Programs of Study

The School of Computing offers programs leading to the Master of Science degree and the Doctor of Philosophy degree in computer science.

MS As a candidate for the MS degree, you will be required to satisfactorily complete an approved program of at least 30 graduate hours. If you have minor deficiencies in certain academic areas, you may be admitted provisionally. If you have several academic deficiencies, you may be required to satisfactorily complete prerequisite work as a post-baccalaureate student prior to admission. There are three options available to satisfy the degree requirements: the research experience, the research paper and the thesis. These options will allow you to count zero, three or six hours respectively of research credit toward the 30-hour requirement. You may take up to six hours of approved courses in areas outside the department.

As a student, you will have significant exposure to application areas that emphasize the integration of the core areas and have the opportunity to participate in a research project under the direction of a faculty member. In addition, you will also acquire advanced programming skills as a part of the program.

PhD Requirements for a PhD degree include a comprehensive examination, 12 hours of course work beyond the MS and the writing and successful defense of the doctoral dissertation. The comprehensive examination is a portfolio review in which the candidate must establish both core competencies in computer science and the potential for success in research.

Student Group

Of the MS program’s 60 students, roughly 80 percent are men; 90 percent attend full time; and 50 percent are international students. Of the 40 PhD students in the School

of Computing, 75 percent are men; 70 percent attend full time; and 25 percent are international students.

Student Outcomes

Most MS graduates find employment in the high-technology industry. Recent graduates have taken positions with DreamWorks, AT&T, Cisco, EMC, IBM, Intel, Lucent, Microsoft, Nortel, Qualcomm and Sun Microsystems. Starting salaries range from the mid-$60,000s to as high as $80,000 per year or more.

Facilities

The School of Computing maintains a network of more than 150 UNIX-based systems. These include Sun and Intel-based workstations and servers running the Solaris and Linux operating systems. Systems are distributed among three general use labs, two instructional labs, several research labs and graduate student offices. Areas supported by the research labs include graphics and virtual reality, operating systems, ATM and Gigabit networking and software engineering.

Financial Aid

Financial support is available through research assistantships associated with grants and contracts, teaching assistantships and graduate fellowships. Students with assistantships generally are expected to work an average of 20 hours each week while taking nine credit hours per semester. In addition to a stipend, students with an assistantship receive a tuition remission. Alternative employment opportunities for well-qualified applicants are sometimes available.

Research

Some of the school’s research areas are listed below. For more information on these and other research initiatives, visit www.cs.clemson.edu.

• Virtual Reality Eye Tracking (VRET) Lab

One current VRET project is the development of a high-impact, hands-on virtual reality model of the aircraft inspection and maintenance process. Use of virtual reality technology will enable educators to create and students to experience the complex aircraft maintenance environment in a classroom, a setting where it has not yet been successfully created using traditional multimedia-based technologies.

• Resolve Software Research Group (RSRG)

The goal of RSRG is to facilitate specification, design, development and analysis of verifiably correct software systems from reusable components. Group members address a variety of foundational and practical software engineering and programming language issues.

• Dependable Systems Research Group (DSRG)

Members of DSRG study the design, deployment and management of unattended, long-lived applications at scale.

• Institute for Modeling and Simulation

The institute’s goal is to further knowledge by using models and simulations in education, industry and research. This includes research in computational science.

• Discrete Algorithms and Self-Stabilizing Algorithms

Discrete algorithms are algorithms designed for objects such as trees, graphs and sequences. Another area of focus is self-stabilizing algorithms. The traditional approach in designing fault-tolerant distributed protocols assumes a maximum number of faults and involves a worst-case design by fault masking. Self-stabilizing algorithms make no assumptions about initial data and need no global coordination, so they can recover from many arbitrary faults. These algorithms have applications in ad hoc networks.

