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. It may be possible to make up minor background deficiencies after admission to the program by taking appropriate courses.
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 1150. 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.
Degree RequirementsCredit Requirements:
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 following course requirements must be satisfied in completing the necessary number of credit hours.
A student must complete a minimum of 76 hours of course work at the graduate level. CS 600 and CEG 633 will not be counted toward meeting this requirement.
The 76 credit hours in courses must include:
Completion of either the Computer Science or Computer Engineering core courses.
At least 40 hours of formal computer science and computer engineering courses available to graduate students only (CS/CEG 700/800 level). A course other than those listed may be used to satisfy the graduate only course requirement only 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. Up to 12 hours of thesis research (CS 799 or CEG 799) taken at Wright State in the successful completion of a Masters thesis may be included in these hours.
At least 12 credit hours of graduate courses outside of the CSE Department e.g. mathematics or statistics, electrical engineering, psychology, biology, etc. that provide a coherent second area of specialization that complements the students research area.
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 659, EE 662, 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.
Graduate Core Curriculum
The core curriculum is designed to ensure that students completing a graduate degree have demonstrated competence at the graduate level in a breadth of core topics in the discipline.
CS core curriculum:
Areas: Associated Course Distributed Computing CEG 730
Database Systems CS 701
Programming Languages CS 784
Computational Complexity CS 740
CEG core curriculum
Areas: Associated Course
Distributed Computing CEG 730
Computer Networks CEG 702
Computer Architecture CEG 720
Computer Engineering Mathematics CEG 770
2. Additional Requirements:
A student's program of study must include:
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:
The successful completion of the Qualifying Examination demonstrates that the student has attained a breadth of knowledge in computer science or computer engineering at the graduate level. The examination may be passed either by outstanding performance on the core courses or through a series of written examinations. Students have two opportunities to pass the Qualifying Examination
The First Examination
Within the first two quarters of entering the Ph.D. program and prior to taking any of the core courses, the student must indicate whether he/she will take the Qualifying Examination by coursework or by a written examination. Student selecting to qualify for the Ph.D. program by the core curriculum must declare whether they will complete the Computer Science or the Computer Engineering core.
Examination by Core Curriculum
The student passes the Qualifying Examination if he/she completes the core curriculum courses
1. within the 6 quarters of entering the program, and
2. achieves a 3.75 grade point average or greater in the core courses (no repeat of classes).
The written examination will cover the topics from the core curriculum courses. If this option is chosen, the student must take the examination within 4 quarters of entering the program. The exam will consist of a two-hour examination on each of the areas. A grade point average of at least 3.75 on the examinations is required to pass.
Students not passing the examination on the first attempt will be given one additional opportunity to pass at the next available offering of the written examination. Any student who fails to pass the examination on the second attempt will be dismissed from the program.
The second examination will be a written examination over the students selected core curriculum. The student is required to take the exam in each area in which he/she did not receive an A on the first examination. The grades obtained on the second examination will replace those from the first examination. A grade point average of at least 3.75 on the two combined examinations is required to pass.
WSU Masters Students
Students entering the Ph.D. program with a Masters in Computer Science or Computer Engineering from Wright State will be credited with passing the Qualifying Examination if their performance on the core courses in the Masters program satisfies the criteria for passing the Qualifying Examination by coursework described above.
Students must register for CS 892 or CEG 892 to take the written examination. Students will be notified of the results within two weeks of the final session of the examination.
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. 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.
6. 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.
7. Publication Requirement:
The student must have at least one journal paper of which he/she is the first author accepted for publication from his/her dissertation research. The dissertation committee will specify peer reviewed journals appropriate for the satisfaction of this requirement.
A paper published in a highly selective conference may satisfy this requirement with the agreement of the dissertation committee and the Director of the Ph.D. Program.
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, X, 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. A variety of high-end and special-purpose systems are available for research through the Ohio Supercomputer Center. University and college systems include a variety of servers and workstations running current operating systems including Linux, Mac OS, and Windows. Department facilities provide specialized systems and support equipment tailored to specific curriculum and research areas. These include a Linux-based Operating Systems and Internet Security lab, an Immersive Visualization and Animation Theater lab, and a variety of workstations and personal computers providing software tools for project design and development. The program also has access to one of the most advanced visualization and presentation environments in the nation, the Appenzeller AudioVisualization Lab, located in the Joshi Research Center. The Department has laboratories dedicated research in assistive technologies, RFID, 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, semantic web services oriented computing, scientific workflows, business process management, and bioinformatics.
