Computer Science and Engineering Ph.D. Program
IntroductionThe Department of Computer Science and Engineering offers a program of graduate study leading to the Doctor of Philosophy degree in computer science and engineering. The Ph.D. degree is awarded for demonstrated, scholarly excellence in study and research that provides a significant contribution to the fields of computer science or computer engineering. The program requires a concentration of study and research in specific areas of computer science and engineering. Programmatic strength lies in the unique blend of faculty expertise, in the combination of theory with software and hardware design, and in the laboratory facilities available to the program.
Most courses are offered in the late afternoon to allow practicing computer professionals to begin the program on a part-time basis.
The department also offers Master of Science in Computer Science and Master of Science in Computer Engineering degrees, as well as graduate certificates in Database Management and Design, Software Engineering, and Software Management.
AdmissionStudents may be admitted to the Ph.D. program in Computer Science and Engineering with a baccalaureate degree or a masters degree in computer science, computer engineering, or a related area and appropriate experience; satisfaction of the admission requirements as set forth by the School of Graduate Studies; and a record that indicates potential for a career in computer science and engineering research, as evaluated by the departments admission committee.
Students should come to the program with a knowledge of higher-level programming languages, data structures, real time programming, computer organization, formal languages, operating systems, and computer systems design. It may be possible to make up minor background deficiencies after admission to the program by taking appropriate courses.
In addition, minimum expectations are a baccalaureate or master's degree from an accredited institution in computer science, computer engineering, or related discipline with a grade point average of at least 3.3 and a score on the Graduate Record Examination (GRE) of at least 1700. The Graduate Record Examination is not required of students with a master's degree from the Wright State University College of Engineering and Computer Science, provided that a grade point average of 3.6 or better was achieved.
There are approximately 30 active Ph.D. students currently in the department and those who were required to present GRE scores have an average value of 1923.
Degree RequirementsDoctor of Philosophy Degree in Computer Science and Engineering
A student entering the program with a Bachelor of Science or Bachelor of Arts degree must complete a minimum of 136 credit hours. A student entering the program with a masters degree in computer science, computer engineering, or a related field from a regionally accredited university must complete a minimum of 91 credit hours. The program must be completed with a minimum grade point average of 3.0.
The following course requirements must be satisfied in completing the necessary number of credit hours.
1. Course Requirements:
A student must complete a minimum of 76 hours of course work at the graduate level. CS 600/CEG 633 will not be counted toward meeting this requirement.
The 76 credit hours in courses must include:
At least 40 hours of formal computer science and computer engineering courses available to graduate students only (CS/CEG 700/800 level), including at least eight quarter hours of formal 800 level courses. A course other than those listed may be used to satisfy the graduate only course requirement if it is part of a coherent program and has received approval from the Graduate Studies Committee prior to enrollment in the course.
At least 24 hours of graduate level CSE technical electives including at least 8 hours of formal course work.
At least 12 credit hours of graduate courses outside of the CSE Department, e.g. mathematics or statistics, electrical engineering, psychology, biology, etc.
Courses that are co-listed as CS or CEG cannot be used toward this requirement except MTH 607, MTH 619, MTH 656, MTH 658, EE 619, EE 654, EE 656, EE 662 (formerly EE 658), EE 659, and HFE 665.
For the purposes of the course requirements given above, a formal course is defined as follows:
A formal course meets on a regularly scheduled basis throughout the quarter as specified in the quarterly university bulletin. In a formal course, a faculty member delivers a series of lectures and students are evaluated using a combination of projects, presentations, and examinations. Consequently, this excludes seminars, independent study, thesis research, dissertation research, principles of instruction, or other directed research hours. However, the 24 hours of graduate level CSE technical electives allows for 16 hours of independent study type courses, but not thesis or dissertation research.
2. Additional Requirements:
The students program of study must include:
A minimum of 2 credit hours in a Ph.D. Seminar (CS 891 or CEG 891)
Registration for the Ph.D. Qualifying Examination (CS 892 or CEG 892)
Registration for the Candidacy Examination (CS 894 or CEG 894)
Registration for the Dissertation Defense (CS 896 or CEG 896)
Registration for the 36 hours of Residency Research (CS 897 or CEG 897)
3. Qualifying Examination:
Students entering the Ph.D. program with a masters degree must demonstrate proficiency in computer science and engineering by passing the qualifying examination within five enrolled quarters of admission into the program. Students entering with a bachelors degree must pass the examination within eight enrolled quarters.
The qualifying examination is designed to ascertain the students depth of knowledge in selected areas of computer science and engineering, and explore the students ability to integrate concepts and ideas to form solutions for complex problems and applications.
The examination will cover three core areas of computer science and engineering:
1. Operating systems
2. Computer architecture
3. Mathematical foundations of
a. computer science
b. computer engineering
The student must take examinations in areas 1, 2, and 3a or 3b. The department maintains a syllabus for each examination. The content of the examinations is not directly tied to a set of formal courses that the student must complete prior to attempting the examination. Students who have completed graduate level course work in the three core areas should be able to pass the examination by reviewing materials described in the examination syllabi.
