Gil Gallegos, Ph.D., Department Chair
Ivan Hilton Science Building
- Mission of the Department of Computer and Mathematical Sciences
- Admission Requirements
- Masters of Arts Sciences
- Resources and Facilities
The Department of Computer and Mathematical Sciences offers graduate courses in computer science and mathematics. Additionally, a joint media arts and computer science degree is offered by the Department of Computer and Mathematical Sciences and the School of Business, Media and Technology.
Gil Gallegos, Ph.D. (Computer science)
John S. Jeffries, Ph.D. (Mathematics)
Richard Medina, Ph.D. (Computer science)
Joe Sabutis, Ph.D. (Physics)
Gregg Turner, Ph.D. (Mathematics)
Mission of the Department of Computer and Mathematical Sciences
The mission of the Department of Computer and Mathematical Sciences is to train students in the fields of computer science. The mathematics discipline offers an emphasis in an interdisciplinary program within the School of Education’s Curriculum and Instruction master’s program designed for secondary education mathematics teachers. By encouraging and developing problem-solving, critical/analytical thinking, and practical, laboratory-based skills, our students will be well-prepared for careers in any combination of these fields, either through solid preparation for further graduate education or immediate entrance into the workforce (industry, teaching, government, and national laboratories). The department offers graduate-level courses in mathematics and physics that support graduate degrees in other disciplines such as business, chemistry, computer science, and education. The department does not offer standalone graduate degrees. Students who pursue graduate degrees requiring the preparation of a thesis are encouraged to select research topics that require the application of mathematics or physics principles.
Media Arts and Computer Science (MS)
- Statement of Educational Goals
- 2 Letters of Recommendation
- Transcripts from all previously attended regionally accredited institutions (3.0 GPA or higher)
- Will consider those who do not meet the GPA requirement.
Master of Arts/Science
The disciplines of computer science and media arts are experiencing a significant convergence of interests. Computer science, with its interest in exploring and developing new programming paradigms, big data, analytics, cybersecurity, machine learning, high performance computing, user interfaces, computer networking models, and multimedia-based technologies, is constantly offering new and challenging topics in the field of computer science. The media arts professions, including graphics design, broadcasting, as well as video and audio production, have always sought new and more effective ways to express ideas, concepts, and visions. Thus, they have a natural interest in the possibilities offered by the technologies coming out of computer science. The Department of Visual and Performing Arts and the Department of Computer and Mathematical Sciences jointly offer a program in Media Arts and Computer Science (MACS) that, depending on one’s program of study and background, could lead to either a master of arts or master of science degree.
Students can enter the program starting from either a media arts or computer science perspective and develop further skills in both areas. The key to the program is its interdisciplinary nature, and students are expected to work with students from other disciplines in class and out of class. Students have options of taking both media arts and computer science with the approval of their adviser.
While the program itself is broadly based, students are expected to develop a focused program of study in conjunction with an adviser. Students are encouraged to be innovative in the development of their focus. Possibilities could grow out of multimedia systems, human-computer interface issues, animation and visualization, data mining, and computer vision.
The general entrance requirement for the program is a bachelor’s degree in an area related to one of the disciplines involved in this program or a bachelor’s degree in some unrelated area AND work experience in an area related to one of the discipline areas. To be accepted into the master of science track, a student must have a bachelor of science degree or have a strong mathematics background, including calculus and either discrete mathematics or linear algebra.
To promote the integration of disciplines stressed above, all students take a core set of team-taught courses. This nine-unit core is the foundation of the interdisciplinary nature of this program. The first two courses create the interdisciplinary, collective atmosphere that sets the tone for the rest of the program. Working together, students and faculty from various backgrounds create a common language and educate each other in the core ideas of the different disciplines. In the third course, students use industrial techniques and tools in the development of a sophisticated, multimedia-based project. In all three courses there is time set aside to support the process of developing a thesis project.
Resources and Facilities
The department resides within the Ivan Hilton Science Building on Highlands’ main campus.