Nikolaos G. Bourbakis, (Director, Assistive Technologies Research Center), information security (encryption, information hiding, compression, forensics), 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), assistive technology (blind, deaf, paraplegic), biomedical (bioimaging, cells modeling, neuromorphic systems, brain surgery, brain biometrics, endoscopy, human-eye)
Chien-In Henry Chen (Department of Electrical Engineering), computer aided design, verification and testing of VLSI circuits and systems, specifically in digital analog, mixed-signal designs, and system-on-a-chip (SoC), VLSI and FPGA implementation of signal processing and communication systems like GPS and digital wideband receivers
Soon M. Chung, database, data mining, Grid computing, parallel processing, XML, multimedia, computer architecture
Guozhu Dong, database systems, data mining and knowledge discovery, data warehousing and integration, data cubes and OLAP, bioinformatics, knowledge management, information and internet security
Arthur A. Goshtasby, computer vision, computer graphics, geometric modeling, medical image analysis
Jack Jean, high-performance computer architectures, RFID applications
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
Amit P. Sheth, semantic web; information integration & analysis; services science; workflow management; data & knowledge intensive applications in biomedical, health care, and national security domain
Thomas A. Sudkamp (Chair), fuzzy set theory, soft computing, approximate reasoning
Travis E. Doom, bioinformatics, digital design automation, computer architecture and operating systems, optimization theory, and engineering education
John M. Emmert (Department of Electrical Engineering), physical VLSI design in nanoscale technologies, physical design automation for VLSI, mixed-signal design, built-in self-test, and fault tolerance for VLSI systems
John C. Gallagher, Adaptive and Evolvable Hardware, Autonomous Robotics, neural networks, machine intelligence, computational neuroscience
Prabhaker Mateti, distributed computing, Internet security, formal methods in software design
Michael L. Raymer, evolutionary computation, pattern recognition, bioinformatics, protein structure modeling, molecular evolution, forensic bioinformatics, computational toxicology
Krishnaprasad Thirunarayan, semantic web: knowledge representation and reasoning, programming languages: specification, design and implementation
Bin Wang, communication networks, wireless sensor and mobile networks, UWB, dynamic spectrum access, cognitive radio, information theory, network coding, algorithm design, quality of service, dense wavelength division multiplexing (DWDM) optical networks, network security, network modeling, analysis, simulation, protocol design and development
Keke Chen, secure and privacy-preserving computing, databases, data mining and information visualization, web science, and social computing
Meilin Liu, embedded systems, compiler, loop transformation techniques, computer architecture, information security
Yong Pei, distributed computing, multimedia system and networking, sensor network, information theory, bio-networks, distributed signal processing
Shaojun Wang, machine learning, natural language processing, information theory
Thomas Wischgoll, scientific visualizations, biomedical imaging, flow visualization, information visualization, computer graphics, image processing and feature extraction
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. Departmental Graduate Research Assistantships are also available and are associated with research projects of the faculty. They are normally awarded by or based on the recommendation of individual faculty. Application forms for these assistantships are available from the Department or on web at http://www.cs.wright.edu/cse/. To be considered for an assistantship, a student must be admitted to a graduate program or have an application on file with the Graduate School. Assistantships are also available from the Dayton Area Graduate Studies Institute (DAGSI). Applications are available from DAGSI at http://www.dagsi.org.
ResearchA steadily increasing number of funded research projects support graduate research in areas such as medical imaging, multimedia systems and applications, biometrics, assistive technologies, soft computing and evolvable hardware, intelligent agents and robotics, data mining and databases, bioinformatics, networking and mobile computing, wireless and internet security, RFID applications, the semantic web, and services science. A strong research faculty in the Department of Computer Science and Engineering is assisted by qualified research faculty in mathematics, statistics, and electrical engineering.
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. In addition, the new Joshi Research Center and daytaOhio are focal points for new technologies that advance data management solutions and data management innovation.
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