Graduate-level Courses
4321 Data Communications
Pre-requisite(s): CSI 3336 (Systems Programming).
Fundamentals of computer networking including data transmission, communication software, protocols, simple networks and internetworking.
4337 Introduction to Operating Systems
Pre-requisite(s): CSI 3336 (Systems Programming).
Operating system design and implementation. Topics include process control and synchronization, memory management, processor scheduling, file systems, and security. Course projects implement parts of an operating system.
5010 Graduate Seminar
Pre-requisite(s): Graduate standing in computer science.
Research presentations by the graduate faculty, outside speakers, and select advanced graduate students. Attendance at various functions is also required.
5199 Non-Thesis Degree Completion
To fulfill requirements for non-thesis master’s students who need to complete final degree requirements other than coursework during their last semester. This may include such things as a comprehensive examination, oral examination, or foreign language requirement. Students are required to be registered during the semester they graduate.
5310 Introduction to Computation Theory
Pre-requisite(s): CSI 3344 (Intro to Algorithms).
Several models of computation and their related languages. Topics will include finite automata and regular languages, push-down automata and context-free languages, linear-bounded automata and context-sensitive languages. Turing machines and phrase structure languages, closure properties, decidability results, non-determinism.
5321 Advanced Data Communications
Pre-requisite(s): CSI 4321 or equivalent.
Survey of current and seminal research in networking.
5324 Software Engineering
Methods for developing and maintaining software systems; system software life cycle, requirements elicitation, specification and design methods, planning, maintenance, configuration management, documentation and coding standards, cost estimation, metrics and quality attributes; class project.
5325 Introduction to Machine Learning
Pre-requisite(s): CSI 4336 or consent of instructor.
An introduction to topics in machine learning, including supervised and unsupervised learning, modeling for regression and classification, naive Bayes methods, kernel-based learning, support vector machines, statistical and mathematical models for learning, and model assessment and prediction.
5326 Advanced Machine Learning
Pre-requisite(s): CSI 5325 or consent of instructor
This course provides a comprehensive and in-depth exploration of advanced topics in machine learning, emphasizing probabilistic approaches, mathematical rigor, and practical applications. It covers topics such as parameter estimation, optimization techniques, graphical models, graph-based learning, reinforcement learning, and modern deep learning architectures. Through theoretical study, algorithmic development, and hands-on projects, students will gain the skills necessary to tackle complex challenges in modern machine learning.
5330 Advanced Computational Biology (Cross-listed as BINF 5330)
Advanced course of computational methods for understanding biological systems. Topics include string matching, suffix tree analysis, sequence alignment, and other graph theoretic algorithms for gene mapping and sequencing, phylogenetic inference, and biological network analysis.
5335 Advanced Database
Pre-requisite(s): CSI 3334 and 3335.
A continuation of database system implementations to include object-oriented and knowledge-based systems. Additional topics covered are physical-data organization, database integrity, security, transaction management, and distributed database management.
5336 Data Models
Pre-requisite(s): CSI 4334 and 4335.
Conceptual and abstract parts of databases. Topics include commonly used data models (hierarchical, network, relational, semantic network and info-logical) and the use of data models for database design and operation.
5337 Advanced Operating Systems
Pre-requisite(s): CSI 4337 and STA 4385; or PSY 4300.
Advanced topics in operating systems including queuing models, performance measurement and evaluation, security and protection, and design issues involved in operating system design.
5338 Advanced Computer Organization
Pre-requisite(s): CSI 3338 or consent of instructor.
Advanced topics in computer systems organization, including techniques used in large-scale computer systems, parallel and pipeline architectures, stack machines, and other non-von Neumann architectures.
5342 Software Specification and Design
Pre-requisite(s): CSI 4336.
Overview and comparison of existing formal specification methods. In-depth description and use of an existing method, such as algebraic specifications. Mathematical foundations of the method. Applications to practical examples. Use of an existing specification language.
5343 Introduction to Human Computer Interaction
Introduction to Human Computer Interaction is a research seminar designed to explore the issues of design, organization, implementation, communication, training, and management which confront humans as users of computer environments.
5344 Analytic Models
Pre-requisite(s): STA 3381.
Computer modeling of a variety of systems. Topics include selections from: linear programming, network analysis, queuing theory, game theory, and statistical methods and models.
5345 Parallel Systems
Description and evaluation of parallel hardware and software. Distributed-memory versus shared-memory. Design and implementation of parallel programs using parallel hardware and software.
