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The Master of Science degree in Computer Engineering is designed to offer students the opportunity to prepare for leadership roles in careers with industry, government, or educational institutions.
Students enrolled in the M.S. degree program in Computer Engineering will have two different options to obtain their degree: (1) Thesis Option and (2) Nonthesis Option. A thesis option is offered for students who want the opportunity to obtain expertise in research and who may be interested in pursuing the doctoral degree in computer engineering or electrical engineering. A nonthesis option is offered for students who want a practical industrial applications-oriented degree
The research in our graduate programs at the Department of Electrical and Computer Engineering mainly focuses on five concentrations:
Communications:Fiber optic communications, fiber optic sensors, coding and error correction, control of communication networks, positioning and navigation algorithms, GPS, signal processing for communications, digital communications systems, wireless mobile communications, information theory, and signal detection and estimation.Computer and Digital Systems:Parallel and distributed computing, routing in computer networks, network intrusion detection, computer architecture, ASICs, RISC processors, microprocessor based systems, VLSI design and testing, CAD tools, HDL modeling and FPGA implementation, computer graphics hardware and software parallelism, visualization techniques, information science, optimization and forecasting, digital systems, multimedia and network processors, low power VLSI systems, and reconfigurable computing.Signal and Image Processing:Signal and image processing, visual communication, and quantum information processing and communication, signals and systems, tomographic imaging, processing biomedical images FISH (Fluorescence In Situ Hybridization), theory of fast unitary transforms, robust linear and nonlinear filters, morphological image processing, statistical signal processing, Bayesian methods, sampling-based approaches.Systems and Control:Intelligent systems, neural networks and fuzzy systems, adaptive learning, data mining, networking, diagnosis and prognosis, health monitoring, and robotics and automation, Complex Systems, Computational Intelligence, System of Systems Engineering, Mechatronics, Neuro-fuzzy techniques, robotics and intelligent networks/systems, robust and adaptive control, stabilization of nonlinear systems, optimal control, homogeneous systems theory, aerospace systems and power plants.Microelectronics and Microdevices:This concentration area provides students with balanced training in theory and experimentation in the areas of analog and mixed signal integrated circuit design, microsystems technology (MEMS), RF and Microwave devices. Research emphasis covers such diverse topics as wireless transceivers, data converters, power management, VLSI, micromirror arrays, MEMS microwave devices, Bio-MEMS, photonic crystals, microfluidics, sensor arrays, microchemical reactors, micropropulsion and energy harvesting schemes. Graduates are well qualified to seek employment in semiconductor manufacturing, aerospace, telecommunications, petrochemical industry, food and chemical processing, microelectronics research and development, health care and other industries requiring analog circuitry, sensing schemes or the application of microdevices.
Research stipends and scholarships will be posted to the College of Engineering Scholarships page as they become available.
Our graduate courses are offered mostly in afternoon and evening. About half of courses are taught in the afternoon (2 p.m.–5 p.m.) and another half in the evening 5 p.m.–8:15 p.m.).
After graduation, our MS and PhD graduates are employed as engineers or researcher in research firms and industries. Some of our former doctorate students are working in universities as faculty members.
Please visit the Graduate Admissions Deadline page for a list of application deadlines
Department of Electrical and Computer Engineering
Building: Biotechnology Science and Engineering Building (BSE), Room 1.500
One UTSA Circle
San Antonio, TX 78249
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