GRADUATE STUDY IN COMPUTER SCIENCE Department of Computer Science The University of North Carolina at Chapel Hill Graduate admissions information for spring and fall 2004 Updated: September 2003 ============================================================== This is an electronic version of our printed admissions brochure, which is updated once a year. If, after reading this brochure you cannot find answers to all of your questions, or need more information, please contact Janet Jones, Student Services Manager, at 919-962-1900 Mondays through Fridays from 9 a.m. - 4 p.m. Eastern Standard Time, or send e-mail to jones@cs.unc.edu. For the most up-to-date admissions information please visit our Graduate Admissions Web pages: www.cs.unc.edu/Admissions/ ============================================================== CONTENTS Our Department and the Community * The University and Community * Our Department The Faculty and their Research * Our Faculty * Research Areas Degree Programs and Admissions Information * Degree Programs and Requirements * Admissions Requirements and how to Apply * Financial Support * Deadlines Courses for Graduate Students Facilities and Research Laboratories * Facilities * Research Laboratories Recent Ph.D. Graduates Contact Us ============================================================== OUR DEPARTMENT AND THE COMMUNITY The University and Community The University of North Carolina at Chapel Hill (UNC–Chapel Hill) was the first state university to open its doors to students, in 1795. With its reputation for providing high-quality education at an affordable price, the school is consistently ranked one of the nation’s very best public universities. The 689-acre central campus, with its 200-year-old trees and stately colonial brick buildings, is among the most beautiful in the country. Of the approximately 26,000 students enrolled, around 10,000 were graduate and professional students. Chapel Hill (population 51,000) is a scenic college town located in the heart of North Carolina, where small-town charm mixes with a cosmopolitan atmosphere to provide students with a rich and varied living experience. The town and the surrounding area offer many cultural advantages, including excellent theater and music, museums, and a planetarium. There are also many opportunities to watch and to participate in sports. The Carolina beaches, Outer Banks, Great Smoky Mountains National Park, and Blue Ridge Mountains are only a few hours’ drive away. The Research Triangle of North Carolina is named for the triangle formed by the area’s three major research universities: the University of North Carolina in Chapel Hill, Duke University in Durham, and North Carolina State University in Raleigh. The universities have a combined enrollment of more than 63,000 students; have libraries with more than twelve million volumes with interconnected catalogs; and have national prominence in a variety of disciplines. Collectively, they conduct more than $600 million in research each year. At the center of the Triangle lies Research Triangle Park (RTP), set in 7,000 acres of North Carolina pinelands. RTP is the largest research park in the United States, and includes more than 140 organizations—corporations, government agencies, and institutes—that employ approximately 45,000 people. The collaboration between the academic and corporate communities creates a synergy unsurpassed in the scientific arena. The growth of the Department of Computer Science at UNC–Chapel Hill is a consequence of the region’s economic development. Our department sees its task as contributing to the research and educational needs of a growing regional concentration of high technology, and to the national and international computer science communities. Our Department The Department of Computer Science at UNC–Chapel Hill was one of the first in the United States to be established as an independent computer science department. It was founded in 1964 by Dr. Frederick P. Brooks Jr. Many of his founding philosophies still guide us. He strongly believed in creating an atmosphere of cooperation, in which students are seen as colleagues to faculty members. The department’s primary missions are research and graduate and undergraduate teaching. It offers B.S., M.S., and Ph.D. degrees in computer science. The B.S. curriculum is a traditional liberal arts-based computer science degree. The M.S. and Ph.D. curricula are oriented toward the design and application of real computer systems and toward that portion of theory that guides and supports practice. The M.S. program prepares highly competent and broadly skilled practitioners. A majority of the master’s graduates work in industry, in companies ranging from small start-up operations to government labs and large research and development corporations. The Ph.D. program prepares teachers and researchers for positions with universities, government research laboratories, and industry (see below for a list of our recent Ph.D. graduates). Academic employment ranges from four-year colleges, where teaching is the primary focus, to positions at major research universities. Currently, our faculty includes 28 tenured and tenure-track faculty, 7 research faculty, 19 adjuncts, and 3 lecturers. We also have a large technical and administrative support staff (approximately 40 people). Most of our approximately 160 graduate students are full time. Students contribute to nearly every aspect of the department’s operation. In addition to taking a wide variety of courses, they have the opportunity to participate in groundbreaking research, to teach, to attend research group meetings, and to serve on committees that affect all aspects of life in the department. The Computer Science Students Association sponsors both professional and social events and represents the students in departmental matters. Its president is a voting member at faculty meetings. Our student population is very diverse in terms of both geographic origin and previous degrees. While computer science and mathematics represent the largest number of undergraduate majors among our graduate