate coursework.
  2. A GPA of 3.2 or higher on CS/CSE related coursework in the last two years of undergraduate degree.
  3. Relevance of the student's degree (background) to the CSE curriculum.
  4. Rigor of the student's bachelor's degree. A four-year degree is considered more rigorous than a three-year degree.
  5. Reputation of the university/college that the student has received his/her previous degrees from.
  6. GRE General Test: Admitted students typically earn the following scores on the GRE
    1. GRE quantitative score of at least 700
    2. GRE verbal score of at least 400
    3. A sum of verbal and quantitative GRE scores (i.e. scores from parts 6a and 6b combined) of at least 1150 for MS and 1250 for Ph.D. applicants. An applicant can have a minimum score of 700 on the quantitative GRE or a minimum score of 400 on the verbal GRE, but not both. A passing score on the Fundamentals of Engineering (FE) exam is also given consideration.

    Applicants for the MS degree with (or completing in the near future) a BSCSE from UT Arlington and a GPA of at least 3.2 should contact the graduate advisor regarding a GRE waiver. Those with a GPA of at least 3.5 should contact the graduate advisor regarding nomination for Advanced Admission (i.e. admission without application and fee). The GRE waiver may be extended to include non-UT Arlington candidates that have undergraduate degrees in CS or CSE (with GPA of 3.2 or above) from reputable universities with an ABET accredited program or other select universities subject to graduate advisor's approval.

  7. For Ph.D. students, the following are optional. Meeting these criteria will improve both a student's chances of securing admission and receiving financial support.
    1. Publication in scholarly conferences/journals.
    2. A percentile of 80 score or higher on the Computer Science subject GRE.

The above criteria are used as follows in relevance to the three possible admission decisions, i.e., Unconditional Status; Probationary Status; and Denied.

  1. Unconditional Status: Applies to an applicant who meets the first six criteria above to a degree satisfactory to the graduate admissions committee.
  2. Probationary Status: Applies to an applicant who meets at least five of the six criteria to a degree satisfactory to the graduate admissions committee and whose record shows promise for success in the program or to an applicant who does not fulfill all the deficiency course requirements.
  3. Denied:Applies to an applicant who does not meet five of the first six criteria to a degree satisfactory to the graduate admissions committee.

Requirements for BS to PhD accelerated program

  1. An undergraduate degree in CS or CSE or Equivalent.
  2. An overall GPA of 3.0 or higher in undergraduate coursework.
  3. A 3.2 grade point average (on a 4.0 scale) on the last two years of undergraduate course-work. In particular, performance on CS/CSE related courses are emphasized.
  4. Rigor of the student's Bachelors degree. A three-year degree is not considered rigorous enough.
  5. Reputation of the University/College that the student has received his/her previous degrees from.
    1. GRE quantitative score - 700
    2. GRE verbal score - 400
    3. The department does not require the advanced computer science test. A passing score on the Engineering-in-Training (EIT) exam is also given consideration for admission decisions.
  6. A sum of verbal and quantitative scores of 1150 or more on the GRE* :
  7. (International Applicants)
    A Test of English as a Foreign Language (TOEFL) score - 230

 

Waiver of the Graduate Record Examination

Upon recommendation of the Graduate Advisor, outstanding UT Arlington graduates may qualify for waiver of the requirements for the Graduate Record Examination (GRE). To qualify, the applicant must meet the following minimum requirements:

  1. The student must have graduated from a commensurate bachelor's degree program at UT Arlington no more than three academic years prior to admission to the graduate program (as measured from the start of the semester for which admission is sought). A commensurate bachelor's degree program is one that is a normal feeder program for the master's degree program to which the student seeks admission. Undergraduate students in their final year of study are also eligible; in such cases, admission with the GRE waiver is contingent upon successful completion of the bachelor's degree.
    1. as calculated for admission to the Graduate School ;
    2. overall;
    3. in the major field; and
    4. in all upper-division work.
  2. The student's UT Arlington grade-point average must equal or exceed 3.0 in the following calculations:

Applicants qualifying for waiver of GRE who do not qualify for advanced admission, must comply with all other requirements for admission, i.e., submitting the application for admission, paying fees, providing official transcripts from other institutions, and meeting any requirements established by the admitting graduate program. The GRE waiver must be recommended by the Graduate Advisor at the time of admission. The waiver of GRE program applies to applicants for master's degree programs only. Some programs may require higher grade-point averages to qualify and some will not waive the GRE under any circumstances.

Additionally, some programs may waive the GRE requirement for non-UT Arlington graduates who seek admission as a master's student and meet qualifications listed in those programs' specific admission requirements. Such waivers are not offered by all graduate programs.