5346 Design Automation
This course is about automating the design of Very Large Scale Integrated circuits. The curriculum covers compiled and event driven simulation algorithms, differential simulation techniques, current literature in electronic simulation, channel routing algorithms, Lee routers, partitioning, current literature in placement and routing, synthesis algorithms, and current literature in logic and circuit synthesis.
5347 Cloud Computing
Programming and data storage with cloud architectures. Topics include the Apache Hadoop Ecosystem and related programming frameworks.
5350 Advanced Algorithms
Pre-requisite(s): CSI 3344 or graduate standing.
Advanced data structures, algorithm design, and analysis. Topics include common data structures, algorithms, implementation, classes of algorithms, algorithm analysis, computational tradeoffs, and adaptation of familiar algorithms to new problems.
5352 Advanced Object-Oriented Development
Pre-requisite(s): CSI 4344.
Object-oriented analysis, design, and implementation using C++ and a graphical user interface. Principles, methods, and building blocks. Identification and implementation of objects. Class libraries and widget sets. Group projects.
5353 Multimedia Systems
Overview of systems requirements to handle multimedia information. Topics include synchronization, content-based information retrieval, protocols, and media type definitions. Theory and applications are covered.
5354 Advanced Software Engineering
Pre-requisite(s): CSI 5324 or consent of instructor.
Advanced topics in software engineering research, including techniques used in the modeling and analysis of complex systems.
5355 Data Mining and Analysis
Pre-requisite(s): Graduate standing.
Introduces the fundamental data analysis algorithms used in research.
5360 Information Retrieval & Natural Language Processing
Pre-requisite(s): CSI 3344, MTH 2311 or equivalent.
Introduce fundamental and advanced algorithms in Information Retrieval and Natural Language Algorithms. Topics include Language Modelling, Retrieval Algorithms and Evaluation, and Language Processing techniques such as tagging, parsing, and lexical semantics. Applications and research topics are also covered.
5388 Advanced Topics in Human-Computer Interaction
This class investigates the “emerging” next generation of user interaction with a focus on the design and evolution of interaction techniques. Variety of user interaction styles may include gesture, virtual reality, augmented reality, ubiquitous, tangible, lightweight, tacit, passive, affective, perceptual, context-aware, and multi-modal interfaces.
5V90 Special Problems 1 to 9 sem. hrs.
Pre-requisite(s): Consent of instructor.
5V92 Master’s Research 1 to 3 sem. hrs.
Pre-requisite(s): Consent of instructor.
Concentrated research for the purpose of determining whether the thesis or project option is most appropriate, and for the initial selection of a topic area.
5V93 Special Topics in Computer Science 1 to 4 sem. hrs.
May be repeated for credit, provided topic is not duplicated, for a maximum of eighteen semester hours total.
5V96 Master’s Project 1 to 3 sem. hrs.
Pre-requisite(s): Consent of instructor.
5V99 Thesis 1 to 9 sem. hrs.
Pre-requisite(s): Consent of instructor.
Research, data analysis, writing, and oral defense of an approved master’s thesis. At least three hours of CSI 5V99 are required.
6326 Advanced Deep Learning
Pre-requisite(s): CSI 5325 or ELC 5365
This course offers an in-depth exploration of advanced deep learning methodologies, focusing on state-of-the-art neural network architectures such as convolutional, recurrent, attention mechanisms, and auto-regressive generative models. Emphasis is placed on advanced optimization techniques, hyperparameter tuning, and neural architecture search. Students will engage in rigorous theoretical study and practical implementation, addressing applications in computer vision, natural language processing, bioinformatics, and cybersecurity. The course also critically examines the ethical and societal implications of AI technologies. The course integrates theoretical foundations with research projects, preparing students to address complex challenges in AI research and industry.
6347 Research Issues in Distributed Computing
Seminar course on research issues in distributed computing. Issues include correctness, performance, security, fault tolerance, applications and algorithms. Students will read a collection of research papers on one or more topics and present information related to a topic.
6V10 Doctoral Prospectus Research 1 to 6 sem. hrs.
Pre-requisite(s): Instructor approval.
Supervised research for developing a dissertation prospectus. Prepares students for the preliminary exam required for students to advance to candidacy. A student may repeat this course for credit with a maximum of ten total hours. Registration for this course is sufficient for achieving full-time status.
6V90 Special Topics in Computer Science 1 to 3 sem. hrs.
Special topics in Computer Science. This course may be taken up to 6 times, on a different topic each time, for up to 18 hours of credit.
6V99 Dissertation 1 to 12 sem. hrs.
Research, data analysis, writing, and oral defense of an approved doctoral dissertation topic.
If you have any further question regarding the graduate degrees in Computer Science program, please contact our Graduate Program Director: Dr. Eunjee Song