EE 14N:
Things about Stuff
Preference to freshmen. The stories behind disruptive inventions such as the telegraph, telephone, wireless, television, transistor, and chip are as important as the inventions themselves, for they elucidate broadly applicable scientific principles. Focus is on studying consumer devices; projects include building batteries, energy conversion devices and semiconductors from pocket change. Students may propose topics and projects of interest to them. The trajectory of the course is determined in large part by the students themselves.
Terms: Aut

Units: 3

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
EE 15N:
The Art and Science of Engineering Design
The goal of this seminar is to introduce freshmen to the design process associated with an engineering project. The seminar will consist of a series of lectures. The first part of each lecture will focus on the different design aspects of an engineering project, including formation of the design team, developing a project statement, generating design ideas and specifications, finalizing the design, and reporting the outcome. Students will form teams to follow these procedures in designing a term project of their choice over the quarter. The second part of each lecture will consist of outside speakers, including founders of some of the most exciting companies in Silicon Valley, who will share their experiences about engineering design. Onsite visits to Silicon Valley companies to showcase their design processes will also be part of the course. The seminar serves three purposes: (1) it introduces students to the design process of turning an idea into a final design, (2) it presents the different functions that people play in a project, and (3) it gives students a chance to consider what role in a project would be best suited to their interests and skills.
Terms: Win

Units: 3

UG Reqs: GER:DBEngrAppSci

Grading: Letter (ABCD/NP)
EE 25N:
Science of Information
We live in the Information Age, but what is information, anyway? In 1948, Claude Shannon published a seminal paper formalizing our modern notion of information. Through lectures and lab visits, we'll learn how information can be measured and represented, why bits are the universal currency for information exchange, and how these ideas led to smartphones, the Internet, and more. We¿ll get a glimpse of information elements in other domains, including neural codes of the brain, cryptographic codes, genetic code, quantum information, and even entertainment. As a final project, students will create podcast episodes on one of the topics explored in the course.
Terms: Aut

Units: 4

Grading: Letter (ABCD/NP)
EE 26N:
The Wireless World, and the Data You Leak
The world is increasingly based on wireless communication. Cell phones and WiFi are the most visible examples. Others are key fobs, water meters, gas and electric meters, garage door openers, baby monitors, and the list continues to expand. All of these produce RF signals you can detect and often decode. This seminar will explore how much information you broadcast throughout your day, and how it can easily be received and decoded using inexpensive hardware and public domain software. You will be able to explain why different information services use different frequencies, why they encode the information the way they do, and what security risks they present.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 42:
Introduction to Electromagnetics and Its Applications (ENGR 42)
Electricity and magnetism and its essential role in modern electrical engineering devices and systems, such as sensors, displays, DVD players, and optical communication systems. The topics that will be covered include electrostatics, magnetostatics, Maxwell's equations, onedimensional wave equation, electromagnetic waves, transmission lines, and onedimensional resonators. Prerequisites: none.
Terms: Win

Units: 5

UG Reqs: GER:DBEngrAppSci

Grading: Letter (ABCD/NP)
EE 60N:
Man versus Nature: Coping with Disasters Using Space Technology (GEOPHYS 60N)
Preference to freshman. Natural hazards, earthquakes, volcanoes, floods, hurricanes, and fires, and how they affect people and society; great disasters such as asteroid impacts that periodically obliterate many species of life. Scientific issues, political and social consequences, costs of disaster mitigation, and how scientific knowledge affects policy. How spaceborne imaging technology makes it possible to respond quickly and mitigate consequences; how it is applied to natural disasters; and remote sensing data manipulation and analysis. GER:DBEngrAppSci
Terms: Aut

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
EE 65:
Modern Physics for Engineers
This course introduces the core ideas of modern physics that enable applications ranging from solar energy and efficient lighting to the modern electronic and optical devices and nanotechnologies that sense, process, store, communicate and display all our information. Though the ideas have broad impact, the course is widely accessible to engineering and science students with only basic linear algebra and calculus through simple ordinary differential equations as mathematics background. Topics include the quantum mechanics of electrons and photons (Schrödinger's equation, atoms, electrons, energy levels and energy bands; absorption and emission of photons; quantum confinement in nanostructures), the statistical mechanics of particles (entropy, the Boltzmann factor, thermal distributions), the thermodynamics of light (thermal radiation, limits to light concentration, spontaneous and stimulated emission), and the physics of information (Maxwell¿s demon, reversibility, entropy and noise in physics and information theory). Prerequisite: Physics 41. Pre or corequisite: Math 53 or CME 102.
Terms: Spr