students, others majored in physics and engineering, or in subjects in the social sciences and the humanities. Following are the median credentials for the 35 first-year students who began our program in fall 2003: Quantitative GRE: 90th percentile Verbal GRE: 83rd percentile (86th with non-native speakers excluded) Analytical GRE: 90th percentile GPA (undergraduate): 3.6/4.0 ============================================================== THE FACULTY AND THEIR RESEARCH Our Faculty For more details: www.cs.unc.edu/People/Faculty/ James Anderson, Professor and Director of Graduate Admissions; Ph.D., Texas at Austin, 1990. Distributed and concurrent algorithms, real-time systems, fault tolerant computing, formal methods. Sanjoy K. Baruah, Associate Professor; Ph.D., Texas at Austin, 1993. Scheduling theory, real-time and safety-critical system design, computer networks, resource allocation and sharing in distributed computing environments. Gary Bishop, Professor; Ph.D., North Carolina at Chapel Hill, 1984. Hardware and software for man-machine interaction, 3-D interactive computer graphics, virtual environments, tracking technologies, image-based rendering. Frederick P. Brooks Jr., Kenan Professor; Ph.D., Harvard, 1956. 3-D interactive computer graphics, human-computer interaction, virtual worlds, computer architecture, the design process. Peter Calingaert, Professor Emeritus; Ph.D., Harvard, 1955. Prasun Dewan, Professor; Ph.D., Wisconsin-Madison, 1986. User interfaces, distributed collaboration, software engineering environments, object-oriented databases, mobile computing. Henry Fuchs, Federico Gil Professor; Ph.D., Utah, 1975. High-performance graphics hardware, 3-D medical imaging, head-mounted displays, virtual environments. Guido Gerig, Taylor Grandy Professor of Computer Science and Psychiatry; Ph.D., Swiss Federal Institute of Technology, 1987. Image analysis, shape-based object recognition, 3-D object representation and quantitative analysis, medical image processing. John H. Halton, Professor; D.Phil., Oxford, 1960. Applications of combinatorial and probabilistic methods and of scientific and mathematical analysis to computational, scientific, and engineering problems. Kye S. Hedlund, Associate Professor; Ph.D., Purdue, 1982. Computer-aided design, computer architecture, algorithm design and analysis, parallel processing. Kevin Jeffay, S. S. Jones Distinguished Term Professor; Ph.D., Washington (Seattle), 1989. Real-time systems, operating systems, distributed systems, multimedia networking, computer-supported cooperative work, performance evaluation. Jasleen Kaur, Assistant Professor; Ph.D., Texas at Austin, 2002. Design of networks and operating systems, specifically resource management for providing service guarantees, Internet measurements, overlay and peer-to-peer networks, and router architectures. Anselmo A. Lastra, Associate Professor and Director of Graduate Studies; Ph.D., Duke, 1988. Interactive 3-D computer graphics, hardware architectures for computer graphics. Ming C. Lin, Professor; Ph.D., Berkeley, 1993. Physically based and geometric modeling, applied computational geometry, robotics, distributed interactive simulation, virtual environments, algorithm analysis. Gyula A. Magó, Professor Emeritus; Ph.D., Cambridge, 1970. Dinesh Manocha, Professor; Ph.D., Berkeley, 1992. Geometric and solid modeling, physically based modeling, computer graphics, simulation-based design, symbolic and scientific computation, computational geometry. Ketan Mayer-Patel, Assistant Professor; Ph.D., Berkeley, 1999. Multimedia systems, networking, multicast applications. Leonard McMillan, Associate Professor, Ph.D., North Carolina at Chapel Hill, 1997. Computer graphics, image processing, computer vision, multimedia, microelectronics, computer organization. Stephen M. Pizer, Kenan Professor; Ph.D., Harvard, 1967. Image analysis and display, human and computer vision, graphics, numerical computing, medical imaging. Maria Papadopouli, Assistant Professor; Ph.D., Columbia, 2002. Applications for mobile, wireless networks, ad hoc, and sensor networks; pervasive computing. David A. Plaisted, Professor; Ph.D., Stanford, 1976. Mechanical theorem proving, term rewriting systems, logic programming, algorithms. Marc Pollefeys, Assistant Professor; Ph.D., Leuven (Belgium), 1999. Computer vision, image-based modeling and rendering, image and video analysis, multiview geometry. Diane Pozefsky, Research Professor (joint Research Scientist appointment with the Renaissance Computing Institute); Ph.D., North Carolina at Chapel Hill, 1979. Computer-supported cooperative work, distributed systems, mobile computing, networking, software engineering and environments. Jan F. Prins, Professor and Chairman; Ph.D., Cornell, 1987. Parallel algorithms, languages and architectures, high-level programming languages, compilers, formal techniques in program development, algorithms for structural biology and bioinformatics. Timothy L. Quigg, Lecturer and Associate Chairman for Administration and Finance; M.P.A., North Carolina State, 1979. Intellectual property rights, industrial relations, contract management, research administration. Daniel A. Reed, Chancellor's Eminent Professor and Director of the Renaissance Computing Institute (RENCI), Ph.D. 1983, Purdue University. Montek Singh, Assistant Professor; Ph.D., Columbia, 2001. High-performance and low-power digital systems, asynchronous circuits and systems, system-on-a-chip design, and VLSI CAD. F. Donelson Smith, Research Professor; Ph.D., North Carolina at Chapel Hill, 1978. Computer networks, operating systems, distributed systems, multimedia, computer-supported cooperative work. John B. Smith, Professor; Ph.D., North Carolina at Chapel Hill, 1970. Computer-supported cooperative work, hypermedia systems, World Wide Web architecture and programming, Java object storage and access. Jack S. Snoeyink, Professor; Ph.D., Stanford, 1990. Computational geometry, algorithms for geographical information systems and structural biology, geometric modeling and computation, algorithms and data structures, theory of computation. Donald F. Stanat, Professor Emeritus; Ph.D., Michigan, 1966. David Stotts, Associate Professor and Associate Chairman for Academic Affairs; Ph.D., Virginia, 1985. Computer-supported cooperative work, hypermedia, software engineering and formal methods, programming languages and concurrency, interoperable distributed systems. Martin Styner, Research Assistant Professor (joint appointment with Department of Psychiatry); Ph.D. 2001, UNC-Chapel Hill. Russell M. Taylor II, Research Associate Professor; Ph.D., North Carolina at Chapel Hill, 1994. 