CSE Graduate Courses Description

Graduate Courses

Here at the School of Engineering we offer a wide variety of challenging courses. Below is a list of graduate courses offered by the Computer Science & Engineering department.

CSE 300: Special Topics in Computer Science and Engineering

Classroom courses in special topics as announced in advance for each semester.

3 credits, Lecture.

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CSE 311: Seminar

Presentation and discussion of advanced computer science problems.

1 credit, Seminar.

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CSE 320: Independent Study in Computer Science and Engineering

Individual exploration of special topics as arranged by the student with an instructor.

1 - 6 credits, Independent Study. Instructor consent required.

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CSE 321: Software Performance Engineering

Study of performance engineering techniques for the development of software systems to meet performance objectives. Software performance principles, hierarchical performance modeling, and current research trends related to Software Performance Engineering. Methods for computer performance evaluation and analysis with emphasis on direct measurement and analytic modeling, including queuing networks, computation structure models, state charts, probabilistic languages, and Petri-nets. Case studies for the evaluation and analysis of software architecture and design alternatives.

3 credits, Lecture.

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CSE 326: Probabilistic Methods in Digital Systems

Probabilistic methods used to describe random processes and queuing theory and their application to such areas as computer performance, scheduling algorithms, error correcting codes, and stochastic machines.

3 credits, Lecture.

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CSE 327: Advanced Software Engineering

An in-depth study of methodologies for the specification, design, implementation, verification, testing, and documentation of large complex software systems. Special attention is given to the impact of programming language constructs on the quality of complex software.

3 credits, Lecture.

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CSE 330: Advanced Computer Networks and Distributed Processing Systems

Introduction to the design and evaluation of distributed computer communication and processing systems. Case studies, development of suitable queuing and other models to describe and evaluate design problems such as capacity assignment, concentration and buffering, network topology design, routing, access techniques, and line control procedures.

3 credits, Lecture. This course and ECE 335 may not both be taken for credit.

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CSE 331: Distributed Database Systems

Architecture of distributed database systems and their major design problems. Topics include efficient data distribution, distributed views, query processing and optimization, and distributed synchronization. Particular attention is paid to the issue of concurrency control and reliability for distributed transaction processing. Backend database processors and database servers for local area networks are also discussed.

3 credits, Lecture. Prerequisite: CSE 350.

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CSE 332: Parallel Processing

Models of parallel computations, distributed computing design/implementation (problems including structuring, partitioning, allocation and scheduling), data flow and pipelined vector processors, performance measures and performance analysis, parallel algorithms and applications.

3 credits, Lecture. Prerequisite: CSE 221 and CSE 340.

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CSE 333: Distributed Component Systems

This course examines the methodologies, techniques, and tools that can be utilized to design, construct, and prototype a distributed application using a combined object- and component-based approach. Topics that are covered include object-oriented modeling, reusable components, software architectures, security, software agents, interoperation techniques, and deployment strategies. The role of emerging technologies in support of these topics will also be considered.

3 credits, Lecture.

[Back]

CSE 340: Computer Architecture

This course provides an in-depth understanding of the inner workings of modern digital computer systems. Traditional topics on uniprocessor systems such as performance analysis, instruction set architecture, hardware/software pipelining, memory hierarchy design and input-output systems will be discussed. Modern features of parallel computer systems such as memory consistency models, cache coherence protocols, and latency reducing/hiding techniques will also be addressed. Some experimental and commercially available parallel systems will be presented as case studies.

3 credits, Lecture.

[Back]

CSE 350: Advanced Database Topics

Data models/languages including entity-relationship, functional, semantic, and object oriented. Database components including the different building blocks of a database system, concurrency, control, recovery, security, access methods, query optimization, and views. Database architectures including database machines, text-database systems, distributed database systems, multimedia systems, and performance metrics and methodologies. Database applications including CAD/CAM and CASE.

3 credits, Lecture.

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CSE 351: Semantic Data Models

Conceptual data models, semantic and object-oriented data base systems, formal representation methods for data and knowledge, models of active and passive information.

3 credits, Lecture.

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CSE 352: Data Mining

An introduction to data mining algorithms and their analysis. Application of and experimentation with data mining algorithms on real-world problems and domains, with a dual focus on addressing the solution quality issue and the time efficiency issue.
3 credits, Lecture.