Fellowships

The basis for granting a Fellowship to a student will be as follows:

  • The student is admitted without provisional requirements.
  • Relative standing with respect to other qualified applicants.

 

Continuation

To fulfill its responsibility to graduate highly qualified professionals, the Department has established certain requirements that must be met by students continuing in the graduate programs. In addition to the requirements of the Graduate School listed elsewhere in the catalog, the Computer Science and Engineering Department has established additional requirements detailed in its Guide to Graduate Programs.

Degree Requirements

Master of Science in Computer Science - Thesis

The Master of Science in Computer Science degree program is designed to develop the scholarship and research skills of the student. Thirty-one credit hours, which include one orientation seminar credit and six thesis credits, are required.

Master of Science in Computer Science and Engineering - Thesis

The Master of Science in Computer Science and Engineering, which is intended for students with a baccalaureate degree in engineering, requires 31 credit hours of which one is orientation seminar and six are thesis credits, and is designed to develop the scholarship and research skills of the student.

Master of Science in Computer Science - Non Thesis

The Master of Science in Computer Science non-thesis options provide professional development in computer science. The structured option requires 37 credit hours of which one is orientation seminar.

Master of Science in Computer Science and Engineering

The Master of Science in Computer Science and Engineering non-thesis options are intended for students with an engineering baccalaureate degree. The structured option requires 37 credit hours of which one is orientation seminar.

B.S. to Ph.D. Track

The B.S. to Ph.D. track in Computer Science/Computer Science Engineering requires 30 credit hours with 21 hours of diagnostic requirements and nine hours of advanced research-oriented coursework. This is in addition to the Ph.D. requirements.

Ph.D. (Computer Science)

The Ph.D. in Computer Science continues the development of the student's research capability. Coursework selection in each student's program is designed to support the dissertation area selected by the student.

A minimum of two semesters of full-time study is required during the dissertation phase. There is no foreign language requirement.

Ph.D. (Computer Science and Engineering)

The Ph.D. in Computer Science and Engineering is available to students with a prior degree in engineering. It contains essentially the same requirements as the Ph.D. (Computer Science) degree except that it permits interdisciplinary research between Computer Science and one or more of the various engineering disciplines.

 

CS Courses

CS6352 – PERF OF COMPUTE

3 Lecture Hours  ·  0 Lab Hours

 

CS6359 – OBJ ORIENT DESI

3 Lecture Hours  ·  0 Lab Hours

 

CS6378 – ADV OPER SYS

3 Lecture Hours  ·  0 Lab Hours

 

CSE Courses

CSE5191 – INDIVIDUAL STUDY IN COMPUTER SCIENCE

1 Lecture Hour  ·  0 Lab Hours

Topics dealing with special problems in Computer Science on an individual instruction basis. May be repeated for credit.

 

CSE5194 – ORIENTATION SEMINAR

1 Lecture Hour  ·  0 Lab Hours

Presentation of computer science research by CSE faculty, students, and invited speakers. Preparation of program of work.

 

CSE5301 – DATA ANALYSIS & MODELING TECHNIQUES

3 Lecture Hours  ·  0 Lab Hours

Concepts and techniques for performing experiments and analyzing their results. Topics cover fundamental statistics, probability and data-representation concepts, interference through hypothesis testing, information theory, queuing models, and selected topics such as capacity planning and bottleneck analysis, clustering and classification, and hidden Markov models with computer science applications as examples.

 

CSE5306 – DISTRIBUTED SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Issues and challenges in distributed systems, including: communication, distributed processes, naming and name services, synchronization, consistency and replication, transactions, fault tolerance and recovery, security, distributed objects, and distributed file systems.

 

CSE5307 – PROGRAMMING LANGUAGE CONCEPTS

3 Lecture Hours  ·  0 Lab Hours

Study and evaluation of concepts in programming language for modern computer systems. Programming projects are selected from string-based, symbolic, algorithmic, and object-oriented languages.

 

CSE5311 – DESIGN AND ANALYSIS OF ALGORITHMS

3 Lecture Hours  ·  0 Lab Hours

Techniques for analyzing upper bounds for algorithms and lower bounds for problems. Problem areas include: sorting, data structures, graphs, dynamic programming, combinatorial algorithms, introduction to parallel models.

 

CSE5314 – COMPUTATIONAL COMPLEXITY

3 Lecture Hours  ·  0 Lab Hours

Sequential and parallel complexity classes (e.g., NP-complete and P-complete) and representative problems in languages, logic and graphs. Reduction techniques. Approximate solutions. Complexity hierarchies.