Units: 4

UG Reqs: GER: DBNatSci, GER:DBEngrAppSci, WAYSMA

Grading: Letter (ABCD/NP)
EE 100:
The Electrical Engineering Profession
Lectures/discussions on topics of importance to the electrical engineering professional. Continuing education, professional societies, intellectual property and patents, ethics, entrepreneurial engineering, and engineering management.
Terms: Aut

Units: 1

Grading: Satisfactory/No Credit
EE 101A:
Circuits I
Introduction to circuit modeling and analysis. Topics include creating the models of typical components in electronic circuits and simplifying nonlinear models for restricted ranges of operation (small signal model); and using network theory to solve linear and nonlinear circuits under static and dynamic operations. Prerequisite: ENGR40 or ENGR40M is useful but not strictly required.
Terms: Win, Sum

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
EE 101B:
Circuits II
Continuation of EE101A. Introduction to circuit design for modern electronic systems. Modeling and analysis of analog gain stages, frequency response, feedback. Filtering and analog¿to¿digital conversion. Fundamentals of circuit simulation. Prerequisites: EE101A, EE102A. Recommended: CME102.
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
EE 102A:
Signal Processing and Linear Systems I
Concepts and tools for continuous and discretetime signal and system analysis with applications in signal processing, communications, and control. Mathematical representation of signals and systems. Linearity and time invariance. System impulse and step responses. System frequency response. Frequencydomain representations: Fourier series and Fourier transforms. Filtering and signal distortion. Time/frequency sampling and interpolation. Continuousdiscretetime signal conversion and quantization. Discretetime signal processing. Prerequisite: MATH 53 or CME 102.
Terms: Win, Sum

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
EE 102B:
Signal Processing and Linear Systems II
Continuation of EE 102A. Concepts and tools for continuous and discretetime signal and system analysis with applications in communications, signal processing and control. Analog and digital modulation and demodulation. Sampling, reconstruction, decimation and interpolation. Finite impulse response filter design. Discrete Fourier transforms, applications in convolution and spectral analysis. Laplace transforms, applications in circuits and feedback control. Z transforms, applications in infinite impulse response filter design. Prerequisite: EE 102A.
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
EE 103:
Introduction to Matrix Methods (CME 103)
Introduction to applied linear algebra with emphasis on applications. Vectors, norm, and angle; linear independence and orthonormal sets; applications to document analysis. Clustering and the kmeans algorithm. Matrices, left and right inverses, QR factorization. Leastsquares and model fitting, regularization and crossvalidation. Constrained and nonlinear leastsquares. Applications include timeseries prediction, tomography, optimal control, and portfolio optimization. Undergraduate students should enroll for 5 units, and graduate students should enroll for 3 units. Prerequisites:MATH 51 or CME 100, and basic knowledge of computing (CS 106A is more than enough, and can be taken concurrently). EE103/CME103 and Math 104 cover complementary topics in applied linear algebra. The focus of EE103 is on a few linear algebra concepts, and many applications; the focus of Math 104 is on algorithms and concepts.
Terms: Aut

Units: 35

UG Reqs: GER:DBMath, WAYAQR, WAYFR

Grading: Letter or Credit/No Credit
EE 104:
Introduction to Machine Learning
Introduction to machine learning. Formulation of supervised and unsupervised learning problems. Regression and classification. Data standardization and feature engineering. Loss function selection and its effect on learning. Regularization and its role in controlling complexity. Validation and overfitting. Robustness to outliers. Simple numerical implementation. Experiments on data from a wide variety of engineering and other disciplines. Undergraduate students should enroll for 5 units, and graduate students should enroll for 3 units. Prerequisites: EE 103; EE 178 or CS 109; CS106A or equivalent.
Terms: Spr

Units: 35

Grading: Letter or Credit/No Credit
EE 107:
Embedded Networked Systems
Networked embedded systems are often hidden from our view, but they are a key component that enables our modern society. Embedded systems bridge our physical world with powerful digital measurement and control systems. Applications of today's embedded systems range from stabilization in drones authentication in credit cards, and even temperature control in toasters. In this class, students will learn about how to build an networked embedded system from the ground up. The lectures will focus on the key enabling components of embedded systems, including: Clocks, GPIO, Interrupts, Busses, Amplifiers, Regulators, Power supplies, ADC/DAC, DMA, and Storage. The goal of the class is to familiarize the students with these components such that they can build their own embedded systems in devices. Prerequisites: EE 102A or ENGR 40M.
Terms: Win, Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 108:
Digital System Design
Digital circuit, logic, and system design. Digital representation of information. CMOS logic circuits. Combinational logic design. Logic building blocks, idioms, and structured design. Sequential logic design and timing analysis. Clocks and synchronization. Finite state machines. Microcode control. Digital system design. Control and datapath partitioning. Lab. *In Autumn, enrollment preference is given to EE majors. Any EE majors who must enroll in Autumn are invited to contact the instructor. Formerly EE 108A.
Terms: Aut, Win

