Welcome to the Electrical Engineering:Systems (EE:S) Graduate Program.Instructions, information and a link to the online application form.
EE:S is one of two graduate programs offered by the Electrical and Computer Engineering (ECE) Division; the other is Electrical Engineering (EE).
Whether you are interested in a master's or doctoral degree, we have a wide variety of courses, world-renowned faculty and cutting-edge research to give you the experience you need to succeed anywhere.
Please visit the page for current EE:S students for more specific information about your prospective program of study, and resources available to you at U-M. There are also special options for current U-M EECS undergrads wanting to apply to graduate school.
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Attention prospective students!
Attend the Engineering Graduate Symposium held each year in November. Prospective graduate engineering students will have the opportunity to attend the College's premier on-campus visitation program. The Symposium is free for all current and prospective graduate students who wish to attend. Travel Grants are available for prospective students who meet eligibility requirements.
This area covers power systems and energy processing (power electronics and electromechanical conversion). The focus is on establishing fundamental system properties, and using that knowledge to achieve performance enhancement through systematic design strategies. Projects include dynamic performance of wind generation systems, grid integration of plug hybrid electric vehicles, dynamics and control of microgrids, load control strategies, and robustness of large-scale power systems to parameter uncertainty.
Robots are evolving from stationary devices that perform manufacturing tasks to mobile, information gathering, computing, and decision making platforms. We are working on the modeling, estimation and control of multi-robot (multi-agent) systems for applications ranging from intelligent transportation networks to search and rescue. We are developing the fundamentals of computer vision, the science and technology of giving machines the ability to see, in order to perform real-world visual tasks such as autonomous navigation, visual surveillance, or content-based image and video indexing. We are also exploring the feedback control principles of bipedal robotic locomotion, with the goal of endowing machines with the ability to walk on two legs with the agility of a human.
Signal Processing students focus on the representation, manipulation, and analysis of signals, images, video, and other media. Current projects include: image reconstruction, restoration, and segmentation; fast algorithms; tomography and other inverse problems; wavelets and time-frequency distributions; image and video coding; steganography and watermarking; signal detection and target tracking in electro-optical, acoustic and radar remote sensing; pattern recognition and pattern matching; parameter estimation and performance bounds.
Applications include: bioinformatics; psychoacoustics; musical instrument sound synthesis and analysis; MIMO communications; packet switched networking; wireless sensor networks; neural measurements and analysis; medical imaging; and surveillance for security applications.
Much of the signal processing research is a collaborative activity within other areas of EECS, particularly in the areas of communication, electromagnetics, artificial intelligence, and biosystems. Furthermore there are active interdisciplinary collaborations with the departments of music, medicine, dentistry, biological sciences, genetics, mechanical engineering, nuclear engineering and radiation sciences, statistics, biostatistics, and mathematics.