IntroductionThe Department of Computer Science and Engineering offers a program of graduate study leading to the Master of Science degree in Computer Science.
The program balances theory, software, hardware, and practice with degree requirements concentrated in the areas of theory and software. 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 the Master of Science in Computer Engineering degree and the Ph.D. in Computer Science and Engineering, as well as graduate certificates in Database Management and Design, Software Engineering, and Software Management.
AdmissionA student may be admitted to the Master of Science in Computer Science program with a bachelor's degree in computer science, or related areas and appropriate experience, and satisfaction of the admission requirements as set forth by the School of Graduate Studies.
Specific prerequisites for admission are shown below. Students may be admitted conditionally while making up minor deficiencies.
1. An accredited bachelor's degree with an overall minimum grade point average of 3.0 for regular graduate status. Students may be admitted conditionally if they have an undergraduate grade point average of 2.7 or above and at least a 3.0 grade point average in all courses in items 2 and 3 below.
2. Computer Science prerequisites: Data structures, operating systems, and computer organization. The materials covered in these classes are equivalent to CS 400, CS 433, and CEG 320.
3. Mathematics and Science Prerequisites: Introduction to calculus, one year of science, linear or matrix algebra, discrete mathematics, probability and statistics.
4. The Graduate Record Examination (GRE-the general test): a minimum combined score of 1050 on the verbal and quantitative exams is expected.
The GRE will be waived in the following cases: a) a person with a Wright State University BS or BA degree from the College of Computer Science and Engineering and Computer Science whose undergraduate GPA is above 3.3 and who is applying for a M.S. program and b) a person with a graduate degree in Engineering, Science, or Mathematics from an American institution who is applying for a M.S. program. The GRE is highly recommended for anyone who is or will be applying for graduate assistantships.
Degree RequirementsThe program requires forty eight graduate credit hours in Computer Science or Computer Engineering that include the Computer Science Core and the completion of either the thesis or non-thesis option requirements.
COMPUTER SCIENCE CORE
Distributed Computing: CEG 730
Programming Languages: CS 784
Computational Complexity: CS 740
Database Systems: CS 701
Completion of forty-eight graduate credit hours in an approved program of study, including twenty hours of formal coursework at the 700-800 level (CS 795, Independent Study, cannot be used to meet this requirement). Satisfactory completion of a Masters thesis is required in this option with a maximum of twelve hours of independent study and thesis work counted towards the degree.
Completion of forty-eight graduate credit hours in an approved program of study. The forty eight hours must include the core and at least sixteen additional hours of CS/CEG formal courses at the 700/800 level. A maximum of 4 hours of independent study may be counted toward the degree.
Courses: All CS and CEG graduate courses listed in the catalog, (with the exception of CS 600, and CEG 633), may be used to complete the credit hour requirements. Other courses may be used to satisfy the requirements only if they are listed in a program of study that has been approved by the department prior to enrollment in the course.
The Department of Computer Science and Engineering maintains a three C policy 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 to the Graduate School for dismissal at any time the students CS/CEG graduate GPA (including the repeated courses) falls below 3.0. Dismissal action will be taken by the School of Graduate Studies. The rule includes prerequisite courses taken for graduate credit (500/600 level), independent study, and thesis research. Note that repeating a course replaces the grade in the calculation of the GPA but does not remove it from consideration of this rule.
A maximum of 12 graduate credit hours may be transferred after admission to the computer science degree program by petitioning the Graduate Study Committee.
Students who have been employed as teaching or research assistants through the School of Graduate Studies are required to complete the thesis option.
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
Krishnaprasad Thirunarayan, semantic web: knowledge representation and reasoning, programming languages: specification, design and implementation
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
Yong Pei, distributed computing, multimedia system and networking, sensor network, information theory, bio-networks, distributed signal processing
Michael L. Raymer, evolutionary computation, pattern recognition, bioinformatics, protein structure modeling, molecular evolution, forensic bioinformatics, computational toxicology
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
Pascal Hitzler, semantic web, knowledge representation, automated reasoning, mathematical founddatins
Meilin Liu, embedded systems, compiler, loop transformation techniques, computer architecture, information security
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. 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 for students and 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 modern graduate research in such areas 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.
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. 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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