Master of Science
MSCotermJoint DegreeOverview
Students with undergraduate degrees in electrical engineering, other branches of engineering, physics, mathematics, or related sciences are invited to apply for admission. Capable students without such undergraduate preparation may also be considered for admission. Students may hold either a BS or BA degree. Graduate study in electrical engineering requires that students be adequately prepared in circuits, digital systems, fields, lab work, mathematics, and physics. Students should typically be able to complete the master’s degree in five quarters; note that most courses are not offered during the Summer.
In planning a course of study, it is the student’s responsibility, in consultation with an advisor, to determine whether the prerequisites for advanced courses have been met. Prerequisite courses ordinarily taken by undergraduates may be included as part of the graduate program of study. However, if the number of these is large, the proposed program may contain more than the minimum 45 units, and the time required to meet the degree requirements may be increased.
The master’s degree program provides advanced preparation for professional practice or junior college-level teaching. Faculty are assigned as program advisors to guide course selection and exploration of academic opportunities and professional pathways. Each student, with the help of a program advisor, prepares an individual program and submits it to the Department for approval. The program proposal must be submitted to the Degree Progress Officer before the end of the first quarter of graduate study (second quarter for Honors Cooperative Program students); a final revised version is due at the beginning of the last quarter of study, before degree conferral. Detailed requirements and instructions are in the Electrical Engineering Department Graduate Handbook opens in a new tab. All requirements for a master’s degree must be completed within three years after the student’s first term of enrollment in the master’s program (five years for Honors Cooperative Program students).
Requirements
Program Requirements
Depth Requirement
Complete 12 units from only one of the five (5) area lists. All depth courses must be 200-level and above. At least six units must be at the 300-level or above.
Depth Area 1: Circuits
EE 207
Neuromorphics: Brains in Silicon
EE 214A
Fundamentals of Analog Integrated Circuit Design
EE 214B
Advanced Integrated Circuit Design
EE 216
Principles and Models of Semiconductor Devices
EE 233
Analog Communications Design Laboratory
EE 251
High-Frequency Circuit Design Laboratory
EE 253
Power Electronics
EE 254
Advanced Topics in Power Electronics
EE 256
Board Level Design
EE 271
Introduction to VLSI Systems
EE 272
Design Projects in VLSI Systems I
EE 273
Digital Systems Engineering
EE 303
Autonomous Implantable Systems
EE 308
Advanced Circuit Techniques
EE 309A
Semiconductor Memory Devices and Circuit Design
EE 314A
RF Integrated Circuit Design
EE 315
Analog-Digital Interface Circuits
EE 356A
Resonant Converters
EE 356B
Magnetics Design in Power Electronics
EE 372D
Design Projects in VLSI Systems II
Depth Area 2: Software and Hardware Systems
BMDS 270
Algorithmic Foundations for Artificial Intelligence in Healthcare
CS 221
Artificial Intelligence: Principles and Techniques
CS 228
Probabilistic Graphical Models: Principles and Techniques
CS 229
Machine Learning
CS 230
Deep Learning
CS 231A
Computer Vision: From 3D Perception to 3D Reconstruction and Beyond
CS 231N
Deep Learning for Computer Vision
CS 236
Deep Generative Models
CS 240
Advanced Topics in Operating Systems
CS 243
Program Analysis and Optimizations
CS 244
Advanced Topics in Networking
CS 245
Principles of Data-Intensive Systems
CS 246
Mining Massive Data Sets
CS 248A
Computer Graphics: Rendering, Geometry, and Image Manipulation
CS 248B
Fundamentals of Computer Graphics: Animation and Simulation
CS 255
Introduction to Cryptography
CS 347
Human-Computer Interaction: Foundations and Frontiers
CS 348B
Computer Graphics: Image Synthesis Techniques
CS 348K
Visual Computing Systems
CS 354
Topics in Intractability: Unfulfilled Algorithmic Fantasies
CS 357S
Formal Methods for Computer Systems
EE 217
Understanding the Sensors in your Smartphone
EE 272
Design Projects in VLSI Systems I
EE 273
Digital Systems Engineering
EE 282
Computer Systems Architecture
EE 284
Introduction to Computer Networks
EE 284A
Introduction to Internet of Things
EE 285
Embedded Systems Workshop
EE 292D
Machine Learning on Embedded Systems
EE 349
Software Techniques for Emerging Hardware Platforms
EE 372D
Design Projects in VLSI Systems II
EE 382A
Parallel Processors Beyond Multicore Processing
EE 382C
Interconnection Networks
ME 218A
Smart Product Design Fundamentals
