The M.S. degree has both research and professional tracks. The research track provides the student the opportunity to work on a thesis (applied or basic in nature) under the close supervision of a faculty adviser.
The minimum requirements for the research track are 24 credits of graduate course work and preparation and defense of a thesis on a topic in the student's primary area of interest. For the professional option, the minimum requirement is 30 credits of graduate course work. The M.S. degree program can usually be completed in 1 to 1½ years on a full-time basis.
Students can tailor their individual MS program to emphasize different aspects of Electrical Engineering:
More details about the specific programs and requirements can be found in the current Orientation Notes for Graduate Students.
Several applications of electrical engineering technology are being investigated, often in collaboration with faculty in the Department of Bioengineering and/or the University of Pittsburgh Medical School. These projects include modeling and analysis of postural control mechanisms, functional evaluation of patients with chronic pain, development of control strategies for heart-assist devices, analysis of electroencephalograms and source localization, electrocardiogram analysis, remote physiological sensing and fabrication of implanted physiological sensors.
Graduate course work in this area includes: computer architecture, microprocessor systems, VLSI design, design automation for VLSI, software engineering, computer networks, and automata theory. Faculty/student research includes projects in algorithm development, digital implementation of real-time systems, multiprocessor systems, parallel computer architectures, computer-aided engineering, optical computing, VLSI architectures, computer-aided design for VLSI, microprocessor systems, homogeneous and heterogeneous architectures, parallel performance modeling and analysis, cluster computing, and computer and communication networks. Department laboratories that support this research are the Optical Computing Systems Laboratory, Pittsburgh Integrated Circuits Analysis (PICA) Laboratory, the Pitt Parallel Computer Laboratory, the Network Communications Laboratory, the Jurenko Computer Architecture Laboratory, and the Swanson Embedded Computing and Interfacing Laboratory.
Graduate courses offered in this area include linear and nonlinear system theory, optimal control theory, computer control, optimization methods, and optimal stochastic systems. Faculty/student research in this area includes control system theory with emphasis on control of artificial organs, real-time computer control of power systems, and statistical process control.
The graduate electric power engineering program at the University of Pittsburgh offers comprehensive coursework covering all aspects of modern and future electric power systems. The curriculum provides a cross-section of the electric power system, from transmission and distribution, power electronic converters, to advanced control application and design. Close partnerships with industry collaborators has resulted in both co-developed course material, as well as guest lecturers who are leaders in their respective fields, providing students with an education that is both highly technical and highly relevant to their professional futures
Graduate courses are offered in the following topics: quantum electronics, semiconductor optics and devices, high-speed electronics devices, semiconductor lasers, monolithic integrated circuits, and fundamentals of semiconductor and quantum electronic devices. Current research projects are in microelectronics, semiconductor device modeling, computer-aided design, analog circuit design, linear and nonlinear optical devices, solid state lasers, high speed electro-optic modulators, electro-optical field sensors, phase conjugation, optoelectronic integrated devices, low dimensional structures, resonant tunneling, quantum well infrared detectors, semiconductor materials and devices, optoelectronic devices, integrated optics. Some of this research is supported by the Laser Laboratory and the Opto-electronics Laboratory.
Graduate courses are offered in digital image processing, topological algorithms for image processing, pattern recognition, and computer vision. Research is being conducted on the following topics: computer vision, topological algorithms and architectures, digital topology, pattern recognition, biomedical image processing, applications of wavelet transform, magnetic resonance imaging, imagery construction, and computation in medical imaging. Research in this area is supported by the Laboratory for Computer Vision and Pattern Recognition.
Graduate courses are offered in stochastic processes, digital signal processing, statistical signal processing, modern spectral estimation, time-frequency signal analysis, digital speech processing, digital communications, and information theory. Current research projects in this area are in motion analysis to relate body movements to pain, knowledge-based signal processing, statistical signal processing, multidimensional system theory, digital processing of speech signals, spectral estimation, neural networks, stochastic signal processing as applied to communications, image coding, optical processing, nonstationary signal processing, time-frequency distributions, biomedical signal analysis, machine fault monitoring, acquisition and analysis of electrical and magnetic data from the central nervous system, array signal processing, and geophysical applications. The Applied Signal and System Analysis Laboratory supports research in this area.