Master of Science [M.S] (Electrical Engineering and Computer Science)

at Massachusetts Institute of Technology

Electrical Engineering and Computer Science (Course 6) is organized into five research areas that students can pursue:
 

• Information, System, and Network Science

• Circuits; Integrated Electronic and Photonic Systems

• Physical Science, Devices, and Nanotechnology

• Bioelectrical and Biomedical Engineering

• Computer Science: Systems, Theory, and AI

Circuits
 

The focus in circuits is on electronic circuits and systems, microprocessor-based control, and digital and analog signal processing, with an emphasis on design and practical implementation. Circuits research also focuses on both analysis and synthesis of devices and systems for measuring or processing signals, information, or power.

Key Areas of Research: 

Signal Processing, Communications, and Control; Energy and Power Systems; Circuits and Systems; Digital Design and Computer Architecture; Computer-Aided Design and Numerical Methods
 

Sample of Classes: 

6.1311 Independent Inquiry Power Lab; 6.320 Feedback System Design; 6.321 Solid-State Circuits; 6.345 Automatic Speech Recognition; 6.374 Analysis and Design of Digital Integrated Circuits; 6.631 Optics and Photonics; 6.695; Engineering Economic & Regulation: Electric Power; 6.720 Integrated Microelectronics Devices; 6.943 How to Make Almost Anything

Bioelectrical and Biomedical Engineering
 

Working at the cutting edge of engineering and medicine, the goal is to understand complex biological systems and engineer systems that solve important biological problems. Molecular engineering, micro- and nanosystems applied to biology and medicine, biophotonics and medical imaging, electromagnetic fields in biological tissue and cells, auditory physiology and psychophysics, sensory aids for hearing and vision are just a sample of the directions you can go in this innovative research area.

Key Areas of Research: 

Cellular and Molecular Engineering; Medical Imaging; Medical Devices and Microsystems; Clinical Inference and Learning in Medicine; Physiological Modeling
 

Sample of Classes:
 
6.524 Molecular, Cellular, and Tissue Biomechanics; 6.525 Medical Device Design; 6.521 Cellular Neurophysiology and Computing; 6.555 Biomedical Signal and Image Processing; 6.557 Biomolecular Feedback Systems; 6.872 Biomedical Computing

Computer Science (Artificial Intelligence)
 

Computer Science (AI) studies how to make computers see, hear, understand, plan, and act in the world. Opportunities of research in this area span from reducing the carbon footprint of AI, reproducing aspects of human neurology, to helping play a role in stopping the Covid-19 pandemic.

Key Areas of Research:

Knowledge representation and reasoning; Knowledge-based systems; Medical information systems; Machine learning; Natural language processing; Perceptual interfaces and human/computer interaction; Robotics; Speech Understanding; Vision

Sample Classes: 

6.844 Artificial Intelligence; 6.854 Advanced Algorithms; 6.860 Statistical Learning Theory; 6.862 Applied Machine Learning; 6.867 Machine Learning; 6.877 Principles of Autonomy & Decision Making; 6.883 Adv Topics in Artificial Intel; 6.884 Adv Topics in Artificial Intel

Computer Science (Systems)
 

In this area of Systems, you will study the principles, design, and engineering of computer systems, both software and hardware. Students walk away with skills including ability to analyze complex computing problems and apply principles of computing and other relevant disciplines to identify solutions, and design, implement, and evaluate a computing-based solution to meet a given set of computing requirements.

Key Areas of Research: 

Computer architecture; Distributed computing; Fault-tolerant computing; High performance computing and applications; Operating systems; Parallel systems; Parallel computation; Programming languages and compilers; Software specification Design, and analysis; VLSI architecture and computer systems

Sample of Classes: 

6.823 Computer System Architecture; 6.828 Operating System Engineering; 6.829 Computer Networks; 6.831 User Interface Design; 6.833 Human Intelligence Enterprise; 6.835 Intell Multi User Interfaces; 6.857 Network and Computer Security; 6.869 Advances in Computer Vision; 6.894 Adv Top Graph Human Comp Inter

Academic Eligibility:
 

• The students must have a bachelor’s degree(3 or 4 years) in any of the respective fields to apply for this program.
• A strong academic background in science or engineering with significant knowledge of electrical engineering or computer science. 

Work Experience:
 

• Previous work experience in an industrial setting is ideal.

Language Requirements:
 

• The students whose official language is not English are required to write IELTS or TOEFL exams before applying.

• The TOEFL cut-off for this program is 100 out of 120.

• The IELTS cut-off is 7 out of 9.

• IELTS exam is preferred over the TOEFL.

The cost of studying at Massachusetts Institute of Technology varies largely depending on the type of university and the degree chosen. More often than not, humanities, arts, and education courses are less expensive than degrees in medical, engineering, or management. Furthermore, students who choose to study at the postgraduate level typically pay higher tuition fees, which again vary depending on the programme chosen.

Most universities provide scholarships or financial aid to students in order to help them offset their tuition costs. Students should be aware that additional course fees and incidental expenses may not be included in tuition. On average, international students can expect to pay $59,750 annually, to study in Massachusetts Institute of Technology

• Recent graduates from LGO EECS work in electronics, software, e-commerce, and web services.

• Some students go into biotech, research institutes, or consulting.

• Many work in strategic management, operations management, or project management roles directly after the program.