• 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 strictly electrical engineering and inter-disciplinary instruction and research topics.
  • The M.S. program has three (3) possible tracks of study: (a) nano/micro/opto-electronics, photonics, and sensor technology (nEPS); (b) communications, sensor systems, and signal processing (CSSP); and (c) systems engineering (SE). The Ph.D. program has only the first two (2) tracks of study (nEPS and CSSP). The faculty's interests and the various topics defining these tracks of study are:
  • Communications: random processes, detection and estimation theory, information theory, source and channel coding, communication theory, wired/wireless/optical-fiber communications, data compression, adaptive and machine-learning techniques.
  • Nano/micro/opto-electronics: solid-state electronics, semiconductor devices and processing technology, semiconductor opto-electronics, compound semiconductor electronics, and integrated circuits.
  • Photonics: electromagnetic theory, quantum electronics, solid-state and fiber lasers, semiconductor and quantum-cascade lasers, fiber-optic communications, optical networking and interconnections, non-linear/integrated optics/ultra-fast/sub-wavelength optics, and bio/nano/silicon-photonics.
  • Sensor Technology: bio-chemical and opto-electronic-sensors.
  • Signal Processing: signal and linear system theory; digital signal processing (DSP); statistical signal processing (detection, estimation, machine-learning); adaptive and learning techniques; speech processing; pattern recognition; spectral, time-frequency, and joint-domain analysis; biomedical signal processing; and sensor-based systems and networks.
  • Image Processing: automatic target recognition, pattern recognition, image coding and compression, multi-/hyper-spectral imaging, biomedical imaging and image analysis, visual information systems and retrieval.
  • 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.