There are two large teaching labs, three small research labs, a student work lab, and an area set aside for network experimentation. The labs are equipped, for the most part, with machines running both Windows® and Linux(Ubuntu). The department has a 16-node high performance cluster and a dozen high performance nVidia Tegra boards for high performance computing utilizing embedded systems and hybrid GPU/CPU distributed and parallel programming schemes. Software includes symbolic and numerical products, compilers, integrated development environments, web and multimedia development tools, MATLAB®, R, Python, C/C++, databases, and packages for special fields such as machine learning. Some computers are set aside for student experimentation with the understanding that students may install any software as long as copyright laws are not violated. Additionally, the department has a drone and 3D vision hardware and software for high performance testing of real-time 3D vision applications for research in the computer science field.
Master of Arts or Science in Media Arts and Computer Science (MA or MS)
All students must take 6 units of thesis or project work.
CS 6000 Principles of Media Arts and Computer Science (3)
CS 6100 Synthesis of Media Arts and Computer Science (3)
CS 6200 Multimedia Project Development (3)
CS 6970 Field Project (6)
CS 6990 Thesis (6)
Required core: 15 credit hours
With completion of these courses, students begin the process of integrating their special interests with the commitment to maintain an interdisciplinary, collaborative attitude. Students are expected to develop a focused program of study in conjunction with an adviser. They are encouraged to be innovative in the development of their focus.
Electives: 21 credit hours
Choose 21 credit hours (seven courses, from any approved graduate-level courses in computer science, mathematics, or media arts. Students may be able to add courses from psychology, education, art, music, or other disciplines, depending on interests. Students working towards a master of science degree must choose courses from computer science, mathematics, or a discipline offering a master of science degree.
Program Total: 36 credit hours
Computer Science (CS), Courses in
CS 5110. Computer Programming for Educators (3); Fa, Sp
This is an in-depth study of the BASIC and LOGO programming languages, two of the most popular computer programming languages for use in the educational environment. This course will have a strong pedagogic component, and all students will develop lesson plans for teaching computer programming in the secondary school. Previous NMHU CS 511.
CS 5120. Scripting Languages (3); 2, 2 Fa, Sp
This course is an introduction to high-level scripting languages. This course uses script programming to teach the basic ideas of programming and to introduce the object-oriented paradigm. It does not, however, teach the complexities of a standard third-generation language. It is meant as an introduction for students who wish to understand programming principles without learning the details. Previous NMHU CS 512.
CS 5140. The C++ Programming Language (3); 2, 3 Fa, Sp
This course is an in-depth study of the C++ programming language. The significant features of the language will be discussed with special emphasis on those that relate to object-oriented programming. Previous NMHU CS 514.
CS 5150. JAVA Programming (3); 2, 2 Fa
This course is an introduction to object-oriented programming language. Numerous programs will be written to exercise the material covered. Prerequisite: Permission of instructor. Previous NMHU CS 515.
CS 5160. Advanced Computer Programming with Data Structures (3); 2, 3 Sp
This course explores the principles of software engineering, including debugging and testing, string processing, internal searching and sorting, simple data structures, recursion, and object-oriented programming. In addition, students explore how to best teach the material. Prerequisite: CS 5140 with a C or better or permission of instructor. Previous NMHU CS 516.
CS 5180. Multimedia Programming (3); 2, 2 Fa, Sp
This course is an introduction to programming multimedia applications. Numerous programs will be written to exercise the material covered. Prerequisite: Programming experience and permission of instructor. Previous NMHU CS 518.
CS 5210. Advanced Data Structures and Algorithm Development (3); Fa, Sp
This course is an investigation of computer data structures with an emphasis on the design and development of efficient algorithms for solving a wide variety of common computing problems. The course also covers the analysis and measurement of the performance of algorithms. Prerequisite: Grades of at least C in CS 3450, CS 3500, and MATH 3170. Previous NMHU CS 521.
CS 5250. Computer Hardware Installation and Maintenance (1); 0, 2 Fa, Sp
This course is a practical investigation of the processes involved in the installation and debugging of complex computer hardware systems including disk controllers, sounds and graphic boards, communication hardware, and various peripherals. Students will work on their own and in teams to build computer systems. Previous NMHU CS 525.
CS 5260. Computer Software Installation and Maintenance (1); 0, 2 Fa, Sp
This course is a practical investigation of the processes involved in the installation of complex computer software, including operating systems, communication packages, and Windows®-based programs. Students will work on their own and in teams to both prepare computers for installation and actually install a wide range of computer software. Prerequisite: CS 5250 or permission of instructor. Previous NMHU CS 525.