 

CSE5315 – NUMERICAL METHODS

3 Lecture Hours  ·  0 Lab Hours

Selected topics from the theory and practice of using automatic digital computers for approximating arithmetic operations, approximating functions, solving systems of linear and non-linear equations, and solving ordinary and partial differential equations.

 

CSE5316 – MODELING, ANALYSIS, AND SIMULATION OF COMPUTER SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Mathematical formalism and techniques used for computer system modeling and analysis. Reviews probability, transform theory, coding theory, and Petri nets. Topics may include knowledge based modeling, validation procedures, various simulation techniques for stochastic process and real-time distributed systems.

 

CSE5317 – DESIGN AND CONSTRUCTION OF COMPILERS

3 Lecture Hours  ·  0 Lab Hours

Review of programming language structures, translation, and storage allocation. Introduction to context-free grammars and their description. Design and construction of compilers including lexical analysis, parsing and code generation techniques. Error analysis and simple code optimizations will be introduced.

 

CSE5318 – APPLIED GRAPH THEORY AND COMBINATORICS

3 Lecture Hours  ·  0 Lab Hours

Connected and disconnected graphs; trees; graph planarity; Hamiltonian circuits and Euler tours; coloring; flow and graph optimization algorithms, fundamentals of combinatorics; generating functions and recurrence relations; inclusion-exclusion principle; applications in telecommunications; mobile computing, parallel processing and multiprocessor architectures.

 

CSE5319 – SPECIAL TOPICS IN THEORY & ALGORITHMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5320 – SPECIAL TOPICS IN SOFTWARE ENGINEERING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5321 – SOFTWARE TESTING

3 Lecture Hours  ·  0 Lab Hours

Study of software quality assurance, software testing process, methods, techniques and tools. Topics include formal review techniques, black box testing, white box testing, integration testing, acceptance testing, regression testing, performance testing, stress testing, and testing of object-oriented software. Prerequisite: CSE 5324 or concurrent enrollment.

 

CSE5322 – SOFTWARE DESIGN PATTERNS

3 Lecture Hours  ·  0 Lab Hours

Study and application of object-oriented software design patterns to software development and maintenance in the object-oriented paradigm. Prerequisite: CSE 5324 or concurrent enrollment.

 

CSE5323 – SOFTWARE ENGINEERING PROCESSES

3 Lecture Hours  ·  0 Lab Hours

Introduces software lifecycle models, process disciplines, project management concepts, and applies them by mastering the Personal Software Process (PSP).

 

CSE5324 – SOFTWARE ENGINEERING: ANALYSIS, DESIGN, AND TESTING

3 Lecture Hours  ·  0 Lab Hours

Motivations, principles, and goals of software engineering; technical aspects of software projects, including: review of structured analysis and structured design, emphasis on object-oriented methods of requirements analysis and specification, design, and implementation; software testing concepts; team project.

 

CSE5325 – SOFTWARE ENGINEERING: MANAGEMENT, MAINTENANCE, AND QUALITY ASSURANCE

3 Lecture Hours  ·  0 Lab Hours

Issues and principles for software management; managerial and support aspects of software projects, including: processes, estimation techniques, planning and scheduling, risk analysis, metrics, and quality assurance. Other topics include: configuration management, verification and validation, and maintenance; team project. Prerequisite: CSE 5324 or concurrent enrollment.

 

CSE5326 – REAL-TIME SOFTWARE DESIGN

3 Lecture Hours  ·  0 Lab Hours

Specification, design, and analysis of real-time systems including real-time logics and decidability of real-time conditions; real-time scheduling approaches, system requirement specification; procedural and object-oriented methods; specialized analysis techniques for distributed and for control applications; team project. Prerequisite: CSE 5324 or concurrent enrollment.

 

CSE5327 – TELECOMMUNICATIONS SOFTWARE DEVELOPMENT

3 Lecture Hours  ·  0 Lab Hours

General understanding and classification of telecommunications systems and applications. Issues relating to the analysis, design, implementation, and testing of telecommunications software. Prerequisite: CSE 5324 and 5344.

 

CSE5328 – SOFTWARE ENGINEERING TEAM PROJECT I

3 Lecture Hours  ·  0 Lab Hours

Apply the knowledge and skills gained in other software engineering courses to synthesize a solution to a significant and realistic software development team project. Participate in activities including: proposal writing, problem analysis, software requirements specification, project planning, software design, implementation, software quality assurance, software testing, integration, and demonstration. Required for and open only to Master of Software Engineering degree candidates. Prerequisite: one of 5321, 5322, 5325.