[Back]

CSE 353: Information and Data Security

Introduction to privacy, confidentiality, and organizational considerations in the development of security policies for protecting information and data stored, processed and transmitted in computer and communication systems from unauthorized disclosure and modification. In depth study of security enforcement methods and techniques applied to operating systems, database systems and computer networks including user identification and authentication techniques, data access controls, information flow controls, inference controls and cryptographic techniques.

3 credits, Lecture.

[Back]

CSE 354: Introduction to Modern Cryptography

This course covers the foundations of modern cryptography, emphasizing provably-secure cryptographic constructions. The course covers basic topics such as one-way functions, security amplification, and hard-core predicates. Elementary aspects of computational number theory are introduced to motivate current candidate one-way functions such as RSA functions and Rabin's functions. These tools are applied to develop secure encryption schemes, pseudo-random generators, and digital signature schemes.

3 credits, Lecture.

[Back]

CSE 355: Computational Geometry

Curve and surface definitions emphasizing the interplay between those mathematical properties and efficient graphical display. Topics may include Bezier curves and surfaces, nonuniform rational B-spline (NURBS) curves and surfaces, Coons patches, Gordon surfaces, superquadrics, shape preservation, continuity/smoothness, differentiability, twist estimation, the convex hull property, and the treatment of supporting algorithms. Experimental projects are required.

3 credits, Lecture.

[Back]

CSE 356: Advanced Computer Graphics

Computer graphics as a tool for effective human-machine communications. Graphical input and output devices and their relation to human perception. Software systems for image generation, display and manipulation. Languages for description of both static and moving pictures. Solutions to visible-surface and related problems. Computer animation. Models and methodologies for the design of interactive systems for various graphics-oriented applications. Experimental projects are required.

3 credits, Lecture.

[Back]

CSE 357: Advanced Numerical Methods in Scientific Computation

Development, application and implementation of numerically stable, efficient and reliable algorithms for solving matrix equations that arise in modern systems engineering. Computation of matrix expoential, generalized inverse, matrix factorization, recursive least squares, eigenvalues and eigenvectors, Lyapunov and Riccati equations. Extensive digital computer usage for algorithm verification and test.

3 credits, Lecture. Prerequisite: MATH 215Q or EE301, which may be taken concurrently.

[Back]

CSE 358: Advanced Operating Systems

Topics in modern operating systems with the focus on distributed computing, communication, and concurrency. Selected topics from current research in the theory, design, implementation, and verification of operating systems3 credits, Lecture.

[Back]

CSE 361: Advanced Sequential and Parallel Algorithms

Computational complexity measures. Survey of major techniques used to design an efficient algorithm. These include divide and conquer, greedy, dynamic programming, and branch and bound techniques. Randomized algorithms. General characteristics of parallel computation models. General structure of parallel algorithms. Development techniques of efficient parallel algorithms.

3 credits, Lecture.

[Back]

CSE 365: Fundamentals of Automata

A rigorous treatment of automata and formal language theory. Emphasis placed upon finite state automata, regular languages, context-free languages, push-down automata, and Turing machines.

3 credits, Lecture.

[Back]

CSE 367: Computer Science and Engineering Research Laboratory

Experimental investigation of current research topics in computer science. May be repeated for credit with a change in content.

3 credits, Lecture.

[Back]

CSE 372: Image Processing

A formal approach to continuous variable and discrete variable imaging. Continuous and discrete transforms. Image enhancement. Image analysis including multidimensional edge-primitive theories, shape analysis. Multispectral imaging and applications. Image modelling. Syntactical analysis, aspects of image database theories. The course involves exposure to multispectral and extraterrestrial imagery. A substantial programming project is assigned.

3 credits, Lecture.

[Back]

CSE 382: Adanced Artificial Intelligence

Design and implementation of intelligent systems. Topics covered will include automated reasoning, natural language, learning, agents, probabilistic reasoning, and robotics. The course will include a substantial design project, and advanced independent study of at least one of the above topics. This course and CSE 282 may not both be taken for credit.

3 credits, Lecture.

[Back]

CSE 426: Linear Algebraic Queueing Theory

Brief survey of Markov Chains, and their application to simple queues, with some emphasis on their transient behavior. Matrix operators are then introduced to represent the behavior of non-exponential servers. This algebraic structure is applied to the steady-state and non steady-state behavior of both open and closed M/G/1 queues. Then G/M/1 queues are examined in detail. As time permits additional advanced topics will be covered. Applications to computer and telecommunications system performance modeling will be studied.

