Program Description:
The Department of Computer Science and Engineering offers a program of graduate study leading to the Master of Science in Computer Engineering degree. The program balances theory, software, hardware, and practice with degree requirements concentrated in the areas of computer design and analysis. Most courses are offered in the late afternoon to allow practicing computer professionals to enroll in the program on a part-time basis.
A student may be admitted to the Master of Science in Computer Engineering program with the equivalent of an ABET accredited bachelor’s degree in computer engineering and satisfaction of the admission requirements as set forth by the Graduate School. Specific prerequisites for admission to the Master of Science degree program in Computer Engineering are shown below. Students may be admitted conditionally while making up minor deficiencies.
Students must have a bachelor’s degree in Computer Engineering from an accredited institution, 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 below.
Courses covering computer programming, data structures, theory of computation, digital circuits, computer organization, and operating systems. The material covered in these courses should be equivalent to, respectively, CS 5100 , CEG 6350 , and CEG 5200 at Wright State University.
Mathematics and science prerequisites: one year sequences in calculus and calculus-based physics, as well as knowledge of matrix or linear algebra, ordinary differential equations, probability, and statistics.
NOTE: The GRE will be waived for students applying for the Master’s program in the following cases: a) a person with a Wright State University BS or BA degree from the College of Engineering and Computer Science whose undergraduate GPA is above 3.3, b) a person with a graduate degree in Engineering, Science, or Mathematics from an American institution. The GRE is highly recommended for anyone who is or will be applying for graduate assistantships.
Admissions Requirements:
A student may be admitted to the Master of Science in Computer Engineering program with the equivalent of an ABET accredited bachelor’s degree in computer engineering and satisfaction of the admission requirements as set forth by the Graduate School. Specific prerequisites for admission to the Master of Science degree program in computer engineering are shown below. Students may be admitted conditionally while making up minor deficiencies.
- 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.
- Computer Science and Engineering prerequisites: Data structures, operating systems, and computer organization. The materials covered in these classes are equivalent to CS 400, CS 433, and CEG 320.
- Mathematics and Science Prerequisites: One year sequence in calculus, matrix or linear algebra, ordinary differential equations, a one year sequence in calculus based physics, and probability and statistics.
- The Graduate Record Examination (GRE-the general test): a minimum combined score of 298 on the verbal and quantitative exams is expected.
NOTE: The GRE will be waived for students applying for the Master’s program in the following cases: a) a person with a Wright State University BS or BA degree from the College of Engineering and Computer Science whose undergraduate GPA is above 3.3, b) a person with a graduate degree in Engineering, Science, or Mathematics from an American institution. The GRE is highly recommended for anyone who is or will be applying for graduate assistantships.
Facilities:
A 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 Visualization Laboratory, 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, bioinformatics, and cyber security.
Faculty:
Professors
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 (Graduate Program Director), 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 (Chair), evolutionary computation, pattern recognition, image processing, machine intelligence
Amit P. Sheth (Director of Kno.e.sis Center), semantic web; information integration & analysis; services science; workflow management; data & knowledge intensive applications in biomedical, health care, and national security domain
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
Associate Professors
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
Pascal Hitzler, semantic web, knowledge representation, automated reasoning, mathematical foundations
Meilin Liu, embedded systems, compiler, loop transformation techniques, computer architecture, information security
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
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
Assistant Professors
Keke Chen, secure and privacy-preserving computing, databases, data mining and information visualization, web science, and social computing
Junjie Zhang, cyber security
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