Mar 05, 2024  
2023-2024 Graduate Catalog 
2023-2024 Graduate Catalog

Electrical Engineering (EENG)

Return to {$returnto_text} Return to: Graduate Programs

Tino​osh Mohsenin, Graduate Program Director

Degrees Offered

M.S., Ph.D. (Degree Types )



CHEN, YUNG JUI (RAY), Ph.D., University of Pennsylvania: Optical networks, integrated optics and opto-electronic integrated circuits, device physics, ultra-fast optics and non-linear optics.
MORRIS, JOEL M., Ph.D., The Johns Hopkins University: Communication theory and statistical signal processing theory with applications in sensing, detection, estimation, and characterization, error correction codes, adaptive importance sampling for statistical performance assessment, joint time-frequency/time-scale analysis and presentations.


ADALI, TULAY, Ph.D., North Carolina State University: Statistical signal processing, machine learning, matrix and tensor factorizations, applications in multi-set and multi-modal data fusion, medical image analysis, video analysis, and communications.
CARTER, GARY M., Ph.D., Massachusetts Institute of Technology: Optical communications, non-linear optics, lasers, bio-photonics.
CHANG, CHEIN-I, Ph.D., University of Maryland, College Park: Multispectral/hyper-spectral imaging, chemical/biological defense, automatic target recognition (ATR), computer-aided diagnosis for medical imaging, visual information systems and retrieval.
CHOA, FOW-SEN, Ph.D., State University of New York, Buffalo: MOCVD growth, quantum cascade lasers, mid-IR and THz photonic devices, chip-scale integrated sensor systems, RF-photonic and optical switching devices.
JOHNSON, ANTHONY, Ph.D., City College of the City University of New York: Director of the Center for Advanced Studies in Photonics Research (CASPR); Ultra-fast optics, non-linear optics and ultra-fast photophysics of nano-structured materials.
MENYUK, CURTIS R., Ph.D., University of California, Los Angeles: Optical communications, non-linear optics, theoretical electromagnetics, short-pulse lasers, time and frequency transfer.
YAN, LI, Professor, Ph.D., University of Maryland, College Park; Ultra-fast optics, non-linear optics, solid-state and fiber lasers, optical communications.

Associate Professor

RUTLEDGE, JANET, Ph.D., Georgia Institute of Technology: Modeling and Compensating for the effects of sensorineural hearing loss and other communication disorders.

Assistant Professors

KIM, SEUNG JUN, PH.D., University of California, Santa Barbara: Statistical signal processing, optimization, and statistical learning, with applications to wireless communication and networking, future power systems, and big data analytics.
ZHU, TING, Ph.D., University of Minnesota:  Big data, embedded systems, cyber-physical systems, Mobile systems, Distributed systems, Operating Systems, power systems, renewable and sustainable energies, Internet of things, wireless and sensor networks, network protocols, social networks, and security.

Professor of Practice

LABERGE, E.F. CHARLES, Ph.D., UMBC: Coding theory, signal processing, communication system design, interface analysis, safety-critical avionics, system engineering.


Program Description

The CSEE Department offers a graduate program (EENG/ENEE) leading to the Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) degrees in Electrical Engineering (EE). The diversity of course offerings and research interests within the department, and interactions with the medical and dental schools at the University of Maryland, Baltimore, and other science and engineering departments at UMBC, encompass a broad spectrum of electrical engineering and inter-disciplinary instruction and research topics. The faculty’s interests and the various topics defining these tracks of study are:

Signal Processing & Machine Learning - Faculty in this area conduct research developing new platforms and methods to address many of the challenges posed by today’s data-rich applications, especially addressing problems in the complex and big data realm. The application domains are many and include problems in medical image analysis and data fusion, remote sensing, image processing for hyperspectral data, cognitive radio networks and future power systems (smart grids).

Microelectronics/ Microsystems (MEMS) & Photonics - Faculty in this area conduct research in the complementary fields of electronic, bioelectronic, nanotechnology, electromagnetic, and optical devices and circuits, with broad application to the next generation light emitters, power electronics, wearable and implantable biomedical sensors that advance consumer, industrial, national security, and health care outcomes.

Optics & Communications - Faculty in this area conduct basic and applied research that relies on the synergy of physics, materials science, numerical modeling, and device applications to understand and develop innovative materials, devices, and algorithms that addresses the demand for higher data transfer rates and bandwidths, and next generation mobile/wireless technologies.