 

CSE5329 – SOFTWARE ENGINEERING TEAM PROJECT II

3 Lecture Hours  ·  0 Lab Hours

Apply the knowledge and skills gained in other software engineering courses to synthesize a solution to a significant and realistic software development team project. Participate in activities including: proposal writing, problem analysis, software requirements specification, project planning, software design, implementation, software quality assurance, software testing, integration, and demonstration. Required for and open only to Master of Software Engineering degree candidates. Prerequisite: one of 5321, 5322, 5325.

 

CSE5330 – DATABASE SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Database system architecture; management and analysis of files, indexing, hashing, and B-trees; the relational model and algebra; the SQL database language; database programming techniques, database design using Entry-Relationship, extended E-R, and UML modeling; basics of normalization. Introduction to database security, query processing and transaction management. Prerequisite: CSE 2320.

 

CSE5331 – DBMS MODELS AND IMPLEMENTATION TECHNIQUES

3 Lecture Hours  ·  0 Lab Hours

DBMS system implementation techniques, including query optimization, transaction processing, concurrency control, buffer management and recovery. Object-oriented, object-relational and XML databases. Introduction to advanced database models, such as active, distributed, temporal, spatial and data warehousing. Prerequisite: CSE 3330/CSE 5330, or consent of instructor.

 

CSE5333 – DISTRIBUTED AND PARALLEL DATABASES

3 Lecture Hours  ·  0 Lab Hours

Distributed database system architecture and design, distributed transaction management and database interoperability; distributed query processing; parallel database architectures and techniques; and parallel algorithms for database operations. Prerequisite: CSE 5330 or consent of instructor.

 

CSE5334 – DATA MINING

3 Lecture Hours  ·  0 Lab Hours

Preparing data for mining, using preprocessing, data warehouses and OLAP; data mining primitives, languages and system architecture; data mining techniques including association rule mining, classification/prediction and cluster analysis.

 

CSE5335 – WEB DATA MANAGEMENT & XML

3 Lecture Hours  ·  0 Lab Hours

XML has become an important standardization for data representation and information exchange among Internet co-operative applications. This course provides an in depth study of the area of web data management with an emphasis on XML standards and technologies. The course primarily covers the state of the art in designing and building web applications and services, primarily focusing on issues and challenges that revolve around the management and processing of XML data. Topics include: Web programming, XML standards, XML query languages, native XML storage management, XML on relational databases, XML indexing, Web Services, metadata management with RDF, and Semantic Web. Prerequisite: CSE 3330/CSE 5330, or consent of instructor.

 

CSE5336 – STREAM DATA MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

This course provides a study of special-purpose data management systems for processing stream data generated by sensors, RFIDs (Radio Frequency Identifications), and other ubiquitous devices. Topics include: Analysis of the differences between processing and managing stored data and stream data (including events). Using sliding windows to unblock blocking operations for continuous queries. Approximation techniques for continuous aggregation queries. Quality of Service (QoS) requirements of stream and complex event processing applications and their impact on various aspects of processing. Modeling continuous queries, scheduling strategies for (multiple) continuous queries, adaptive query plans, and load shedding to trade-off QoS requirements. Design and implementation of stream processing systems. Prerequisite: CSE 3330 or CSE 5330, or consent of instructor.

 

CSE5339 – SPECIAL TOPICS IN DATABASE SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5343 – REAL-TIME DATA ACQUISITION AND CONTROL SYSTEMS

2 Lecture Hours  ·  3 Lab Hours

Advanced course in design of microcomputer-based systems. Emphasis is on the application of state-of-the-art microprocessors, microcomputers, and other LSI and VLSI components to real-time, interactive, and/or embedded systems. Prerequisite: CSE 5442 or consent of instructor.

 

CSE5344 – COMPUTER NETWORKS

3 Lecture Hours  ·  0 Lab Hours

Study of computer network architectures, protocols, and interfaces. The OSI reference model and the Internet architecture will be discussed. Networking techniques such as multiple access, packet/cell switching, and internetworking will be studied. Discussion will also include end-to-end protocols, congestion control, high-speed networking, and network management. Emphasis will be on Internet and ATM. Prerequisite: CSE 3320 or consent of instructor.

 

CSE5345 – FUNDAMENTALS OF WIRELESS NETWORKS

3 Lecture Hours  ·  0 Lab Hours

Fundamentals of wireless networks, including wireless channels, coding and modulation, cellular architectures and protocols, multiple division techniques, multiple access control, wireless LAN/PAN, mobile IP and wireless internet, TCP over wireless, ad-hoc networks, sensor networks. Prerequisite: CSE 4344/5344 or equivalent course.