CS 5270. UNIX and Systems Administration (1); 0, 2 Fa, Sp
This course is a hands-on introduction to the UNIX operating system with an emphasis on system administration and networking. Prerequisite: Graduate standing and knowledge of at least one other operating system. Previous NMHU CS 527.
CS 5280. C and UNIX (3); 3, 0 Fa, Sp
This course explores C programming language and system programming on UNIX and LINUX™ operating systems. Prerequisite: CS 5270 or permission of instructor. Previous NMHU CS 528.
CS 5310. Database Management (3); 3, 0 Fa, Sp
This course explores the development of the major types of database systems, providing the framework for some experience with at least one database model. Assignments will include accessing, updating, and organizing a database. The use of a relational model will be emphasized along with various database inquiry systems, including natural language-like systems. Prerequisite: CS 5160 with a minimum grade of C or permission of instructor. Previous NMHU CS 531.
CS 5320. Advanced Database Management (3); Fa, Sp
This course is an investigation into advanced topics in information management and retrieval. The focus of the course may change from year to year. Some example topics that may be taught include multimedia databases, building digital libraries, relational or object-oriented implementation, building database-driven websites, text and image information retrieval, and data mining. Students will be expected to read and report on research literature related to the course topic. Prerequisite: Permission of instructor. Previous NMHU CS 532.
CS 5350. Selected Topics in Computer Science (1 – 4 VC); Fa, Sp
Course in a topic or topics in computer science. May be repeated with change of content. Previous NMHU CS 535.
CS 5360. Human-Computer Interaction (3); 3, 0 Fa, Sp
This course investigates theory and practice in human-computer interaction. Students will study the impact of human perception and cognition on user interface design and learn to use tools for building graphical user interface (GUIs) and speech interfaces. In addition, each student will design and implement a user interface. Prerequisite: CS 5160 with a minimum grade of C or permission of instructor. Previous NMHU CS 536.
CS 5420. Computer Systems Architecture (3); 3, 0 Fa, Sp
This course acquaints the student with the way a computer works internally. Topics to be covered include basic logic design, data coding, parity generation and detection, number representation and arithmetic, and computer architecture. Prerequisites: CS 3410 and CS 5160 with a minimum grade of C or permission of instructor. Previous NMHU CS 542.
CS 5430. Operating Systems (3); Fa, Sp
This course is a study of the concepts associated with the modern operating system. Topics will include supervisors, command processors, device drivers, interrupt handlers, queue managers, resource managers, memory allocation schemes, process activation and control, and timesharing or multitask control. Prerequisite: CS 3410. Previous NMHU CS 543.
CS 5510. Software Engineering (3); Fa, Sp
This course is a study of the concepts and techniques of software engineering. Emphasis will be object-oriented design principles, the integration of systems analysis methodologies into software engineering, and topics such as formal specifications and proof of program correctness. Prerequisite: CS 3500. Previous NMHU CS 551.
CS 5550. Computer Graphics (3); Fa, Sp
This course provides an introduction to the applications and basic techniques involved in the general field of computer graphics. The course will be a combination of surveying the different hardware and software used in graphic systems and of implementing some basic graphic algorithms. Students will have access to SGI hardware and software. Prerequisite: CS 5160 or permission of instructor. Previous NMHU CS 555.
CS 5560. Internet Services (3); 2, 2 Fa, Sp
This course is an introduction to telecommunications and the Internet. This course introduces the use of Internet for both research and problem solving. Students will be expected to develop tools for enhancing and accessing the Internet. Previous NMHU CS 556.
CS 5570. Computer Networks (3); Fa, Sp
This course is a study of the major concepts of computer networks and data communications. Topics discussed will include data communication networking, computer communications architectures and protocols as well as applications including local area networks (LAN) and wide area networks (WAN). Cross-listed as: MIS 5200. Previous NMHU CS 557.
CS 5580. Network Management (3); Fa, Sp
This course explores the application of networking concepts related to the management of LANs. Includes topics related to repair, setup, management and maintenance of LANs. Prerequisite: CS 5570, MIS 5200 or experience with computer networks, with permission of instructor. Previous NMHU CS 558.