The qualifying examination will be offered twice a year, in the fall quarter and in the spring quarter. Students not passing the examination on the first attempt will be given a grade of U, but will be given one additional opportunity to pass the examination at the next available offering. Any student who fails to pass the examination on the second attempt will be dismissed from the program.
4. Residency Research:
A student must enroll in three quarters over two consecutive years of Residency Research (CS/CEG 897). A student will generally enroll in residency research after completing the Ph.D. Qualifying Examination. Enrollment in residency research prior to completion of the Qualifying Examination will be permitted only by the petition to the Graduate Studies Committee.
5. Course Grade Requirements:
Prior to taking the Candidacy Examination, a student must meet all of the following course grade requirements at the same time.
Out of the following three areas, a student must have:
1. at least three As in a concentration area,
2. at least one course from each of the other two areas,
3. at least a G.P.A. of 3.3 in each of the three areas
Students transferring directly to the Ph.D. program from another institution may count graduate-level courses with grades to meet the grade requirements through a petition process.
Area 1. Machine Intelligence and Human Computer Interaction
CS 711 Knowledge-Based Systems in AI
CS 712 Advanced Topics in AI
CS 714 Machine Learning I
CS 765 Foundations of Neurocomputing
CS 766 Evolutionary Computing
CS 767 Fuzzy Set Theory and Approximate Reasoning
CS 771 Natural Language Processing Techniques
CS 772 Advanced Natural Language Processing Concepts
CS 865 Advanced Topics in Soft Computing
CEG 724 Computer Vision
CEG 725 Computer Vision II
CEG 756 Robotics I
CEG 759 AI in Robotics
CEG 770 Computer Engineering Mathematics
Area 2. Database and Software Systems
CS 701 Database Systems and Design
CS 740 Computational Complexity and Algorithm Analysis
CS 774 Logic Programming
CS 776 Functional Programming
CS 780 Compiler Design and Construction
CS 781 Compiler Design and Construction II
CS 782 Compiler Design and Construction III
CS 784 Programming Languages
CS 801 Advanced Topics in Database Systems
CS 840 Advanced Topics in the Theory of Computation
CS 884 Advanced Topics in Programming Languages
CEG 730 Distributed Computing Principles
CEG 760 Advanced Software Engineering
CEG 763 Formal Methods in Software Engineering
CEG 830 Distributed Computing Systems
CEG 860 Object-Oriented Programming
Area 3. Computing Systems and Technologies
CS 716 Numerical Analysis I
CS 717 Numerical Analysis II
CS 735 Evaluation and Prediction of System Performance
CEG 720 Computer Architecture
CEG 728 Introduction to Optical Computing
CEG 729 Optical Computer Architectures
CEG 750 Microprocessors
CEG 751 Microprocessors II
CEG 752 VLSI Subsystem Design
CEG 754 VLSI Testing and Design for Testability
CEG 758 CMOS Analog IC Design
CEG 820 Computer Architecture II
6. Candidacy Examination:
The Candidacy Examination permits the student to present his/her proposed research to the dissertation committee and the public. The dissertation committee may be formed only after completion of the Qualifying Examination, but prior to the Candidacy Examination. It is the responsibility of the student to find a faculty member who agrees to be the dissertation director and who will supervise the students research. The dissertation director, in consultation with the dissertation committee, will determine when the student has identified a program of research suitable for a Ph.D. dissertation and is prepared to take the Candidacy Examination. The examination will consist of a public presentation of the proposed research and a question-and-answer period. The dissertation committee may also have an interrogatory session with the student that is closed to the public. Unanimous consent of the dissertation committee is required to pass the Candidacy Examination.
The research proposal must exhibit the students thorough background knowledge of the research area, indicate previous work in the area, and explicitly outline the proposed research to be undertaken in the dissertation.
7. Dissertation Defense:
In the Dissertation Defense, the student presents the results of his/her research to the dissertation committee and the public. The dissertation director, in consultation with the dissertation committee, will determine when the student has completed sufficient research to defend the dissertation.
The dissertation director is the chair of the Dissertation Defense. The examination consists of a public presentation of the students research and a question-and-answer period. The dissertation committee may also have an interrogatory session with the student that is closed to the public. Unanimous consent of the dissertation committee is required to pass the Dissertation Defense.
8. Time Limit:
Students must complete all the requirements for a doctoral degree within 10 years from the date that student was admitted to the Ph.D. program.
The department has a three C rule for graduate students. A graduate student who receives 9 or more credit hours of grades C, D, F, or U in computer science or computer engineering graduate courses will be recommended for dismissal from the program. The rule includes prerequisite courses taken for graduate study, independent study, and thesis or dissertation research. Dismissal action will be taken by the School of Graduate Studies.