 

CSE5346 – NETWORKS II

3 Lecture Hours  ·  0 Lab Hours

This course provides an in depth study and comparison of the two primary networking paradigms, Internet/broadcast and switched, using two technologies, IPv6 and ATM, as representative examples. The course is implementation-oriented, focusing on issues such as routing, broadcast, multicast, mobility, network configuration, and quality of service. Prerequisite: CSE 5344.

 

CSE5347 – TELECOMMUNICATION NETWORKS DESIGN

3 Lecture Hours  ·  0 Lab Hours

A study of advanced telecommunication systems and networks, internet working functions, networking architectures and their convergence towards an IP/Ethernet centric architecture. Prerequisite: CSE 4344, CSE 5344, or CSE 5346.

 

CSE5348 – MULTIMEDIA SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Representations and techniques for processing, communicating, and compression of text, audio, graphics, and video in real time. Project integrating these topics.Prerequisite: CSE 3320.

 

CSE5349 – SPECIAL TOPICS IN NETWORKING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5350 – COMPUTER ARCHITECTURE II

3 Lecture Hours  ·  0 Lab Hours

A study of advanced uniprocessor and basic multiprocessor systems. Topics may include memory management systems, pipelined processors, array and vector processors, and introduction to architecture of multiprocessor systems. Prerequisite: CSE 3322 or consent of instructor.

 

CSE5351 – PARALLEL PROCESSING

3 Lecture Hours  ·  0 Lab Hours

Covers the theory and practice of parallel processing. Theoretical topics include: abstract models and algorithms for shared memory computation (PRAM); algorithms for various topologies such as meshes and hypercubes; efficiency and speedup analysis. Problem areas include data structures, numerical methods, graphs, combinatorics. Practical topics include synchronization, routing, scheduling, parallelizing serial computations, programming languages. Includes programming exercises using one or more concurrent programming languages, on one or more parallel computers. Prerequisite: CSE 3320 or consent of instructor.

 

CSE5353 – DISTRIBUTED COMPUTING

3 Lecture Hours  ·  0 Lab Hours

Programming languages, support components, coordination models, and fundamental algorithms for distributed and clustered systems. Prerequisite: CSE 5306.

 

CSE5355 – COMPUTER SYSTEM PERFORMANCE EVALUATION

3 Lecture Hours  ·  0 Lab Hours

Queueing network models and simulation for studying the performance of overall computer systems. Theory and applications of Markov process, Random Walk, Renewal Process, and Birth and Death Process. Topics also include bottleneck identification, capacity planning, hardware selection and upgrade, and performance tuning. Data collection, presentation and interpretation, benchmarking and the proper choice of performance metrics will be emphasized. Prerequisite: CSE 3320.

 

CSE5359 – SPECIAL TOPICS IN SYSTEMS & ARCHITECTURE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5360 – ARTIFICIAL INTELLIGENCE I

3 Lecture Hours  ·  0 Lab Hours

Introduction to the methods, concepts and applications of artificial intelligence, including knowledge representation, search, theorem proving, planning, natural language processing, and study of AI programming languages. Prerequisite: CSE 2320 and 3315, or consent of instructor.

 

CSE5361 – ARTIFICIAL INTELLIGENCE II

3 Lecture Hours  ·  0 Lab Hours

Continuation of artificial intelligence methods and techniques, including uncertainty reasoning, machine learning, perception, and advanced topics in knowledge representation, search and planning. Emphasis on design and implementation of AI solutions. Prerequisite: CSE 5360 or consent of instructor.

 

CSE5362 – SOCIAL NETWORKS AND SEARCH ENGINES

3 Lecture Hours  ·  0 Lab Hours

Social networks, Search Engines, Recommendation systems, Question & Answering systems are web-enabled Information Technology main stream. This course covers the foundations of these technology including text/query processing, web content analysis, basic graph theory, random walk, PageRank, power law distribution, random graphs, small world, growth models, and network diffusion. Prerequisite: CSE 5311.

 

CSE5364 – ROBOTICS

2 Lecture Hours  ·  3 Lab Hours

An introduction to robotics and the design and programming of autonomous robot systems. Topics include basic kinematics, dynamics, and control, as well as sensors, knowledge representation, and programming techniques. Coursework includes individual and group projects involving the building and programming of simulated and real robots. Prerequisite: CSE 2320 and CSE 3442.

 

CSE5365 – COMPUTER GRAPHICS

3 Lecture Hours  ·  0 Lab Hours

Input/output devices and programming techniques suitable for the visual representation of data and images. Prerequisite: CSE 1320, analytic geometry and linear algebra, or consent of instructor.