CS 5590. Network Security (3); Fa, Sp
This course addresses security issues for TCP/IP-based and NT networks, access control and communications security. Prerequisite: CS 5570, MIS 5200, or permission of instructor. Previous NMHU CS 559.
CS 5610. Programming Languages (3); Fa, Sp
This course is a comparative study of programming languages and their features. The course develops an understanding of the organization of programming languages, especially the run-time behavior of programs. Students will gain experience with a variety of languages. Prerequisite: CS 2450 and one other programming language course. Previous NMHU CS 561.
CS 5620. Compiler Design (3); Fa, Sp
This course is a formal treatment of programming language interpreter, translator, and compiler design concepts. Topics include lexical analysis, parsing, code generation, and code optimization. Emphasis will be on the theoretical aspects of parsing context-free languages, translation specifications, and machine-independent code improvement. Programming projects that demonstrate various concepts will be assigned. Prerequisite: CS 5610. Previous NMHU CS 562.
CS 5630. Web Programming (3); 2, 2 Fa, Sp
This course is an introduction to programming on the Internet. Prerequisite: Permission of instructor. Previous NMHU CS 563.
CS 5640. Network Programming (3); Fa, Sp
This course extends the students’ knowledge and practice in analysis, design, and programming of computer networks. Prerequisites: CS 2450 and CS 5280. Previous NMHU CS 564.
CS 5710. Artificial Intelligence (3); Fa, Sp
This course is a general introduction to the theories and problems involved in the development of computer-based intelligence systems with specific emphasis on knowledge representation and search. The focus will be on artificial intelligence research that provides information for the understanding of human intelligence and on application research in areas such as expert systems, natural language systems, and intelligent computer-aided instruction. Previous NMHU CS 571.
CS 5720. Cognitive Science (3); Fa, Sp
This course is an interdisciplinary investigation of the foundations of human knowledge representation and understanding, the functioning of the human mind, and how these impact on recent computer technologies. Cross-listed as: PSY 5720 and Phil 5720. Previous NMHU CS 572.
CS 5730. Artificial Neural Networks (3); Fa, Sp
This course examines basic neurobiology, neural networks, single neuron models, single-layer perceptrons, multi-layer perceptrons, radial basis function networks; committee machines; Kohonen networks, and applications of neural networks. Prerequisites: Previous NMHU CS 573.
CS 5740. Machine Learning Algorithms (3); Fa, Sp
This course studies different machine learning techniques/paradigms, including decision trees, neural networks, genetic algorithms, Bayesian leaning, rule learning, and reinforcement learning. The applications of these techniques to problems in data analysis, knowledge discovery and data mining are discussed. Previous NMHU CS 574.
CS 5750. Image Processing (3); Fa, Sp
The course provides mathematical foundations and practical techniques for digital manipulation of images such as preprocessing, segmentation, Fourier domain processing, and compression. Previous NMHU CS 575.
CS 5760. Animation and Visualization (3); Fa, Sp
Computer-based graphical representations, or visualizations, or scientific processes and phenomena have become commonplace in scientific communities. For example, geologists like to visualize plate tectonics; meteorologists like to visualize weather systems; and computer scientists like to visualize algorithms. After briefly surveying the use of visualization in scientific communities, this course pursues an in-depth investigation of its theoretical underpinnings, from the three diverse perspectives: the cognitive perspective, the social perspective, and the cultural perspective. Prerequisites: CS 2450, MATH 3200. Previous NMHU CS 576.
CS 5770. Parallel and Distributed Programming (3); Fa, Sp
This course introduces algorithms and techniques for programming highly parallel computers. Topics covered include trends in parallel and distributed computing; shared address space and message passing architectures; design issues for parallel algorithms; converting sequential algorithms into equivalent parallel algorithms; synchronization and data sharing; improving performance of parallel algorithms; interconnection network topologies, routing, and flow control; and latency limits on speedup of algorithms by parallel implementations. Design, coding, performance analysis, debugging and other aspects of parallel algorithm development will be covered. Previous NMHU CS 577.
CS 5900. Independent Study (1 – 4 VC); Fa, Sp
Independent study arranged with an instructor. Prerequisite: Permission of instructor. Previous NMHU CS 590.