ME 218B
Smart Product Design Applications
ME 218C
Smart Product Design Practice
Depth Area 3: Communications and Networking
CS 244
Advanced Topics in Networking
EE 247
Introduction to Optical Fiber Communications
EE 274
Data Compression: Theory and Applications
EE 276
Information Theory
EE 279
Introduction to Digital Communication
EE 284
Introduction to Computer Networks
EE 284A
Introduction to Internet of Things
EE 348
Advanced Optical Fiber Communications
EE 358
Wireless System Design
EE 359
Wireless Communications
EE 374
Fundamentals of Blockchain Infrastructure
EE 376C
Universal Information Processing
EE 379
Digital Communication
EE 379A
Data Transmission Design
EE 379B
Advanced Data Transmission Design
EE 392AA
Multi-User Data Transmission
EE 382C
Interconnection Networks
EE 384A
Internet Switching and Routing Protocols
EE 384S
Performance Engineering of Computer Systems & Networks
EE 387
Algebraic Error Correcting Codes
MS&E 335
Queueing and Scheduling in Processing Networks
Depth Area 4: Physical Technology and Science
BIOE 300B
Quantitative Physiology
EE 212
Integrated Circuit Fabrication Processes
EE 216
Principles and Models of Semiconductor Devices
EE 218
Power Semiconductor Devices and Technology
EE 219
3D+ Imaging Sensors
EE 222
Applied Quantum Mechanics I
EE 223
Applied Quantum Mechanics II
EE 224
Quantum Control and Engineering
EE 225
Biochips and Medical Imaging
EE 234
Photonics Laboratory
EE 235A
Analytical Methods in Biotechnology I
EE 236A
Modern Optics
EE 236B
Guided Waves
EE 236C
Lasers
EE 237
Solar Energy Conversion
EE 238
Introduction to Fourier Optics
EE 242
Electromagnetic Waves
EE 247
Introduction to Optical Fiber Communications
EE 258
Introduction to Radar Remote Sensing
EE 259
Principles of Sensing for Autonomy
EE 292L
Computational Electromagnetics
EE 293B
Fundamentals of Energy Processes
EE 303
Autonomous Implantable Systems
EE 309A
Semiconductor Memory Devices and Circuit Design
EE 309B
Emerging Non-Volatile Memory Devices and Circuit Design
EE 311
Advanced Integrated Circuits Technology
EE 312
Integrated Circuit Fabrication Laboratory
EE 316
Advanced VLSI Devices
EE 317
Special Topics on Wide Bandgap Materials and Devices
EE 323
Energy in Electronics
EE 329
The Electronic Structure of Surfaces and Interfaces
EE 332
Laser Dynamics
EE 336
Nanophotonics
EE 340
Quantum Photonics
EE 346
Introduction to Nonlinear Optics
EE 347
Optical Methods in Engineering Science
EE 348
Advanced Optical Fiber Communications
ENERGY 201C
Energy storage and conversion systems: Solar Cells, Fuel Cells, Batteries
ENGR 240
Introduction to Micro and Nano Electromechanical Systems
ENGR 241
Advanced Micro and Nano Fabrication Laboratory
MATSCI 209
Electronic and Optical Properties of Solids
ME 220
Introduction to Sensors
OPHT 207
Introduction to Electro-neural Interfaces
RAD 235
Advanced Ultrasound Imaging
BIOE 300B: This course can only be used as a 200-level course.
Depth Area 5: Signal Processing, Control and Optimization
AA 203
Optimal and Learning-based Control
AA 212
Advanced Feedback Control Design
CEE 272R
Engineering Future Electricity Systems
CS 234
Reinforcement Learning
CS 238
Decision Making under Uncertainty
CS 326
Topics in Advanced Robotic Manipulation
EE 227
Robot Perception
EE 258
Introduction to Radar Remote Sensing
EE 259
Principles of Sensing for Autonomy
EE 260A
Principles of Robot Autonomy I
EE 260B
Principles of Robot Autonomy II
EE 261
The Fourier Transform and Its Applications
EE 263
Matrix Methods: Singular Value Decomposition
EE 264
Digital Signal Processing
EE 267
Virtual Reality
EE 268
The Engineering Economics of Electricity Markets
EE 269
Quantization and Signal Processing for AI
EE 278
Probability and Statistical Inference
EE 219
3D+ Imaging Sensors
EE 230
Ice Penetrating Radar
EE 355
Imaging Radar and Applications
EE 363
Linear Dynamical Systems
EE 364A
Convex Optimization I
EE 364B
Convex Optimization II
EE 367
Computational Imaging
EE 368
Digital Image Processing
EE 369A
Medical Imaging Systems I
EE 369B
Medical Imaging Systems II
EE 369C
Medical Image Reconstruction
EE 383
Reinforcement Learning: Behaviors and Applications
EE 377
Information Theory and Statistics
EE 378A
Statistical Signal Processing
EE 381
Sensorimotor Learning for Embodied Agents
EE 469B
RF Pulse Design for Magnetic Resonance Imaging
ENGR 205
Introduction to Control Design Techniques
ENGR 209A
Analysis and Control of Nonlinear Systems
MS&E 310
Linear Programming
MS&E 311
Optimization
MS&E 321
Stochastic Systems
MS&E 322
Stochastic Calculus and Control
MUSIC 422
Perceptual Audio Coding
OIT 604
Data, Learning, and Decision-Making
PSYCH 221
Image Systems Engineering
STATS 315A
Modern Applied Statistics: Learning
STATS 315B
Modern Applied Statistics: Learning II
All depth units must be letter graded.