 

CSE5366 – DIGITAL SIGNAL PROCESSING

3 Lecture Hours  ·  0 Lab Hours

Introduction to principles and applications of digital signal processing. Topics include: analysis of signals and systems, Fourier and Z transforms, digital filter design techniques (FIR and IIR), autoregressive (AR) and autoregressive moving average (ARMA) modeling. Applications to science and engineering include: financial predictions and processing of digital music. Laboratory work includes some programming and use of high quality library routines and packages such as Mathematica, Matlab. Prerequisite: CSE 1320 and consent of Graduate Advisor.

 

CSE5367 – PATTERN RECOGNITION

3 Lecture Hours  ·  0 Lab Hours

Principles and various approaches of pattern recognition processes, including Bayesian classification, parametric/non-parametric classifier design, feature extraction for signal representation, and techniques for classification and clustering. Current issues in pattern recognition research will also be examine. Prerequisite: CSE 2320 , MATH 3313.

 

CSE5368 – NEURAL NETWORKS

3 Lecture Hours  ·  0 Lab Hours

Theoretical principles of neurocomputing. Learning algorithms, information capacity, and mapping properties of feedforward and recurrent networks. Different neural network models will be implemented and their practical applications discussed. Prerequisite: CSE 1320 and calculus II, or consent of instructor.

 

CSE5369 – SPECIAL TOPICS IN INTELLIGENT SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5370 – BIOINFORMATICS

3 Lecture Hours  ·  0 Lab Hours

Basic biology of genome and common laboratory techniques Overview of discrete probability theory, random variables and processes. Issues in genome mapping, sequencing and analysis: sequence alignments and alignment algorithms; genomic databases and information access; structure and features of DNA sequences. Techniques in contemporary biotechnology, including proteomics and gene expression analysis using microarray chips. Prerequisite: CSE 5311 or consent of instructor.

 

CSE5379 – SPECIAL TOPICS IN BIOINFORMATICS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5380 – INFORMATION SECURITY 1

3 Lecture Hours  ·  1 Lab Hour

Hands-on introduction to the basics of security. Includes system security, buffer overflows, a high-level overview of cryptography, firewalls and IDS/IPS, malware, penetration testing, forensics, and system administration. Prerequisite: CSE 3320 or consent of instructor.

 

CSE5381 – INFORMATION SECURITY 2

3 Lecture Hours  ·  1 Lab Hour

Deeper study of the fundamentals of security, including symmetric key cryptography, public key cryptography, cryptographic protocols, malware design, network attacks and defenses, data security, privacy, and wireless security. Prerequisite: CSE 5380 and CSE 4344 or consent of instructor.

 

CSE5382 – SECURE PROGRAMMING

3 Lecture Hours  ·  0 Lab Hours

This course is an introduction to methods of secure software design and development for upper-level undergraduate students and graduate students. Students will learn about the major security problems found in software today. Using this knowledge, they will work in teams to find these bugs in software, fix the bugs, and design software so that it has fewer security problems. Static analysis tools will be a core part of the class, but students will also be exposed to black box testing tools. Topics will include input validation, buffer overflow prevention, error handling, web application issues, and XML. Prerequisites: CSE 3310 and CSE 3320, or equivalent.

 

CSE5388 – SPECIAL TOPICS IN INFORMATION SECURITY

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5389 – SPECIAL TOPICS IN MULTIMEDIA, GRAPHICS, & IMAGE PROCESSING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE5391 – INDIVIDUAL STUDY IN COMPUTER SCIENCE

3 Lecture Hours  ·  0 Lab Hours

Topics dealing with special problems in Computer Science on an individual instruction basis. May be repeated for credit.

 

CSE5392 – TOPICS IN COMPUTER SCIENCE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when the topics vary.

 

CSE5393 – DIRECTED STUDY IN COMPUTER SCIENCE

3 Lecture Hours  ·  0 Lab Hours

 

CSE5394 – MASTER'S PROJECT I

3 Lecture Hours  ·  0 Lab Hours

 

CSE5395 – MASTER'S PROJECT II

3 Lecture Hours  ·  0 Lab Hours

 

CSE5398 – MASTER'S THESIS I

3 Lecture Hours  ·  0 Lab Hours

Preliminary research effort for the master's thesis, including problem definition and literature search, along with identification of resources, milestones, examining committee members, and external publication venue. Graded F, R.

