Contact the department on the World Wide Web home page at http://www.eece.maine.edu.

The Electrical and Computer Engineering Department offers the Master of Science and the Ph.D. degrees in Electrical Engineering. Thesis and non-thesis options are available for the M.S. degree in Electrical Engineering. For a non-thesis degree, a minimum of 30 semester hours of course work is required. Thesis options require 30 credit hours of which six credits of ECE 699 shall be devoted to individual study with a member of the graduate faculty. This work must culminate in the preparation of a written thesis on a significant problem of common interest and an oral defense of the thesis. To obtain a M.S. degree in Electrical Engineering, a student must have at least a GPA of 3.0 for all courses taken as a graduate student.

A completed Bachelor of Science degree in Electrical Engineering is normally required to become a candidate for the Master of Science degree in Electrical Engineering. Qualified students with Engineering, Engineering Technology or Science degrees other than Electrical Engineering will be asked to complete with a grade of B or better the following courses (including applicable prerequisites) as a provision of their admission to the Master of Science in Electrical Engineering program: ECE 314, ECE 343, and ECE 351. A set of four core courses in Linear Systems Analysis (ECE 512), Electromagnetic Theory (ECE 550), Random Variable and Stochastic Processes (ECE 515), and Solid State Electronics (ECE 565) are offered on a rotating basis. Students are expected to complete at least three of these four courses. In addition to the core curriculum, students may enroll in state-of-the-art courses offered by the Electrical Engineering graduate program. Normally no more than 6 credits of ECE 400 level course work will be acceptable for graduate credit. In addition, no more than one ECE 599 and two ECE 598 courses may be taken toward fulfilling the requirements for a Master of Science degree in Electrical Engineering. Degree candidates may also choose to take courses in Mathematics, Physics, Chemistry, Computer Science and other disciplines which are consistent with his/her program goals.

Ph.D. candidates are required to pass a qualifying exam on Electrical Engineering fundamentals, and complete a comprehensive exam in the student’s area of research. The Ph.D. candidate must complete a program of study which has obtained the approval of the student’s advisory committee and the Graduate Coordinator of the department. The preparation and defense of a thesis embodying the results of an original investigation in a specialized area of Electrical Engineering are essential features of the program.

Graduate Faculty

Mohamad T. Musavi, Ph.D. (Michigan, 1983), Professor and Chair. Artificial Neural Networks, computer vision.

Scott D. Collins, Ph.D. (Brigham Young University, 1980), Cooperating Professor. Microelectrical mechanical systems (MEMS).

Mauricio Pereira da Cunha, Ph.D. (McGill University, 1994), Assistant Professor. Microwave acoustics, signal processing, sensors and applications.

Richard O. Eason, Ph.D. (Tennessee, 1988), Associate Professor. Robotics and computer vision.

Duane Hanselman, Ph.D. (Illinois, 1985), Associate Professor. Design and control of motors, control theory and design.

Donald M. Hummels, Ph.D. (Purdue, 1987), Professor. Communications, signal processing and pattern recognition.

David Kotecki, Ph.D. (University of California-Davis, 1988), Associate Professor. Microelectronics, electronic materials, computer modeling and simulation.

Habtom Ressom, Ph.D. (University of Kaisers-lautern, Germany, 1999), Assistant Professor. Neural networks, virtual sensing.

Bruce E. Segee, Ph.D. (University of New Hampshire, 1992), Associate Professor. Instrumentation, neural networks and computer interfacing.

Rosemary Smith, Ph.D. (University of Utah, 1982), Professor. Microsensors, microtechnology, biomedical microdevices.

John F. Vetelino, Ph.D. (Rhode Island, 1969), Professor. Surface acoustic wave devices and applications, microsensors, sonar signal processing, solid state.