3-D interactive computer graphics, virtual worlds, distributed computing, scientific visualization, human-computer interaction. Leandra Vicci, Lecturer and Director of the Microelectronic Systems Laboratory; B.S., Antioch (Ohio), 1964. Information processing hardware: theory, practice, systems, and applications. Jeannie M. Walsh, Lecturer; M.S., Oklahoma State, 1984. Computer education; social, legal, and ethical issues concerning information technology. Wei Wang, Assistant Professor; Ph.D., UCLA, 1999. Data mining, database systems, bioinformatics. Stephen F. Weiss, Professor; Ph.D., Cornell, 1970. Information storage and retrieval, natural language processing, communications and distributed systems, computer-supported cooperative work. Gregory F. Welch, Research Associate Professor; Ph.D., North Carolina at Chapel Hill, 1997. Human-machine interaction, 3-D interactive computer graphics, virtual/augmented environment tracking systems, shared virtual environments and telecollaboration. Mary C. Whitton, Research Associate Professor; M.S., North Carolina State, 1984. Virtual and augmented reality systems for data visualization, computer graphics system architectures. William V. Wright, Research Professor Emeritus; Ph.D., North Carolina at Chapel Hill, 1972. Interactive systems for supporting scientific research, molecular graphics, architecture and implementation of computing systems. Adjunct Faculty Hussein Abdel-Wahab, Adjunct Professor; Ph.D., Waterloo, 1976. Computer-supported cooperative work, multimedia systems and communications, distance learning, distributed systems, operating systems, networking. Stephen R. Aylward, Adjunct Assistant Professor; Ph.D., North Carolina at Chapel Hill, 1997. Computer-aided diagnosis, computer-aided surgical planning, statistical pattern recognition, image processing, neural networks. Elizabeth Bullitt, Adjunct Professor; M.D., Colorado at Denver, 1975. Computer-aided surgery, computer-aided diagnosis. Siddhartha Chatterjee, Adjunct Associate Professor; Ph.D., Carnegie Mellon, 1991. High-level programming languages, compilation for highly parallel machines, object-oriented programming, parallel algorithms and architectures. Bert Dempsey, Adjunct Assistant Professor; Ph.D., Virginia, 1994. Computer-supported cooperative work, computer networks, multimedia communications, digital library systems. Nick England, Adjunct Research Professor; E.E., North Carolina State, 1974. Systems architectures for graphics and imaging, scientific visualization, volume rendering, interactive surface modeling. John G. Eyles, Adjunct Research Associate Professor; Ph.D., North Carolina at Chapel Hill, 1982. Graphics architectures, rapid system prototyping, virtual environments, VLSI-based system design. Mark Foskey, Adjunct Research Assistant Professor; Ph.D., California, San Diego, 1994. Computer-aided surgical planning, computer-aided diagnosis, geometric computation. M. Gail Jones, Adjunct Associate Professor; Ph.D., North Carolina State, 1987. Science education, gender and science, high-stakes assessment nanotechnology education, haptics and learning. Sarang C. Joshi, Adjunct Assistant Professor; D.Sc., Washington (St. Louis), 1998. Image analysis, medical image processing, computer vision, computational anatomy. J. Stephen Marron, Adjunct Professor; Ph.D., UCLA, 1982. Smoothing methods for curve estimation. Steven E. Molnar, Adjunct Associate Professor; Ph.D., North Carolina at Chapel Hill, 1991. Architectures for real-time computer graphics, VLSI-based system design, parallel rendering algorithms. Andrew B. Nobel, Adjunct Associate Professor; Ph.D., Stanford, 1992. Statistical analysis of microarrays, analysis of Internet traffic, nonparametric interference, pattern recognition: clustering and clarification. Lars S. Nyland, Adjunct Associate Professor, Ph.D., Duke, 1991. High-performance computing, hardware systems, computer graphics and image analysis, geometric modeling and computation, parallel algorithms, parallel computer architecture, programming languages, program transformation and optimization techniques, scientific computing, real-time systems, distributed systems. John Poulton, Adjunct Research Professor; Ph.D., North Carolina at Chapel Hill, 1980. Graphics architectures, VLSI-based system design, design tools, rapid system prototyping. Julian Rosenman, Adjunct Professor; Ph.D., Texas at Austin, 1971; M.D., Texas Health Science Center at Dallas, 1977. Computer graphics for treatment of cancer patients, contrast enhancement of poor quality X rays. Diane H. Sonnenwald, Adjunct Associate Professor; Ph.D., Rutgers, 1993. Collaboration among multidisciplinary, cross-organizational teams, collaboration across distances, collaboration technology, human information behavior, digital libraries. Richard Superfine, Adjunct Associate Professor; Ph.D., 1991, Berkeley. Condensed-matter physics, biophysics, microscopy. Sean Washburn, Adjunct Professor; Ph.D., 1982, Duke. Condensed-matter physics, materials science. Research Areas Our faculty conduct research in a broad range of research areas. Following is a quick reference index to their interests. Algorithms and Complexity Theory Agarwal, Anderson, Baruah, Chatterjee, Edelsbrunner, Halton, Plaisted, Snoeyink Assistive Technology Bishop, Welch Bioinformatics and Computational Biology Brooks, Prins, Snoeyink, Wang Computer Architectures Brooks, Chatterjee, England, Eyles, Hedlund, Lastra, Molnar, Nyland, Poulton, Prins, Singh, Wright Computer Graphics, Image Analysis and Computer Vision