MS in Electrical and Computer Engineering

Objective

Participants in the MS in Electrical and Computer Engineering (ECE) is open to both entry-level graduate students who want to pursue a career in electrical and computer engineering and professionals who have responsibilities in engineering or computer science fields and want to further their knowledge and skills.

The program offers three tracks: audio engineering, data analytics, sensors and devices, and a general ECE track.

Specialty areas of study in Electrical and Computer Engineering include:

  • Statistical signal processing
  • Image and video processing, pattern recognition, computer vision and automation of visual tasks
  • Machine learning and big data analytics
  • Bioinformatics, computational biology and genomics
  • Nano-photonics, plasmonics, micro/nano-electronic devices, nano-materials and structures
  • Fusion and learning in networks
  • Data mining, multimedia information systems, multimedia networking and security
  • Intelligent sensor microchips and MEMS, BioMEMS, implantable medical devices, VLSI, ASICS, system-on-a-chip and FPGAs
  • Integrated optics, holography, lithography, spectral imaging and optical coherence tomography
  • Game theory and multi-agent systems

Industry Advisory Board

The MS program is informed by an industry advisory board with significant experience in in electrical and computer engineering. To view the MS in Electrical and Computer Engineering Program advisory board, please click here.

Curriculum

Students enrolled in the MS in Electrical and Computer Engineering program must successfully complete 27 credits in one of the tracks and a three-credit research project.

Audio Engineering Track

Students who choose the audio engineering track are encouraged to take the following courses:

Course # Title Credits
ECE 602 Engineering Acoustics 3
ECE 633 Random Signals and Noise 3
ECE 636 Adaptive Filters and Signal Processing 3
ECE 638 Introduction to Digital Image Processing 3
ECE 640 Digital Speech and Audio Processing 3
ECE 648 Machine Learning 3
ECE 677 Data Mining 3

Remaining credits may be taken from 600/700 level courses in electrical and computer engineering (ECE), computer science (CS) or mathematics (MTH).

Courses for the Data Analytics Track

Students who choose the data analytics track are encouraged to take the following courses:

Course # Title Credits
ECE 600 Engineering Analytical Techniques 3
ECE 633 Random Signals and Noise 3
ECE 634 Communication Networks 3
ECE 648 Machine Learning 3
ECE 672 Object-Oriented and Distributed Database Management Systems 3
ECE 676 Internet and Intranet Security 3
ECE 677 Data Mining 3

Remaining credits may be taken from 600/700 level courses in ECE, CS or MTH.

Courses for the Microdevices and Photonics Track

Students who choose the sensors and devices track are encouraged to take the following courses:

Course # Title Credits
ECE 603 Laser Communications 3
ECE 604 Fundamentals of Optical Imaging 3
ECE 605 Semiconductor Photonic Devices 3
ECE 606 Microfabrication 3
ECE 632 VLSI Systems 3
ECE 643 BioNanotechnology 3

Remaining credits may be taken from 600/700 level courses in ECE, CS or MTH.

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