Breadth Requirements
Completing nine additional units from any area list other than the chosen depth area
All breadth units must be letter graded and at the 200-level or above
If a course is listed in the chosen depth area, it cannot be used to count in the breadth area
Technical Course Requirement
Completion of 15 units of courses in engineering, natural sciences, mathematics, or statistics
At least nine of the 15 units must be lecture courses at the 200-level or above
EE courses must be 200-level or above
A maximum of six units can be graduate-level independent study and/or 100-level courses; all units must be letter-graded
All technical units must be letter-graded
Independent study units may not be taken in place of the nine units of 200-level or above letter-graded lecture courses.
Mathematics, natural sciences, or engineering courses are acceptable, provided they use quantitative or scientific methods to analyze, design, or optimize artificial or natural systems. Courses primarily addressing entrepreneurship, management, economics, collaboration, design philosophy, language, or public speaking are typically unacceptable. Consult with your advisor or the Degree Progress Officer before selecting courses in Economics, GSB, d.school, MS&E, Psychology, or other departments offering semi-technical or non-technical courses.
Other Courses
Completion of at least nine additional units. These units must be at the 100-level or above and letter-graded or CR/NC in EE or other departments relevant to the EE MS degree and at the graduate level.
Suggested courses include:
• Depth/breadth courses
• Additional technical courses
• Independent study (e.g., EE 390, EE 391)
• Curricular Practical Training (e.g., EE 290A)
• Seminars
• Entrepreneurial or design courses
Please note: Athletics courses do not count toward the 45 units. EFSLANG (English for Foreign Students) courses do not count toward the 45 units. If the university requires you to take any of these classes, they are additional units above the required 45 units.
All units must be at the 100 level or higher. No courses numbered below the 100 level can count toward a graduate degree. Note: Athletics courses do not count toward the 45 units. EFSLANG (English for Foreign Students) courses do not count toward the 45 units. If the university requires you to take any of these classes, they are additional units above the required 45 units.
All units must be at the 100 level or higher. No courses numbered below the 100 level can count toward a graduate degree.
Master of Science with Distinction in Research
Requirement Overview
A graduate student enrolled in 8-10 units who wishes to pursue the MS in Electrical Engineering (EE) with distinction in research must first identify a faculty advisor who agrees to supervise and support the research work. The research advisor must be a member of the Academic Council and must hold an appointment in Electrical Engineering. The student and principal advisor must also identify another faculty member who need not be in the Department of Electrical Engineering to serve as a secondary advisor and reader for the research report. In addition, the student must complete the following requirements beyond those for the regular MS in EE degree:
Research Experience – The program must include significant research experience at the level of a half-time commitment over the three academic quarters. In any given quarter, the half-time research commitment may be satisfied by:
a. 50 percent appointment to a departmentally supported research assistantship
b. Six (6) units of independent study (EE 300 or EE 391)
c. A prorated combination of the two (such as a 25 percent research assistantship supplemented by three (3) units of independent
study)
d. An equivalent research experience while fully supported on a Stanford-funded or externally funded fellowship. Students and research advisors must document the planned research experience before the quarter starts and its completion at the end. Note: Fellowship must provide full support at the 10-unit tuition level and allow the student to pursue degree-related research in addition to their full-time course enrollment. This research must be carried out under the direction of the primary or secondary advisor.
Supervised Writing and Research – In addition to the research experience outlined in the previous requirement, students must enroll in at least three (3) units of independent research (EE 300 or EE 391) under the direction of their primary or secondary advisor. These units should be closely related to the research described in the first requirement but focused more on preparing the research report described in the next section. The writing and research units described in parts (1) and (2) may be counted toward the 45 units required for the degree.
All independent study units (EE 300 or EE 391) must be taken for letter grades, and a GPA of 3.0 (B) or better must be maintained.
Research Report – Students must complete a significant report describing their research and its conclusions. The research report represents work publishable in a journal or at a high-quality conference, although it is presumably longer and more expansive in scope than a typical conference paper. A copy of the research report must be submitted to the student services office in the department three weeks before the beginning of the examination period in the student’s final quarter. The primary and secondary advisors must approve the research report before the distinction-in-research designation can be conferred.
Joint Degree Program: MS/MBA
Overview and Admissions
The Joint MS in Electrical Engineering /MBA Degree Program (EE/MBA) opens in a new tab enables students to pursue simultaneously a Master of Business Administration at the Graduate School of Business (GSB) and a Master of Science in Electrical Engineering at the Stanford School of Engineering. Joint MS/MBA degree students will be interested in technology and leadership and want to become managers or entrepreneurs in technologically-inclined businesses. The Joint MS/MBA Degree Program requires an application opens in a new tab to, and acceptance for admission by, the Electrical Engineering Department (EE) and the GSB. MS/MBA students typically apply to and gain approval for admission to both programs within the same year. However, it is possible for current EE (or MBA) students who previously did not apply for the joint degree option to apply for and pursue the Joint MS/MBA Degree Program. EE students in the second year and MBA students in the second year may not apply for the Joint MS/MBA Degree Program.
Additional information on the MS in Electrical Engineering/MBA Joint Degree Program and its requirements is available on the Electrical Engineering Department’s website. opens in a new tab

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