Aylward, Bishop, Brooks, Bullitt, England, Eyles, Fuchs, Gerig, Joshi, Lastra, Lin, Manocha, Molnar, Nyland, Pizer, Pollefeys, Poulton, Rosenman, Snoeyink, Superfine, Taylor, Welch, Whitton, Wright Computer-Supported Cooperative Work Abdel-Wahab, Dempsey, Dewan, Jeffay, Mayer-Patel, Papadopouli, Pozefsky, F. D. Smith, J. B. Smith, Sonnenwald, Stotts, Weiss Databases and Data Mining Wang Distributed Systems Abdel-Wahab, Anderson, Baruah, Dewan, Jeffay, Kaur, Mayer-Patel, Papadopouli, Pozefsky, F. D. Smith, Stotts, Taylor, Washburn Geometric Modeling and Computation Agarwal, Brooks, Edelsbrunner, England, Gerig, Halton, Joshi, Lin, Manocha, Nyland, Pizer, Pollefeys, Snoeyink, Vicci, Wright Hardware Systems and Design Bishop, England, Eyles, Fuchs, Hedlund, Lastra, Molnar, Nyland, Poulton, Singh, Superfine, Vicci, Welch, Wright Human-Machine Interaction Bishop, Brooks, Dewan, England, Eyles, Fuchs, Jones, Lastra, Lin, Pizer, Pollefeys, Rosenman, F. D. Smith, J. B. Smith, Sonnenwald, Stotts, Superfine, Taylor, Vicci, Washburn, Welch, Whitton, Wright Hypertext F. D. Smith, J. B. Smith, Stotts, Wang, Weiss Mobile Computing Papadopouli, Pozefsky The Monte Carlo Method Halton Multimedia Systems Abdel-Wahab, Dempsey, Dewan, Jeffay, Kaur, Mayer-Patel, Papadopouli, F. D. Smith, J. B. Smith, Stotts Networking Baruah, Dempsey, Jeffay, Kaur, Mayer-Patel, Papadopouli, Pozefsky, F. D. Smith, Wang Parallel Computing Anderson, Chatterjee, Eyles, Fuchs, Halton, Manocha, Molnar, Nyland, Poulton, Prins, Singh, Vicci Programming Language Design and Implementation Chatterjee, Dewan, Nyland, Plaisted, Prins, Stotts Real-Time Systems Abdel-Wahab, Anderson, Baruah, Fuchs, Jeffay, Kaur, Rosenman, F. D. Smith, Taylor, Washburn Software Engineering and Environments Aylward, Bullitt, Dewan, Jeffay, Pozefsky, Prins, Stotts, Wang Theorem Proving and Term Rewriting Plaisted ============================================================== DEGREE PROGRAMS AND ADMISSIONS INFORMATION Overview of Degree Programs and Requirements Graduate Curriculum. A flexible course of study for the M.S. and Ph.D. degrees focuses on areas of choice and accommodates differences in students’ backgrounds. The two degree programs share a basic distribution requirement of four courses chosen from theoretical, systems, and applied subject areas. The Ph.D. program includes work in specialized areas, preparation for teaching, and active involvement in advanced research. Master of Science. An M.S. candidate must earn 30 semester hours of credit in courses numbered 100 or higher, of which up to 6 hours may be transferred from another institution or graduate program, and of which 18 hours must be completed in our department. Satisfactory completion of the distribution requirement provides 12 hours of credit. The remaining credits are earned in areas of specific interest, and may include course work, as needed, to address the following requirements: * The technical writing requirement may be satisfied in one of three ways: (1) by taking our technical writing course, COMP 291, (2) by writing a thesis, or (3) by writing a technical document in either academic or nonacademic work that has been reviewed and accepted (this may include a previously written thesis or dissertation). * The program product requirement may be satisfied by taking our software engineering course, COMP 145, or by presenting satisfactory documentation of previous experience with the development of a significant software system. * The background preparation requirement reflects the body of material that is prerequisite to our graduate courses. Courses needed, if any, to satisfy this requirement are decided in consultation with the candidate’s adviser, course instructors, and the graduate studies committee. A thesis is optional; if one is written, it counts for six hours. A comprehensive exam is required and has two possible forms: (1) satisfactory completion of an integrative paper (this also satisfies the technical writing requirement when written as part of COMP 291), or (2) an oral exam covering material from the courses in the candidate’s program of study. While either exam is sufficient for the M.S. program, the integrative paper is required for the Ph.D. program. A student with an assistantship generally completes the M.S. degree in four semesters or less. For the complete M.S. official degree requirements, see: www.cs.unc.edu/Admin/AcademicPrograms/Masters/MastersReqOfficial.html Doctor of Philosophy. Admission to the Ph.D. program is by oral qualifying examination and recommendation of the faculty. There is no credit hour requirement for the Ph.D. program, but a Ph.D. candidate must complete courses to satisfy the distribution requirement and any needed background preparation, and must write an integrative paper. A Ph.D. candidate proposes an individual program of study, typically 15 to 18 hours. The program of study includes a primary and secondary concentration in computer science, training in mathematics and a supporting program of external courses or a foreign language. Previous course work can be used to satisfy much of the program of study. A candidate must also satisfy the program product requirement, teach a course, participate in the technical communication seminar, pass an oral examination in the proposed dissertation area, and submit and defend a dissertation that presents an original contribution to knowledge. The normal time needed to complete the degree by a full-time student with an assistantship is five years. Distribution Requirement. The distribution requirement requires satisfactory completion of four courses from the list below, with at least one course from each area. Grades earned in these four courses must satisfy additional requirements according to the degree program (M.S. or Ph.D.). Formal * COMP 202: Algorithm Analysis * COMP 244: Programming Languages * COMP 247: Distributed and Concurrent Algorithms * COMP 250: Scientific Computation Systems * COMP 204: Software Design and Implementation * COMP 240: Compilers * COMP 242: Operating Systems * COMP 243: Distributed Systems Applied * COMP 203: Parallel and