 

CSE5442 – EMBEDDED COMPUTER SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Design of micro computer-based systems; microcomputer programming, component and system architectures, memory interfacing, parallel and serial I/O interfacing, A/D and D/A conversion, and typical applications. Prerequisite: CSE 3322 or consent of instructor.

 

CSE5698 – MASTER'S THESIS II

6 Lecture Hours  ·  0 Lab Hours

Completion of tasks in support of the thesis defined in Master's Thesis I, including oral defense of the written documents. Prerequisite: CSE 5398. Graded F, R, P.

 

CSE6197 – RESEARCH IN COMPUTER SCIENCE

1 Lecture Hour  ·  0 Lab Hours

Individually supervised research projects.

 

CSE6297 – RESEARCH IN COMPUTER SCIENCE

2 Lecture Hours  ·  0 Lab Hours

Individually supervised research projects.

 

CSE6306 – ADVANCED TOPICS IN OPERATING SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5306 or consent of instructor.

 

CSE6311 – ADVANCED COMPUTATIONAL MODELS AND ALGORITHMS

3 Lecture Hours  ·  0 Lab Hours

This course aims at exploring advanced computation models, theory and advanced algorithm design and analysis techniques that have broad applicability in solving real-life problems in cross-disciplinary areas such as the Internet computing, Web search engines, data mining, bioinformatics, wireless mobile and sensor networks, dynamic resource management, distributed computing, and social networking. Topics include: Theory of NP-completeness; Equivalence of Machine Models; Lower Complexity Bounds; Randomized and Probabilistic Algorithms; Game-theoretic and Information-theoretic Models; Approximation and Optimization Techniques. Prerequisite: CSE 5311 or consent of instructor.

 

CSE6314 – ADVANCED TOPICS IN THEORETICAL COMPUTER SCIENCE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5314 or consent of instructor.

 

CSE6319 – SPECIAL TOPICS IN ADVANCED THEORY AND ALGORITHMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated when topics vary.

 

CSE6323 – AUTOMATED SOFTWARE ENGINEERING

3 Lecture Hours  ·  0 Lab Hours

Study of foundations, techniques and tools for automating software processes and methodologies including analysis, design, implementation, testing, and maintenance of large software systems. Prerequisite: CSE 5324 or consent of instructor.

 

CSE6324 – ADVANCED TOPICS IN SOFTWARE ENGINEERING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5324 or consent of instructor.

 

CSE6329 – SPECIAL TOPICS IN ADVANCED SOFTWARE ENGINEERING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary. CSE 5324 or consent of instructor.

 

CSE6331 – ADVANCED TOPICS IN DATABASE SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5332 and consent of instructor.

 

CSE6332 – TECHNIQUES FOR MULTIMEDIA DATABASES

3 Lecture Hours  ·  0 Lab Hours

Overview of data types, formats and compression techniques for audio, video and image data; operating systems techniques for multimedia; video delivery techniques; indexing and retrieval techniques; content-based video modeling; multimedia data on the Web. Prerequisite: CSE 5331 or consent of instrucor.

 

CSE6339 – SPECIAL TOPICS IN ADVANCED DATABASE SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6344 – ADVANCED TOPICS IN COMMUNICATION NETWORKS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5346 or consent of instructor.

 

CSE6345 – PERVASIVE COMPUTING & COMMUNICATIONS

3 Lecture Hours  ·  0 Lab Hours

Issues and challenges in pervasive computing environments: interoperability and heterogeneity; location-awareness and mobility; transparency and proactivity; trust, authentication and security, information acquisition and dissemination in mobile and pervasive systems. Contest-aware computing. Ad-hoc, sensor and mobile P2P systems in pervasive computing. Case studies. Prerequisite: Introductory courses in Networks, Algorithms and Operating Systems: e.g., CSE 5344, CSE 5311, and CSE 5306, or consent of instructor.

 

CSE6347 – ADVANCED WIRELESS NETWORKS & MOBILE COMPUTING

3 Lecture Hours  ·  0 Lab Hours

Wireless architectures and protocols (e.g., GSM, CDMA); channel assignment and resource allocation; mobility and location management; mobile data management; wireless data networking and multimedia; call admission control and QoS provisioning; cross layer optimization, performance modeling. Prerequisite: CSE 5345 and CSE 5330.

 

CSE6348 – ADVANCES IN SENSOR NETWORKS

3 Lecture Hours  ·  0 Lab Hours

Covers application and architecture of wireless sensor networks. Topics include platforms, routing, coverage, MAC, transport layer, data storage, query, and in-network processing. Prerequisite: CSE 5345 or equivalent course.

 

CSE6349 – SPECIAL TOPICS IN ADVANCED NETWORKING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6350 – ADVANCED TOPICS IN COMPUTER ARCHITECTURE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5350 and consent of instructor.