FacilitiesA wide range of computing systems interconnected via the campus-wide network support all the degree programs in the department. Full Internet connectivity is provided from campus labs and from residence halls. A variety of high-end and special-purpose systems is available for research efforts through the Ohio Supercomputer Center. Wright State University is also an Internet 2 member. University and college systems include a variety of servers and workstations running current popular operating systems, including UNIX systems from SGI and Sun, and a variety of personal computer labs featuring current versions of Windows and Mac OS. Department facilities provide specialized systems and support equipment tailored to specific curriculum and research areas. These include an SGI Origin 2000 system with 32 parallel processors, an NCR Teradata 4850, an 8-processor SGI Onyx 2 system, a Linux-based Operating Systems and Internet Security lab, and a variety of workstations and personal computers providing software tools for project design and development. The program has laboratories dedicated to student and faculty study and research in the areas of assistive technology, vision interfaces and systems, medical image analysis, parallel and distributed computing, evolvable hardware, database systems, data mining, mobile information and communications, software engineering, artificial intelligence, adaptive vision, advanced computer networking, and bioinformatics.
Nikolaos G. Bourbakis, (director, Information Technology Research Institute), information security (encryption, information hiding, compression), computer systems (distributed, formal languages, processors, modeling), applied artificial intelligence (knowledge representation, planning, learning, autonomous agents, natural language processing), machine vision and image processing (architectures, languages, algorithms), Robotics (navigation, grasping, 3-D space maps, walking)
James E. Brandeberry, P.E. (dean), digital electronics, microprocessors, system theory
Chien-In Henry Chen (Department of Electrical Engineering), computer aided design, simulation and testing of VLSI circuits and systems, specifically digital, analog, and mixed-signal design synthesis and testability, timing analysis and optimization for very-deep sub-micron ICs, and chip design for signal processing, communication, and networking
Soon M. Chung, database, data mining, xml, parallel and distributed processing, multimedia, computer architecture
Forouzan Golshani, (chair) digital video processing, image analysis, indexing and classification, correlated media synthesis, multimedia information systems, information security
A. Ardeshir Goshtasby, image and video understanding, medical image analysis, geometric modeling, curves and surfaces, multimodal image capture and fusion
Jack Jean, high-performance computer architectures, machine intelligence
Terry A. McKee (Department of Mathematics and Statistics), graph theory
Kuldip S. Rattan (Department of Electrical Engineering), fuzzy control, robotics, digital control systems, prosthetic/orthotics and microprocessor applications
Mateen M. Rizki, evolutionary computation, pattern recognition, image processing, machine intelligence
Thomas A. Sudkamp, fuzzy set theory, soft computing, approximate reasoning
Guozhu Dong, database systems, data mining and knowledge discovery, data warehousing and integration, data cubes and OLAP, bioinformatics, knowledge management, information and internet security
Travis E. Doom, bioinformatics, digital design automation, computer architecture and operating systems, optimization theory, and engineering education
Daniel Lee, computer/communication networks, wireless communications, multimedia transport
Prabhaker Mateti, distributed computing, Internet security, formal methods in software design
Krishnaprasad Thirunarayan, semantic web: knowledge representation and reasoning, programming languages: specification, design and implementation
Natsuhiko Futamura, algorithms for high performance computing, parallel algorithms, computational biology, search algorithms, distribution independent spatial data structure and algorithms
John C. Gallagher, neural networks, computational neuroscience, machine intelligence, genetic algorithms, evolvable hardware, autonomous robotics
Yong Pei, information theory, communication systems and networks, image/video compression and communications, and distributed signal processing
Michael L. Raymer, evolutionary computation, machine learning, pattern recognition, computational biology, protein structure and function, protein-water interactions, bioinformatics
Bin Wang, computer communication and networks, providing quality of service assurance, quality of service routing, service provisioning in dense wavelength division multiplexing (DWDM) optical networks, wireless and mobile networks, network security (including countering denial of service attacks), stochastic modeling, queuing analysis of systems, network simulation, protocol design and development
Graduate AssistantshipTeaching assistantships are available on a competitive basis for students who have established strong academic credentials and can demonstrate good communication and teaching skills. A number of departmental research assistantships are awarded annually based on exceptional performance or potential. Additional graduate support is available in the form of assistantships associated with research projects of the faculty. Scholarships are also available from the Dayton Area Graduate Studies Institute (DAGSI), and through the Information Technology Research Institute. Application forms for these assistantships and scholarships are available from the department for students admitted to the graduate program.
ResearchA steadily increasing number of funded research projects support modern graduate research in such areas as database systems, knowledge-based systems, knowledge discovery from databases, parallel and distributed computing, machine intelligence, hardware systems and communications, neural networks, software systems and engineering, computer graphics and visualization, human-computer interaction, optical computing, and robotics. A strong research faculty in the Department of Computer Science and Engineering is assisted by qualified research faculty in mathematics, statistics, and electrical engineering.
Recent and current sources of research support include federal agencies, military agencies, and local industries. Research at Wright State University is not limited to on-campus laboratory facilities. Several industrial laboratories, Wright-Patterson Air Force Base laboratories, and the Major Shared Resource Center at Wright-Patterson Air Force Base are involved in joint research efforts with the university. The Information Technology Research Institute (ITRI) is closely associated with the Department of Computer Science and Engineering in seeking and pursuing research and development opportunities with state and federal agencies and local information-intensive industries. In addition, the universitys Wright Center of Innovation for Advanced Data Management and Analysis is a focal point for new technologies that advance data management solutions and data management innovation.
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