Graduate Research

SHARE:

Almost all of the research by MIT EECS faculty, staff, and students is carried out in interdepartmental laboratories, centers, and programs. The primary labs include the Computer Science and Artificial Intelligence Lab (CSAIL), the Laboratory for Information and Decision Systems (LIDS), the Microsystems and Technology Laboratories (MTL) and the Research Laboratory of Electronics (RLE). For a complete list of laboratories, centers and programs at MIT, visit http://web.mit.edu/research/.

As a convenience for administering the department doctoral program, research activities in EECS are divided into two Graduate Research Areas.

 

Graduate Research Areas

Research Supervisors

EECS Research Fields

 Area I: Information Systems (InfoSys)
Lying at the critical interface between computation and the physical world, Information Systems bridges the more traditionally computer science centric and more traditionally electrical engineering centric areas of the department. 
Area II: Computer Science: AI, Systems, Theory
Academic programs for graduate students in the field of computer science lead to the Master of Engineering, Master of Science, Engineer's, and either Doctor of Philosophy or Doctor of Science degree. 
Area I: Circuits
Research in Area I: Circuits emphasizes electronic circuits and systems, microprocessor based control, and digital and analog signal processing. Design and practical implementation are emphasized. 
Area I: Applied Physics and Devices (ApplPhysDev)
Area I: Applied Physics and Devices uses the foundation and underlying principles of physics to enable the engineering of complex integrated systems. The highlighted topics are electromagnetics, photonics, power, energy materials, devices, microsystems, nanotechnology, and physics of information.
Area I: BioMedical Sciences and Engineering (BioMed)
Area I: BioMedical Sciences and Engineering within EECS is composed of EECS faculty and students who work at the cutting edge of engineering and/or medicine. Our collective goal is to understand complex biological systems and/or engineer systems that solve important biological problems. Related: bioEECS