CS 5920. Independent Research (1 – 4 VC); Fa, Sp
Independent research arranged with an instructor. Prerequisite: Permission of instructor. Previous NMHU CS 592.
CS 6000. Principles of Media Arts and Computer Science (3); Fa
This course is an interdisciplinary investigation of the terminology, roots, assumptions and principles that underlie the merging disciplines of computer science, mass communications, and design studies. Cross-listed as: MART 6000. Previous NMHU CS 600.
CS 6100. Synthesis of Media Arts and Computer Science (3); Sp
This course is an interdisciplinary synthesis of the principles that underlie the merging disciplines of computer science, mass communications, and design studies. Cross-listed as: MART 6100. Previous NMHU CS 610.
CS 6200. Multimedia Project Development (3); Fa
This course is a study of the processes, techniques, and tools used in the development of sophisticated multimedia-based projects. The course focuses on both the theoretical and practical aspects of multimedia design and programming. A key component of the course is the completion of a project that combines the various tools and techniques discussed in the course. The course will also involve student presentations on the research related to their thesis or project. Prerequisites: CS or MART 6000 or 6100. Previous NMHU CS 620.
CS 6350. Selected Topics in Computer Science (3); Fa, Sp
Course in a topic or topics in computer science. May be repeated with change of content. Prerequisite: CS 5350 in the same topic area. Previous NMHU CS 635.
CS 6500. Seminar: Project Development (1); Fa, Sp
This course is a seminar that focuses on the process of writing a thesis or project with specific emphasis on literature search. Students will propose a topic and develop an annotated bibliography using as many different search modalities as possible.
CS 6510. Seminar: Literature Review and Methodology (1); Fa, Sp
This course is a seminar that focuses on the process of developing a formal thesis/project proposal as well as writing the first and second chapters of a thesis or project. Prerequisite: CS 6500. Cross-listed as: MART 6510. Previous NMHU CS 651.
CS 6520. Seminar: Interdisciplinary Reports (1); Fa, Sp
This course is the presentations by students of their process on their thesis or project. The focus will be on interdisciplinary presentations that allow students from one discipline to understand a subject from another discipline and on the development of collaborative efforts. Prerequisite: CS 6510. Cross-listed as: MART 6520. Previous NMHU CS 652.
CS 6970. Field Project (1 –6 VC); Fa, Sp
Individual field research and writing in preparation of a graduate field project (equivalent to a thesis). Prerequisite: Permission of instructor. Previous NMHU CS 697.
CS 6990. Thesis (1 –6 VC); Fa, Sp
Individual research and writing in preparation of a graduate thesis. Prerequisite: Permission of instructor. Previous NMHU CS 699.
Mathematics (MATH), Courses in
MATH 5010. Discrete Chaos and Fractals (3); Fa, Sp
This course is an introduction to fractal geometry and discrete dynamics in one dimension. Topics include stability of one-dimensional maps, periodic points, bifurcations, period three orbis, Sharkovsky’s theorem, Schwarzian derivative, chaos in one, metric spaces, transitivity, conjugacy, fractals, fractal dimension, Julia and Mandelbrot sets. Previous NMHU MATH 501.
MATH 5020. Discrete Dynamical Systems and Chaos (3); Fa, Sp
This course is a continuation of MATH 401 in higher dimensions. Topics include discrete linear dynamical systems, orbits, stability, spectral decomposition theorem, affine systems, nonlinear dynamical systems, bounded invariance, global stability of fixed points, sinks, repellers and saddles, bifuraction, attractors, Li-Yorke chaos, hyperbolic Anosov toral automorphism, and more on fractal dimension. Prerequisite: MATH 5010 with a minimum grade of C. Previous NMHU MATH 5020.
MATH 5040. Intro to Numerical Analysis (3); Fa, Sp
This course is an introduction to numerical methods for determining the roots of nonlinear equations, numerical interpolation and integration, and numerical methods for approximating solutions to ordinary differential equations. Prerequisite: MATH 3200, and MATH 3250 and permission of instructor. Previous NMHU MATH 504.
MATH 5060. College Geometry (4); 3, 2 Fa, Sp
This course is a rigorous treatment of the elements of Euclidean geometry and hyperbolic geometry. Prerequisite: Previous NMHUMATH 506.