3 credits, Lecture. Prerequisite: CSE 326.

[Back]

CSE 430: Research Topics in Computer Networks

Research and development in planning, analysis and design of an interconnected collection of autonomous computers. Technical and organizational issues of computer networks, including communication media, topology, architecture, structures, and protocols. Topics include efficient resource sharing; high reliability, integrity and security; installation flexibility and expandability; ease of access; application adaptability; interface standardization; and internetworking.

3 credits, Lecture. Prerequisite: CSE 330.

[Back]

CSE 455: Computational Topology

Topology has traditionally generalized concepts of real analysis to metric spaces and set axioms. The new field of computational topology has great potential for encompassing abstractions to unify domain-specific techniques now used in computational geometry, geometric modeling, visualization, image processing, engineering analyses and molecular simulation. The course will include perspectives from traditional topology and show how these need to be modified for realistic use in modern computing environments. Topics and emphases will vary.

3 credits, Lecture. Prerequisite: CSE 455.

[Back]

CSE 461: Fault-Tolerant Parallel Computing

Advanced topics in fault-tolerant parallel algorithms. Shared memory and message-passing models of computation. Models of failure. Formal treatment of complexity measures, such as time, space, communication, work, and speedup. Lower bounds for parallel fault-tolerant computation. Design and analysis of efficient fault-tolerant algorithms. Combining efficiency and fault-tolerance in parallel and distributed algorithms.

3 credits, Lecture. Prerequisite: CSE 332 or CSE 361.

[Back]

CSE 483: Natural Language Processing

An artificial-intelligence approach to computational linguistics. Representation of meaning and knowledge in computer-usable form. Understanding and generation of natural-language sentences and text. Theories of inference and application of world knowledge. Organization of large knowledge-based text-processing systems for applications in summary and paraphrase, question-answering, machine translation, conversation and computer-aided instruction. "Real" text-processing systems are demonstrated, and a term project is required.

3 credits, Lecture. Prerequisite: CSE 382.

[Back]


