Master of Science in Electrical & Computer Engineering

All concentrations of the MS in Electrical and Computer Engineering are offered in Boston.

The Hardware and Software for Machine Intelligence concentration, the Computer Vision, Machine Learning, and Algorithms concentration, and the Computer Systems and Software concentration are also available in Seattle, WA.

Note: a subset of electives may be offered at campuses outside of Boston.

The program may be pursued full time or part time. Part-time students will find that many graduate courses are offered by video streaming to allow them to maintain a full-time career.

Students also select from 8 concentrations to personalize their education.

Choice of coursework or thesis-based.

Northeastern electrical and computer engineering faculty and graduate students conduct world-class research at the forefront of electrical and computer engineering. The department is home to experts in a variety of disciplines spanning the field of electrical and computer engineering. Our faculty and graduate students are deeply connected with the intellectual community of Boston and Cambridge. Our department features numerous collaborations with top-tier institutions such as MIT, Harvard, Draper Labs, and Massachusetts General Hospital to name just a few. Our research is also funded by numerous federal agencies. The department has strong ties to industry with joint projects with them. Additionally, Northeastern is home to several cutting-edge labs and facilities in areas of electrical and computer engineering such as the Institute for Experiential Robotics, the Institute for the Wireless Internet of Things, the Institute for Experiential AI, Institute for NanoSystems Innovation, and many others in the areas of health, security/cybersecurity, and sustainability.

View our department research areas.

View our research centers.

[Listed by concentrations]

• Communications, Control, and Signal Processing
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.
• Computer Systems and Software
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.
• Computer Vision, Machine Learning, and Algorithms
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.
• Electromagnetics, Plasma, and Optics
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.
• Hardware and Software for Machine Intelligence
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.
• Microsystems, Materials, and Devices
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.
• Power Systems
  • An ability to study engineering problems and to apply deterministic or statistical tools or techniques to efficiently produce computational, mathematical or physical models, or design experiments, for solving problems.
  • An ability to apply analytical or numerical methods to study the computational, mathematical or physical models, or if appropriate the results of experiments, to produce solutions or designs.
  • An ability to evaluate the efficiency or adequacy of the solutions using analytical, computational, or experimental techniques.

MS thesis students should have a research advisor one year after their matriculation.

Dissertation/Thesis Instructions

Over 15 graduate certificates are available to provide students the opportunity to develop a specialization in an area of their choice. Certificates can be taken in addition to or in combination with a master’s degree, or provide a pathway to a master’s degree in Northeastern’s College of Engineering. Master’s programs can also be combined with a Gordon Engineering Leadership certificate. Students should consult with their faculty advisor regarding these options.