Distributed Computing * COMP 206: Computer Architecture and Implementation * COMP 235: Images, Graphics, and Vision * COMP 261: Elements of Hardware Systems Integrative Paper. An integrative paper is a survey of three or more technical papers that span multiple sub-fields of computer science and have a common thread. The integrative paper is written in one semester and is organized as an issue-based survey of approximately 5,000 words, emphasizing the integration of concepts found in the subject papers. Faculty members can suggest suitable collections of papers, but students may propose a collection of subject papers as well. Two faculty members must agree to read the integrative paper for style and content. The student follows a schedule of milestones for drafts and revisions. Both faculty members must accept the final revision for the integrative paper requirement to be satisfied. Concurrent registration in our technical writing class, COMP 291, is recommended but not required. The satisfactory completion of an integrative paper satisfies the technical writing requirement. For the complete Ph.D. official degree requirements, see: www.cs.unc.edu/Admin/AcademicPrograms/Doctoral/DoctoralReqOfficial.html Admissions Requirements and how to Apply Admission to the department is highly competitive. Although we welcome promising students from all disciplines, entering students must have a substantial background in both mathematics and computer science. This background normally includes at least six semester courses in mathematics and six in computer science. We consider knowledge of the following subjects to be essential preparation for our graduate program: * differential and integral calculus; * discrete mathematics: sets, relations, functions, algebra; * linear algebra or matrix theory; * mathematical probability, preferably calculus-based; * structured programming techniques; * data structures and abstract data types; * computer organization. Most entering students have studied all but two or three of the following subjects, which are required preparation for our graduate program: * design and analysis of algorithms; * formal languages and automata theory; * databases; * operating systems; * compilers; * digital logic techniques; * numerical computing methods; * programming languages; * software engineering. Students who are admitted but who have not completed all the requirements must complete them after admission. Preference is given to applicants who are solidly prepared, especially in mathematics. Previous Degrees. A baccalaureate degree is required, with a grade point average of at least B (3.0/4.0); most entering students have a GPA of more than 3.5. For more information on our recently enrolled students’ credentials, please see the section on “Our Department” (above). GRE. High scores on all three parts of the General Aptitude Test of the Graduate Record Examination are also recommended: a minimum of 80th percentile on the verbal and 90th percentile on the quantitative and analytical sections is recommended (a score of 5 is recommended for the Writing Assessment). In recent years, most entering students have averaged in the 90th percentile or higher on each of the three sections. Allowances are made in interpreting the verbal test scores of applicants whose native language is not English. Although GRE Advanced Test scores are not required, applicants are encouraged to take the advanced test in computer science, mathematics, engineering, or physics, as appropriate. TOEFL. Applicants whose native language is not English must submit TOEFL scores. We give preference to applicants who score above 640. Applicants from Australia, Bahamas, Canada (except Quebec) England, Ghana, Ireland, India, Jamaica, New Zealand, Nigeria, Scotland, St. Vincent and the Grenadines, Trinidad, Tobego, and Wales are exempt from the TOEFL requirement and should not submit test scores. Also exempt from the TOEFL requirement are those who have received a degree from a university in the United States. Personal Statement. Each applicant must submit a short personal statement directly to the department. The statement should include: * objectives in pursuing graduate study; * identification of fields within computer science in which the applicant has a particular interest; * information that is relevant to the applicant’s qualifications for graduate study but that has not been included already in the application (e.g. major academic projects, papers presented or published, and non-academic computer experience); * an informative title or a brief description of any course listed on the applicant’s transcript without a title (or with a vague title such as “Mathematics II”); * a list of all courses taken or planned that do not yet appear on a transcript; * an e-mail address, if available. It should be between a half page and two pages long. Recommendations. Three letters of recommendation are required. Letters written by an applicant’s present or former professors are usually more informative than those written by employers or colleagues. Sponsorship. Because of the large number of applicants, the department’s faculty members are unable to provide individual assessments of an applicant’s chances for admission. Applicants cannot improve their chances of admission by finding a faculty sponsor within the department, because all admissions decisions are made by a faculty committee that reviews all applications, ranks the applicants by overall merit, and makes decisions on admission and financial support based on the application material submitted. In particular, students are not admitted by research project directors; contacting individual faculty members whose research is of interest has no effect on one’s chances of being admitted. How to Apply. Admission is based solely on merit. The University of North Carolina is an affirmative action, equal opportunity institution. Prospective applicants who clearly surpass the minimum requirements are encouraged to apply. You can submit an electronic application or write for application materials to: The Graduate School