Computer Science & Engineering Department 371 Fairfield Road Unit 2155 Storrs, CT 06269-2155 Phone: (860) 486-3719 Fax: (860) 486-4817	Graduate Courses Here at the School of Engineering we offer a wide variety of challenging courses. Below is a list of graduate courses offered by the Computer Science & Engineering department. CSE 300: Special Topics in Computer Science and Engineering Classroom courses in special topics as announced in advance for each semester. 3 credits, Lecture. [Back] CSE 311: Seminar Presentation and discussion of advanced computer science problems. 1 credit, Seminar. [Back] CSE 320: Independent Study in Computer Science and Engineering Individual exploration of special topics as arranged by the student with an instructor. 1 - 6 credits, Independent Study. Instructor consent required. [Back] CSE 321: Software Performance Engineering Study of performance engineering techniques for the development of software systems to meet performance objectives. Software performance principles, hierarchical performance modeling, and current research trends related to Software Performance Engineering. Methods for computer performance evaluation and analysis with emphasis on direct measurement and analytic modeling, including queuing networks, computation structure models, state charts, probabilistic languages, and Petri-nets. Case studies for the evaluation and analysis of software architecture and design alternatives. 3 credits, Lecture. [Back] CSE 326: Probabilistic Methods in Digital Systems Probabilistic methods used to describe random processes and queuing theory and their application to such areas as computer performance, scheduling algorithms, error correcting codes, and stochastic machines. 3 credits, Lecture. [Back] CSE 327: Advanced Software Engineering An in-depth study of methodologies for the specification, design, implementation, verification, testing, and documentation of large complex software systems. Special attention is given to the impact of programming language constructs on the quality of complex software. 3 credits, Lecture. [Back] CSE 330: Advanced Computer Networks and Distributed Processing Systems Introduction to the design and evaluation of distributed computer communication and processing systems. Case studies, development of suitable queuing and other models to describe and evaluate design problems such as capacity assignment, concentration and buffering, network topology design, routing, access techniques, and line control procedures. 3 credits, Lecture. This course and ECE 335 may not both be taken for credit. [Back] CSE 331: Distributed Database Systems Architecture of distributed database systems and their major design problems. Topics include efficient data distribution, distributed views, query processing and optimization, and distributed synchronization. Particular attention is paid to the issue of concurrency control and reliability for distributed transaction processing. Backend database processors and database servers for local area networks are also discussed. 3 credits, Lecture. Prerequisite: CSE 350. [Back] CSE 332: Parallel Processing Models of parallel computations, distributed computing design/implementation (problems including structuring, partitioning, allocation and scheduling), data flow and pipelined vector processors, performance measures and performance analysis, parallel algorithms and applications. 3 credits, Lecture. Prerequisite: CSE 221 and CSE 340. [Back] CSE 333: Distributed Component Systems This course examines the methodologies, techniques, and tools that can be utilized to design, construct, and prototype a distributed application using a combined object- and component-based approach. Topics that are covered include object-oriented modeling, reusable components, software architectures, security, software agents, interoperation techniques, and deployment strategies. The role of emerging technologies in support of these topics will also be considered. 3 credits, Lecture. [Back] CSE 340: Computer Architecture This course provides an in-depth understanding of the inner workings of modern digital computer systems. Traditional topics on uniprocessor systems such as performance analysis, instruction set architecture, hardware/software pipelining, memory hierarchy design and input-output systems will be discussed. Modern features of parallel computer systems such as memory consistency models, cache coherence protocols, and latency reducing/hiding techniques will also be addressed. Some experimental and commercially available parallel systems will be presented as case studies. 3 credits, Lecture. [Back] CSE 350: Advanced Database Topics Data models/languages including entity-relationship, functional, semantic, and object oriented. Database components including the different building blocks of a database system, concurrency, control, recovery, security, access methods, query optimization, and views. Database architectures including database machines, text-database systems, distributed database systems, multimedia systems, and performance metrics and methodologies. Database applications including CAD/CAM and CASE. 3 credits, Lecture. [Back] CSE 351: Semantic Data Models Conceptual data models, semantic and object-oriented data base systems, formal representation methods for data and knowledge, models of active and passive information. 3 credits, Lecture. [Back] CSE 352: Data Mining An introduction to data mining algorithms and their analysis. Application of and experimentation with data mining algorithms on real-world problems and domains, with a dual focus on addressing the solution quality issue and the time efficiency issue. 3 credits, Lecture. [Back] CSE 353: Information and Data Security Introduction to privacy, confidentiality, and organizational considerations in the development of security policies for protecting information and data stored, processed and transmitted in computer and communication systems from unauthorized disclosure and modification. In depth study of security enforcement methods and techniques applied to operating systems, database systems and computer networks including user identification and authentication techniques, data access controls, information flow controls, inference controls and cryptographic techniques. 3 credits, Lecture. [Back] CSE 354: Introduction to Modern Cryptography This course covers the foundations of modern cryptography, emphasizing provably-secure cryptographic constructions. The course covers basic topics such as one-way functions, security amplification, and hard-core predicates. Elementary aspects of computational number theory are introduced to motivate current candidate one-way functions such as RSA functions and Rabin's functions. These tools are applied to develop secure encryption schemes, pseudo-random generators, and digital signature schemes. 