MATH 5070. Mathematical Models (3); Fa, Sp
This course is an overview of model construction with many different examples. The course includes differential equations, Markov chains, linear programming, zero sum games, graphs, and queues, with computer simulations of some of the above. Previous NMHU MATH 507.
MATH 5100. Optimization Techniques (3); Fa, Sp
This course is a study of unconstrained and constrained optimization computational algorithms. Previous NMHU MATH 510.
MATH 5150. Intro to Cryptography (3); Fa, Sp
This is an introductory course on the mathematics of cryptography. Topics include column transposition, monoalphabetic and polyalphabetic ciphers, the one-time pad, the Hill cipher, and cipher machines. Prerequisite: Previous NMHU MATH 515.
MATH 5170. Mathematical Statistics II (3); Fa, Sp
This course is a continuation of MATH 3450 covering the topics of contingency tables, multiple regression, analysis of variance, and other special topics in mathematical statistics including multivariate topics. Previous NMHU MATH 517.
MATH 5190. Modern Methods of Cryptography (3); Fa, Sp
This course is a study of modern methods of cryptography and their applications. Topics include the Data Encryption Standard, the RSA public-key cryptosystem, digital signatures, and quantum cryptography. Prerequisite: MATH 5150 with a grade of C or better. Previous NMHU MATH 519.
MATH 5250. Introduction to Real Analysis (3); Fa, Sp
This course gives students a solid background in theoretical graduate analysis, stressing the theory and deeper understanding of calculus. Students are introduced to proofs that motivate them toward clear thought and understanding of limits, continuity, differentiation, and series. This provides a rigorous training in mathematical thinking. Previous NMHU MATH 525.
MATH 5260. Intro to Complex Variable (3); Fa, Sp
This course is an introduction to the properties of analytic functions. Topics include mappings, limits, continuity, differentiation, Cauchy-Riemann equations, harmonic functions and branch points, definite integrals and the Cauchy-Goursat theorem, Cauchy integral formula, maximum modulus theorem, Liouville’s theorem, fundamental theorem of algebra, Taylor and Laurent series, residues and poles, analytic continuation and Poisson integral. Prerequisite: MATH 5250 with a minimum grade of C. Previous NMHU MATH 526.
MATH 5320. Abstract Algebra (3); Fa, Sp
Topics from groups, rings, and field theory. Previous NMHU MATH 532.
MATH 5350. Selected Topic in Mathematics (1 –4 VC); Fa, Sp
Course in a topic or topics in mathematics. May be repeated with change of content. Previous NMHU MATH 535.
MATH 5440. Matrix Theory with Applications (3); Fa, Sp
This course is a study of advanced topics in linear algebra and the theory of matrices with emphasis on computer-based applications. Topics include eigenvalues, eigenvectors, similarity, characteristic and minimal polynomials, diagonalizable matrices, and symmetric matrices, Jordan canonical form, vector and matrix norms, spectral radius, stable matrices, functions of matrices, nonnegative matrices and Perron-Frobenius theory, differential equations, stability, location of eigenvalues, Rayleigh quotient and Gersgorin’s theorem, matric polynomials, solvents and analytic matrix functions. Previous NMHU MATH 544.
MATH 5500. Seminar in Mathematics (1 –4 VC); Fa, Sp
Seminar course in a topic or topics in mathematics. Previous NMHU MATH 550.
MATH 5600. Applied Multivariate Statistics I (3); Fa, Sp
This course is an introductory matrix analysis for statistics, multivariate distributions, multiple regression, multiple analysis of variance and covariance, principal component analysis, and canonical correlations. Prerequisite: MATH 3200. A continuation of MATH 5500, including discriminant analysis, factor analysis, categorical techniques, distance concepts, and cluster analysis. Prerequisite: MATH 5500. Previous NMHU MATH 560.
MATH 5900. Independent Study (1 –4 VC); Fa, Sp
Independent study arranged with an instructor. Prerequisite: Permission of instructor. Previous NMHU MATH 590.
MATH 5920. Independent Research (1 –4 VC); Fa, Sp
Individual, directed research arranged with an instructor. Prerequisite: Permission of instructor. Previous NMHU MATH 592.