The University of North Carolina at Chapel Hill Campus Box 4010, 200 Bynum Hall Chapel Hill, N.C. 27599-4010 USA Phone: (919) 966-2611 web: http://gradschool.unc.edu/ The Graduate School’s web site includes information on applying and on-line application forms. Domestic applicants (U.S. citizens and resident aliens) should check http://gradschool.unc.edu/applicant_dom.html. International applicants should refer to http://gradschool.unc.edu/applicant_intl.html. Candidates Day. Each spring, the department invites those applicants who have been admitted to the graduate program for the fall semester and who are currently living in the United States for a two-day visit to Chapel Hill. The prospective students learn about the research opportunities open to them and meet with individual faculty members and current graduate students. Financial Support During the academic year, most of our students are supported by assistantships and fellowships. The stipend for research and teaching assistantships for the nine-month academic year 2004–2005 is $14,500 (20 hours a week). Also, at no cost to them, students are covered by a comprehensive major medical insurance program, underwritten by Blue Cross/Blue Shield of North Carolina. Full-time summer employment on a research project is normally available to students who would like to receive support. The rate for summer 2005 will be $765 per week (40 hours) for 10 to 12 weeks. This will produce a combined annual financial package for our graduate assistants of approximately $23,680. Students with assistantships qualify for a Graduate Student Tuition Grant and pay no tuition. They are, however, responsible for paying student fees of approximately $619 per semester. Graduate Student Tuition grants typically cover M.S. students for four semesters of study and Ph.D. students for ten semesters of study. Annual living costs for single graduate students in the Chapel Hill area are estimated to be $13,000 or higher. On-campus housing is available for both single and married students. The department provides a $500 educational fund each semester to any student who receives a competitive fellowship not granted by UNC–Chapel Hill. The fund may be used for education-related expenses, including books, journals, travel, computer supplies and accessories, and professional memberships. The department also awards a $1,500 supplement each semester to nonservice fellowship holders who join a research team. To apply for an assistantship, the applicant should check the appropriate item on the admissions application form. Applicants for assistantships are automatically considered for all available fellowships. Students can expect continued support, contingent on satisfactory work performance and academic progress. Students are not assigned to specific research projects or teaching assistant positions immediately upon being admitted to the department. Assignments are made just prior to the start of each semester, after faculty members and students have had an opportunity to meet and to discuss their interests. Students are encouraged to gain professional experience through summer internships with companies in the Research Triangle area or in other parts of the country. Deadlines Applications for fall admission, complete with test scores, a personal statement, all transcripts, and recommendations, should be received by the Graduate School no later than 1 January. To ensure meeting that deadline, applicants are encouraged to take the Graduate Record Examination (GRE) no later than December. Early submission of applications is encouraged. International applicants should consider completing their applications earlier to allow time for processing financial and visa documents. ============================================================== COURSES FOR GRADUATE STUDENTS Upper-level Undergraduate Courses (graduate credit) 114 Foundation of Programming (4) 117 Introduction to WWW Programming (3) 118 Advanced WWW Programming (3) 120 Computer Organization (3) 121 Data Structures (4) 122 Algorithms and Analysis (3) 123 Internet Services and Protocols (3) 130 Files and Databases (3) 136 Introduction to Computer Graphics (3) 140 Compilers (3) 142 Operating Systems (3) 144 Programming Language Concepts (3) 145 Software Engineering Laboratory (3) 170 Applications of Natural Language Processing (3)* 171 Natural Language Processing (3)* 181 Models of Languages and Computation (3) 190 Topics in Computer Science (1–3) Graduate Core Courses 202 Algorithm Analysis (3) 203 Parallel and Distributed Computing (3) 204 Software Design and Implementation (3) 205 Scientific and Geometric Computation (3) 206 Computer Architecture and Implementation (3) Advanced Graduate Courses 228 Advanced Analysis of Algorithms (3) 230 Database Management Systems (3) 231 Introductory Computer Graphics (1) 232 Real-Time Systems (3) 233 Discrete Event Simulation (3)* 235 Images, Graphics, and Vision (3) 236 Computer Graphics (3) 238 Advanced Image Synthesis (3) 239 Exploring Virtual Worlds (3) 240 Compilers (3) 241 Internet Architecture and Performance (3) 242 Operating Systems (3) 243 Distributed Systems (3) 244 Programming Languages (3) 245 Functional Programming (3) 246 Logic Programming (3) 247 Distributed and Concurrent Algorithms (3) 248 Semantics and Program Correctness (3) 249 Multimedia Networking (3) 250 Scientific Computation (3)* 252 Monte Carlo Method (3) 254 Image Processing and Analysis (3) 255 Recent Advances in Image Analysis (3) 256 Computer Vision of our 3D World (3) 257 Visual Solid Shape (3) 258 Geometric and Solid Modeling (3) 259 Physically Based Modeling and Simulation (3) 261 Elements of Hardware Systems (3) 265 Advanced Computer Architecture (3) 267 Advanced Computer Implementation (3) 268 VLSI Systems Design (3) 269 Advanced Design of VLSI Systems (3) 273 Neural Networks (3) 275 Expert Systems (3) 277 Visual Perception (3) 282 Mechanized Mathematical Inference (3) 286 Topics in Discrete Optimization (3)* 288 Information Theory (3)* 289 Error-Correcting Codes (3)* 290 Topics in Computer Science (1–3) 291 Professional Writing in Computer