• Re-coloring Images

Color images usually have gamuts that span three dimensions, typically parameterized as red, green and blue. Some important applications, such as printing on grayscale printers and re-coloring images for viewing by color-deficient observers, require a reduction in gamut dimension. The effort focuses on techniques for preserving image information content in the face of such reductions.

• Lattice-Boltzmann Models for Rendering

Lattice-Boltzmann methods are computational alternatives to finite-element methods for solving coupled systems of

partial differential equations. The advantages over standard techniques lie in ease of implementation, straightforward parallelization and an ability to handle inter-facial dynamics and complex boundaries. Several difficult problems in rendering, including cloud dynamics and photon transport, now appear amenable to these methods.

Faculty Listing

• Timothy A. Davis, Associate Professor; PhD, North Carolina State. Graphics, parallel and distributed computing.

• Brian C. Dean, Assistant Professor; PhD, MIT. Algorithms, combinatorial optimization.

• Andrew T. Duchowski, Associate Professor; PhD, Texas AandM. Visual perception, HCI, graphics, eye tracking, VR, computer vision, image and video processing.

• Robert M. Geist III, Professor; PhD, Notre Dame. Systems modeling, performance evaluation, reliability modeling, graphics.

• Sebastien Goasguen, Assistant Professor; PhD, Arizona State University. Distributed systems, middleware, grid security.

• Wayne D. Goddard, Associate Professor; PhD, Natal (South Africa); PhD, MIT. Algorithms, combinatorics, mobile networks.

• Harold C. Grossman, Associate Professor; PhD, Michigan State. Programming language theory, design and implementation; software development methodology.

• Jason O. Hallstrom, Assistant Professor; PhD, Ohio State. Software engineering, design patterns, runtime maintenance, programming languages.

• Sandra M. Hedetniemi, Professor; PhD, Virginia. Data structures, analysis of algorithms.

• Stephen T. Hedetniemi, Professor; PhD, Michigan. Design and analysis of algorithms, parallel algorithms, computational complexity and combinatorial optimization.

• David P. Jacobs, Professor; PhD, Missouri-Columbia. Algorithms, algebraic computation.

• Feng Luo, Assistant Professor; PhD, Texas at Dallas. Bioinformatics, biological data mining, biological databases.

• Krishna P. C. Madhavan, Assistant Professor; PhD, Purdue. Semantic grid, web technologies, cyberinfrastructure, natural language processing, engineering and science education.

• A. Wayne Madison, Associate Professor; PhD, Virginia. Operating systems, performance measurement and evaluation.

• Brian A. Malloy, Associate Professor; PhD, Pittsburgh. Languages, compilers, parallel processing, software maintenance and testing, simulation modeling.

• James J. Martin, Assistant Professor; PhD, North Carolina State. Computer networking, Internet protocols and issues, network security.

• John D. McGregor, Associate Professor; PhD, Vanderbilt. Software engineering, graphical systems, object-oriented development.

• Roy P. Pargas, Associate Professor; PhD, North Carolina. Web, Mobile PC and Tablet PC applications; development of software pedagogical tools for the classroom.

• Murali Sitaraman, Professor; PhD, Ohio State. Software engineering, reusable software.

• Mark K. Smotherman, Associate Professor; PhD, North Carolina. Computer architecture, superscalar processors, reliability.

• Pradip K. Srimani, Professor; PhD, Calcutta. Distributed systems, parallel algorithms, mobile computing.

• Dennis E. (Steve) Stevenson, Associate Professor; PhD, Clemson. Computational science, numerical analysis, computation theory.

• James (Zijun) Wang, Assistant Professor; PhD, Central Florida. Multimedia, database systems, operating systems, distributed computing.

• Kenneth A. Weaver, Lecturer; PhD, Clemson. Student performance and pedagogies, student services technologies.

• James M. Westall, Professor; PhD, North Carolina. Performance modeling of computer systems and networks, operating systems, computer networks.

• Damon L. Woodard, Assistant Professor; PhD, Notre Dame. Computer vision, digital image processing and analysis, computer vision based biometric systems.