3 credits, Lecture. [Back] CSE 355: Computational Geometry Curve and surface definitions emphasizing the interplay between those mathematical properties and efficient graphical display. Topics may include Bezier curves and surfaces, nonuniform rational B-spline (NURBS) curves and surfaces, Coons patches, Gordon surfaces, superquadrics, shape preservation, continuity/smoothness, differentiability, twist estimation, the convex hull property, and the treatment of supporting algorithms. Experimental projects are required. 3 credits, Lecture. [Back] CSE 356: Advanced Computer Graphics Computer graphics as a tool for effective human-machine communications. Graphical input and output devices and their relation to human perception. Software systems for image generation, display and manipulation. Languages for description of both static and moving pictures. Solutions to visible-surface and related problems. Computer animation. Models and methodologies for the design of interactive systems for various graphics-oriented applications. Experimental projects are required. 3 credits, Lecture. [Back] CSE 357: Advanced Numerical Methods in Scientific Computation Development, application and implementation of numerically stable, efficient and reliable algorithms for solving matrix equations that arise in modern systems engineering. Computation of matrix expoential, generalized inverse, matrix factorization, recursive least squares, eigenvalues and eigenvectors, Lyapunov and Riccati equations. Extensive digital computer usage for algorithm verification and test. 3 credits, Lecture. Prerequisite: MATH 215Q or EE301, which may be taken concurrently. [Back] CSE 358: Advanced Operating Systems Topics in modern operating systems with the focus on distributed computing, communication, and concurrency. Selected topics from current research in the theory, design, implementation, and verification of operating systems3 credits, Lecture. [Back] CSE 361: Advanced Sequential and Parallel Algorithms Computational complexity measures. Survey of major techniques used to design an efficient algorithm. These include divide and conquer, greedy, dynamic programming, and branch and bound techniques. Randomized algorithms. General characteristics of parallel computation models. General structure of parallel algorithms. Development techniques of efficient parallel algorithms. 3 credits, Lecture. [Back] CSE 365: Fundamentals of Automata A rigorous treatment of automata and formal language theory. Emphasis placed upon finite state automata, regular languages, context-free languages, push-down automata, and Turing machines. 3 credits, Lecture. [Back] CSE 367: Computer Science and Engineering Research Laboratory Experimental investigation of current research topics in computer science. May be repeated for credit with a change in content. 3 credits, Lecture. [Back] CSE 372: Image Processing A formal approach to continuous variable and discrete variable imaging. Continuous and discrete transforms. Image enhancement. Image analysis including multidimensional edge-primitive theories, shape analysis. Multispectral imaging and applications. Image modelling. Syntactical analysis, aspects of image database theories. The course involves exposure to multispectral and extraterrestrial imagery. A substantial programming project is assigned. 3 credits, Lecture. [Back] CSE 382: Adanced Artificial Intelligence Design and implementation of intelligent systems. Topics covered will include automated reasoning, natural language, learning, agents, probabilistic reasoning, and robotics. The course will include a substantial design project, and advanced independent study of at least one of the above topics. This course and CSE 282 may not both be taken for credit. 3 credits, Lecture. [Back] CSE 426: Linear Algebraic Queueing Theory Brief survey of Markov Chains, and their application to simple queues, with some emphasis on their transient behavior. Matrix operators are then introduced to represent the behavior of non-exponential servers. This algebraic structure is applied to the steady-state and non steady-state behavior of both open and closed M/G/1 queues. Then G/M/1 queues are examined in detail. As time permits additional advanced topics will be covered. Applications to computer and telecommunications system performance modeling will be studied. 3 credits, Lecture. Prerequisite: CSE 326. [Back] CSE 430: Research Topics in Computer Networks Research and development in planning, analysis and design of an interconnected collection of autonomous computers. Technical and organizational issues of computer networks, including communication media, topology, architecture, structures, and protocols. Topics include efficient resource sharing; high reliability, integrity and security; installation flexibility and expandability; ease of access; application adaptability; interface standardization; and internetworking. 3 credits, Lecture. Prerequisite: CSE 330. [Back] CSE 455: Computational Topology Topology has traditionally generalized concepts of real analysis to metric spaces and set axioms. The new field of computational topology has great potential for encompassing abstractions to unify domain-specific techniques now used in computational geometry, geometric modeling, visualization, image processing, engineering analyses and molecular simulation. The course will include perspectives from traditional topology and show how these need to be modified for realistic use in modern computing environments. Topics and emphases will vary. 3 credits, Lecture. Prerequisite: CSE 455. [Back] CSE 461: Fault-Tolerant Parallel Computing Advanced topics in fault-tolerant parallel algorithms. Shared memory and message-passing models of computation. Models of failure. Formal treatment of complexity measures, such as time, space, communication, work, and speedup. Lower bounds for parallel fault-tolerant computation. Design and analysis of efficient fault-tolerant algorithms. Combining efficiency and fault-tolerance in parallel and distributed algorithms. 3 credits, Lecture. Prerequisite: CSE 332 or CSE 361. [Back] CSE 483: Natural Language Processing An artificial-intelligence approach to computational linguistics. Representation of meaning and knowledge in computer-usable form. Understanding and generation of natural-language sentences and text. Theories of inference and application of world knowledge. Organization of large knowledge-based text-processing systems for applications in summary and paraphrase, question-answering, machine translation, conversation and computer-aided instruction. "Real" text-processing systems are demonstrated, and a term project is required. 3 credits, Lecture. Prerequisite: CSE 382. [Back] Print \| Email