Science (3) 321 Technical Communication in Computer Science (1) 322 Seminar in Professional Practice (1) 323 Seminar in Research (1) 324 Computers and Society (1) 390 Research Seminar in Computer Science (0.5–3) Practicum (0.5) Numbers following course title represent credit hours *Non-computer science courses cross-listed with our Department ============================================================== FACILITIES AND RESEARCH LABORATORIES Facilities Sitterson Hall, which opened in 1987, is the home of the Department of Computer Science at UNC–Chapel Hill. The building, named for former University Chancellor J. Carlyle Sitterson, provides 74,000 square feet of sophisticated, state-of-the-art research facilities and office space for all members of the department. It is organized in “clusters” to create research communities featuring shared laboratories and open conference areas to facilitate interaction among students and faculty. Included are the 60-seat C. Hugh Holman video teleclassroom, named for the former provost and dean of the Graduate School who was instrumental in establishing this department; a 125-seat auditorium; the Lib Moore Jones Faculty Conference Room, named for the department’s first secretary; a reading room; and various research laboratories, conference areas, and study areas. Graduate students have access to all of the department’s research and teaching facilities, including specialized research laboratories for graphics and image processing; computer building and design; and collaborative, distributed, and parallel systems. The laboratories, offices, conference areas, and classrooms are bound together by the department’s fully integrated, distributed computing environment. General Computing Environment. The department’s computing environment includes approximately 700 computers, ranging in performance from 12 million instructions per second (MIPS) to more than 25 billion instructions per second (BIPS). These systems are integrated by means of high-speed networks and by software that is consistent at the user level over the many architectural platforms. In addition, our research laboratories contain specialized equipment and facilities. Every student is assigned to a two- to four-person office. Each student is assigned a computer. General computing systems include approximately 600 Intel-based personal computers, 4 SGI computers, 26 Sun workstations, and 42 Apple Macintosh systems. Main memory on each computer ranges from 16 megabytes to 16 gigabytes. Total disk space exceeds 22 terabytes. Parallel Computing Facilities. The parallel computing facilities include an SGI Power Onyx machine; a Reality Monster, a 32 processor SGI Onyx2(TM) Infinite Reality2(TM) workstation; and several Sun multiprocessor systems. The Reality Monster has 16 gigabytes of main memory and 8 InfiniteReality2 graphics subsystems. Software Environment. Our primary software environment consists of the Windows 200 operating system; Linux, Solaris, and several other flavors of UNIX; the AFS file system, and the X Window System. Languages most commonly used include J++, C++, Java, C, and Turing. Document preparation is usually accomplished via PC and Macintosh systems. Our extensive software holdings are continually evolving. Network Environment. The department’s computer systems are connected to one another by a high-speed data network. The network was upgraded in 2002 to provide switched 100 megabit connections to every desktop, plus fiber, video, and multiple voice and data connections in each office. Special purpose systems and switches use gigabit connections. The campus Internet II connection is in Sitterson Hall and provides even higher speeds for applications that require it. The department’s network is connected to the North Carolina Research and Education Network (NC-REN), a statewide network that links research and educational institutions. Our two-way video classroom and teleconference room allow connection to any institution served by the network. Courses are shared among the institutions via two-way, interactive video teleclassing. NC-REN substantially widens the course, concentration, and advising opportunities available to students at participating universities. The network in Sitterson Hall also incorporates a satellite earth station. Libraries. Our students have access to the entire University library system, which includes a major academic affairs library, and numerous satellite libraries containing almost five million books and periodicals, as well as to libraries at nearby N.C. State and Duke universities, with a unified on-line searching capability. The Brauer Library located on the third floor of Phillips Hall, next door to Sitterson Hall, is a satellite library with extensive holdings in computer science, mathematics, operations research, physics, and statistics. Research Laboratories The Collaboratory supports research and teaching in computer-supported cooperative work, distributed and real-time systems, hypermedia, and web-based distributed systems. Research conducted in this laboratory is motivated by the driving problem of creating computer and communication systems to aid collaboration in teams of technical professionals working in physically separate locations. Projects include exploring the use of the World Wide Web, Java, and virtual environments to support collaboration; flexible coupling of related, but distinct, collaboration tools; and applying natural adaptation techniques to improve real-time multimedia communication. Specialized equipment includes facilities for research in multimedia—including both analog and digital video and audio systems—and in virtual environments. The Graphics and Image Laboratory supports research and teaching in the broad areas of computer graphics and image processing, including virtual and augmented environments, medical image processing, computer vision, scientific visualization, geometric modeling, graphics hardware, and pattern recognition. The laboratory is equipped with both commercial and custom devices for image analysis, image capture, high-performance image