 

CSE6351 – TOPICS IN PARALLEL AND DISTRIBUTED COMPUTING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics change. Prerequisite: CSE 5350, 5351, or consent of instructor.

 

CSE6352 – FAULT-TOLERANT COMPUTING

3 Lecture Hours  ·  0 Lab Hours

Topics in reliable and fault-tolerant computing. May be repeated for credit when topics change. Prerequisite: CSE 5350 and consent of instructor.

 

CSE6359 – SPECIAL TOPICS IN ADVANCED SYSTEMS & ARCHITECTURE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6362 – ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when the topic changes. Prerequisite: CSE 5361 and consent of instructor.

 

CSE6363 – MACHINE LEARNING

3 Lecture Hours  ·  0 Lab Hours

A detailed investigation of current machine learning methods, including statistical, connectionist, and symbolic learning. Presents theoretical results for comparing methods and determining what is learnable. Current issues in machine learning research will also be examined. Prerequisite: CSE 5361 and consent of instructor.

 

CSE6366 – DIGITAL IMAGE PROCESSING

3 Lecture Hours  ·  0 Lab Hours

Digitization and coding of images, characterization and representation of digital images in spatial and frequency domains, picture restoration and enhancement, filtering of two-dimensional signals, image reconstruction. Prerequisite: CSE 5366 or consent of instructor.

 

CSE6367 – COMPUTER VISION

3 Lecture Hours  ·  0 Lab Hours

Advanced techniques for interpretation, analysis, and classification of digital images. Topics include methods for segmentation, feature extraction, recognition, stereo vision, 3-D modeling, and analysis of time-varying imagery. Also taught as EE 6358. Prerequisite: CSE 5301 or CSE 5360 or EE 5356 or EE 5357, and consent of instructor.

 

CSE6369 – SPECIAL TOPICS ADVANCED INTELLIGENT SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6379 – SPECIAL TOPICS IN ADVANCED BIOINFORMATICS

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6388 – SPECIAL TOPICS IN ADVANCED INFORMATION SECURITY

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6389 – SPECIAL TOPICS IN ADVANCED MULTIMEDIA, GRAPHICS, & IMAGE PROCESSING

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when topics vary.

 

CSE6392 – SPECIAL TOPICS IN ADVANCED COMPUTER SCIENCE

3 Lecture Hours  ·  0 Lab Hours

May be repeated for credit when the topics vary.

 

CSE6397 – RESEARCH IN COMPUTER SCIENCE

3 Lecture Hours  ·  0 Lab Hours

Individually supervised research projects.

 

CSE6399 – DISSERTATION

3 Lecture Hours  ·  0 Lab Hours

Preparation of dissertation in computer science or computer science and engineering. Graded F, R.

 

CSE6697 – RESEARCH IN COMPUTER SCIENCE

6 Lecture Hours  ·  0 Lab Hours

Individually supervised research projects.

 

CSE6699 – DISSERTATION

6 Lecture Hours  ·  0 Lab Hours

Preparation of dissertation in computer science or computer science and engineering. Graded F, R,P,W.

 

CSE6997 – RESEARCH IN COMPUTER SCIENCE

9 Lecture Hours  ·  0 Lab Hours

Individually supervised research projects.

 

CSE6999 – DISSERTATION

9 Lecture Hours  ·  0 Lab Hours

Preparation of dissertation in computer science or computer science and engineering. Graded P, F, R.

 

CSE7399 – DOCTORAL DEGREE COMPLETION

3 Lecture Hours  ·  0 Lab Hours

This course may be taken during the semester in which a student expects to complete all requirements for the doctoral degree and graduate. Enrolling in this course meets minimum enrollment requirements for graduation, for holding fellowships awarded by The Office of Graduate Studies and for full-time GTA or GRA positions. Students should verify that enrollment in this course meets other applicable enrollment requirements. To remain eligible in their final semester of study for grants, loans or other forms of financial aid administered by the Financial Aid Office must enroll in a minimum of 5 hours as required by the Office of Financial Aid. Other funding sources may also require more than 3-hours of enrollment. Additional hours may also be required to meet to requirements set by immigration law or by the policies of the student's degree program. Students should contact the Financial Aid Office, other sources of funding, Office of International Education and/or their graduate advisor to verify enrollment requirements before registering for this course. This course may only be taken once and may not be repeated. Students who do not complete all graduation requirements while enrolled in this course must enroll in a minimum of 6 dissertation hours (6699 or 6999) in their graduation term. Graded P/F/R.