Systems Engineering: life-cycles of complex systems; system architecture and design; system modeling, simulation, and analysis; system implementation, integration, and test; and systems of systems.
ENEE students, except for those in the SE track, may select their course and research plan in one track of study or in an interdisciplinary area approved by their advisor and the Graduate Program Director.

A departmental brochure that describes in more detail the department, its graduate programs, degree requirements, and the research interests of the faculty can be obtained from the graduate program specialist or can be viewed at either the CSEE Department or ENEE Graduate Program websites,, respectively.

Program Admission Requirements

When seeking admission to the graduate program in Electrical Engineering, applicants must satisfy all entrance requirements of the Graduate School at UMBC. These include the submission of official transcripts, three letters of recommendation, statement of purpose, Graduate Record Examination (GRE General Test) scores and, for international students, scores for the TOEFL. All original application materials must be sent directly to the Graduate School, not the graduate program. Application deadlines for international and domestic students are January 1/June 1 for the fall semester, and June 1/November 1 for the spring semester. The application review process will begin by January 1 for admission in the fall semester, and by October 1 for admission in the following spring semester. Early application is recommended.

In addition to the requirements of the graduate school, minimum requirements for admission to the graduate program in Electrical Engineering are a B.S. degree from an ABET-accredited undergraduate program in Electrical Engineering with a GPA equivalent to ‘B+’ or higher. Individuals whose records indicate strong potential for successful pursuit of the master’s or doctoral degree objectives and who have similar undergraduate preparation with strong academic records in computer science, mathematics, physics or other areas of engineering or science are encouraged to apply (B.S. degrees in engineering technology are not considered equivalent to the B.S. degree in engineering or the B.A. degree in the sciences). Students whose degrees are not in electrical engineering generally will be required to take courses to make up deficiencies in their backgrounds. Students who plan to pursue the Ph.D. degree but who do not already have an M.S. degree are advised to apply for admission to the M.S. program. Applicants are judged competitively by the program’s admissions committee, and those who appear suitably qualified to complete the requirements of the intended degree program successfully are selected for admission, subject to available resources. Applications are not processed until all documents and fees are received.

Facilities and Special Resources

Faculty and students in the electrical engineering program at UMBC have access to extensive computational resources. The research and instructional activities of the department are supported by a number of laboratories. Laser-based laboratories support research in ultra-fast non-linear optics and optical spectroscopy, solid state, diode and fiber lasers. Device fabrication laboratories support research in optical and electronic properties of compound semiconductors and organic polymers and in exploring and developing new materials, micro/nano device structures and processing technologies via CAIBE. Compound semiconductor growth research, such as quantum cascade lasers, is being pursued using MOCVD techniques. The optical communication and optical networking laboratories contains high-performance, fiber-optics communication equipment to perform experiments in digital transmission using multi-channels over long distances and optical networking. The remote sensing signal and image processing laboratory supports research in multi-spectral and hyper-spectral imagery, pattern recognition, target tracking and detection, image coding and progressive image transmission, computer vision, and medical imaging. The focus in the Machine Learning for Signal Processing laboratory ( if the development and theory and tools for processing of signals that arises in today’s growing array of applications with a n emphasis on medical image analysis and data fusion. Collaborations and funding resources include NSf, NIH, ARL, LTS, LPS, NASA, NIST, and NRL, University of Maryland School of Medicine, and Johns Hopkins School of Medicine, among many others.

Financial Assistance

Financial aid is available on a competitive basis to a limited number of qualified graduate students in the form of graduate teaching assistantships (TAs), graduate research assistantships (RAs), work-study positions, and hourly employment as graders. Graduate RAs are often available to students actively engaged in a master’s thesis or doctoral dissertation research, and are awarded and renewed subject to availability of funds and satisfactory research progress. Students are encouraged to apply directly to nationally awarded fellowship programs.

Course Listing

For ENEE (also CMPE and CMSC) course descriptions, and current year special topic course listings and descriptions, see the CSEE Graduate Program(s) website or CSEE Department website The set of ENEE 691  courses address specialized electrical engineering topics representing the research focus of the faculty, and are scheduled according to student and faculty interests.


    Master of ScienceDoctor of Philosophy


      Electrical Engineering

      Return to {$returnto_text} Return to: Graduate Programs