generation, spatially-immersive and head-worn image display, wide-area tracking, interaction, force feedback, and telecollaboration. Both lab equipment and space is shared between graphics and image research. Noteworthy research instruments are a Reality Monster, a 32 processor SGI Onyx2TM Infinite Reality2TM workstation, which has 16 gigabytes of main memory and 8 InfiniteReality2 graphics subsystems, and the HiBall system, a UNC-built wide-area tracker that provides sub-millimeter-accuracy tracking over an area larger than 500 square feet. Our first-rate facilities enable us to pursue a wide range of research topics, and our tradition of collaborating with users wanting to use computers to solve real-world problems in their own disciplines ensures a steady stream of interesting computer science problems. The Hardware Systems Teaching Laboratory is an integral part of the department’s curriculum in information processing hardware systems. The lab offers specialized utilities, including grounding, static control, compressed air, vacuum, and isolated power, and is equipped with the necessary instruments and tools for hands-on experimentation with components, circuits, transducers, and integration of entire systems. The lab has both workbench and conferencing space and accommodates both individual and team experiments, as well as systems design projects. Researchers continue to equip the lab with the latest analytical and fabrication technologies so that students have the best access to current technology. The Microelectronic Systems Laboratory (MSL) provides facilities and expertise for building prototypes of a variety of microtechnology-based systems. It enables research in the use of information processing technology in a multidisciplinary context. Custom-designed and/or off-the-shelf VLSI and conventional components are used to build systems from small-scale proof-of-concept prototypes through systems of significant size and complexity, such as the Pixel-Planes family of graphics supercomputers and the HiBall tracker for virtual environments. A technical staff of research faculty and engineers provides continuity of know-how and economically leverages new research thrusts. Sophisticated facilities and equipment are maintained to support work in electronic, optical, mechanical, and other relevant technologies. A network of component suppliers and service organizations is also maintained, as well as an extensive in-house suite of design automation tools. The MSL is an exceptional academic prototyping laboratory with an established, world-class track record. Researchers in the Multimedia Networking Laboratory study operating system and network support for performance-sensitive applications, such as streaming media systems, distributed virtual environments, and collaborative systems. Research focuses on media adaptations for end-system response to congestion, router mechanisms for realizing better-than-best-effort forwarding services, performance studies of active router queue mechanisms, and Internet traffic modeling, characterization, and generation. The laboratory houses approximately 60 Intel-based personal computers running a wide range of production and experimental operating systems, and 10 local area network switching and routing devices. The machines are interconnected via dynamically configurable and partitionable networks running at 10, 100, and 1,000 Mbps. The laboratory is also directly connected to the North Carolina Networking Initiative’s GigaPOP, a Cisco DPT fiber ring spanning the Research Triangle Park region of North Carolina, operating at speeds of up to OC-48 (2.4 Gbps), and interconnecting the Triangle with the Abilene Internet2 network. ============================================================== RECENT PH.D. GRADUATES Doctoral degrees awarded since August 2002. For a complete list of Ph.D. graduates, visit www.cs.unc.edu/Publications/Dissertations.html. Alexandra A. Bokinsky (Aug. 2003), “Visualization of Multiple Spatial Variables with Data-Driven Spots.” (F. P. Brooks Jr.) Goopeel Chung (Dec. 2002), “Log-based Collaborative Infrastructure.” (P. Dewan) Christopher L. Dwyer (May 2003), “Self-Assembled Computer Architecture: Design and Fabrication Theory.” (R. M. Taylor) Gentaro Hirota (Dec. 2002), “An Improved Finite Element Contact Model for Anatomical Simulations.” (H. Fuchs) Aditi Majumder (Aug. 2003), “The Emineoptic Function: A Comprehensive Framework for Modeling and Correcting Color Variations Across Multi Projector Displays.” (G. F. Welch) David Kirk McAllister (Aug. 2002), “A Generalized Surface Appearance Representation for Computer Graphics.” (A. A. Lastra) Pablo Mauricio Rademacher (May 2003), “Measuring the Perception of Realism in Images.” (G. Bishop) Ramesh Raskar (Dec. 2002), “Projector-based Three Dimensional Graphics.” (H. Fuchs, G. F. Welch) Vassil R. Roussev (Aug. 2003), “Flexible Sharing of Distributed Objects Based on Programming Patterns.” (P. Dewan) Nicholas M. Vallidis (Aug. 2002), “WHISPER: A Spread Spectrum Approach to Occlusion in Acoustic Tracking.” (G. Bishop) Michele Aylene Clark Weigle (Aug. 2003), “Investigating the Use of Synchronized Clocks in TCP Congestion Control.” (K. Jeffay) Andrew Thomas Wilson (Dec. 2002), “Spatially Encoded Image-Space Simplifications for Interactive Walkthrough.” (D. Manocha) Ruigang Yang (Aug. 2003), “View-dependent Pixel Coloring—A Physically-based Framework for 2D View Synthesis.” (G. F. Welch) Paul Alexander Yushkevich (May 2003), “Statistical Shape Characterization Using the Medial Representation.” (S. M. Pizer) ============================================================== CONTACT US General Department Information Phone: (919) 962-1700 FAX: (919) 962-1799 E-mail: info@cs.unc.edu Web: www.cs.unc.edu Graduate Admissions and Graduate Studies Phone: (919) 962-1900 FAX: (919) 962-1799 E-mail: admit@cs.unc.edu Department of Computer Science The College of Arts and Sciences The University of North Carolina at Chapel Hill CB #3175, Sitterson Hall Chapel Hill, NC 27599-3175 USA ==============================================================