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYAQR, WAYSMA

Grading: Letter or Credit/No Credit
EE 109:
Digital Systems Design Lab
The design of integrated digital systems encompassing both customized software and hardware. Software/hardware design tradeoffs. Algorithm design for pipelining and parallelism. System latency and throughput tradeoffs. FPGA optimization techniques. Integration with external systems and smart devices. Firmware configuration and embedded system considerations. Enrollment limited to 25; preference to graduating seniors. Prerequisites: 108B, and CS 106B or X.
Terms: Spr

Units: 4

Grading: Letter or Credit/No Credit
EE 114:
Fundamentals of Analog Integrated Circuit Design (EE 214A)
Analysis and simulation of elementary transistor stages, current mirrors, supply and temperatureindependent bias, and reference circuits. Overview of integrated circuit technologies, circuit components, component variations and practical design paradigms. Differential circuits, frequency response, and feedback will also be covered. Performance evaluation using computeraided design tools. Undergraduates must take EE 114 for 4 units. Prerequisite: 101B. GER:DBEngrAppSci
Terms: Aut

Units: 34

UG Reqs: GER:DBEngrAppSci

Grading: Letter (ABCD/NP)
EE 116:
Semiconductor Devices for Energy and Electronics
The underpinnings of modern technology are the transistor (circuits), the capacitor (memory), and the solar cell (energy). EE 116 introduces the physics of their operation, their historical origins (including Nobel prize breakthroughs), and how they can be optimized for future applications. The class covers physical principles of semiconductors, including silicon and new material discoveries, quantum effects, band theory, operating principles, and device equations. Recommended (but not required) corequisite: EE 65 or equivalent.
Terms: Spr

Units: 3

UG Reqs: GER:DBEngrAppSci

Grading: Letter or Credit/No Credit
EE 118:
Introduction to Mechatronics (ME 210)
Technologies involved in mechatronics (intelligent electromechanical systems), and techniques to apply this technology to mecatronic system design. Topics include: electronics (A/D, D/A converters, opamps, filters, power devices); software program design, eventdriven programming; hardware and DC stepper motors, solenoids, and robust sensing. Large, openended team project. Prerequisites: ENGR 40, CS 106, or equivalents.
Terms: Win

Units: 4

Grading: Letter (ABCD/NP)
EE 124:
Introduction to Neuroelectrical Engineering
Fundamental properties of electrical activity in neurons, technology for measuring and altering neural activity, and operating principles of modern neurological and neural prosthetic medical systems. Topics: action potential generation and propagation, neuroMEMS and measurement systems, experimental design and statistical data analysis, information encoding and decoding, clinical diagnostic systems, and fullyimplantable neural prosthetic systems design. Prerequisite: EE 101A and EE 102A.
Terms: Win

Units: 3

UG Reqs: WAYSMA

Grading: Letter or Credit/No Credit
EE 133:
Analog Communications Design Laboratory (EE 233)
Design, testing, and applications of Radio Frequency (RF) electronics: Amplitude Modulation (AM), Frequency Modulation (FM) and concepts of Software Define Radio (SDR) systems. Practical aspects of circuit implementations are developed; labs involve building and characterization of subsystems as well as integration of a complete radio system and a final project. Total enrollment limited to 25 students¿undergraduate and graduate levels. Prerequisite: EE101B. Undergraduate students enroll in EE133 for 4 units and Graduate students enroll in EE233 for 3 units. Recommended: EE114/214A.
Terms: Win

Units: 34

Grading: Letter or Credit/No Credit
EE 134:
Introduction to Photonics
Photonics, optical components, and fiber optics. Conceptual and mathematical tools for design and analysis of optical communication, sensor and imaging systems. Experimental characterization of semiconductor lasers, optical fibers, photodetectors, receiver circuitry, fiber optic links, optical amplifiers, and optical sensors. Class project on confocal microscopy or other method of sensing or analyzing biometric data. Laboratory experiments. Prerequisite: EE 102A and one of the following: EE 42, Physics 43, or Physics 63.
Terms: Win

Units: 4

UG Reqs: GER:DBEngrAppSci

Grading: Letter (ABCD/NP)
EE 142:
Engineering Electromagnetics
Introduction to electromagnetism and Maxwell's equations in static and dynamic regimes. Electrostatics and magnetostatics: Gauss's, Coulomb's, Faraday's, Ampere's, BiotSavart's laws. Electric and magnetic potentials. Boundary conditions. Electric and magnetic field energy. Electrodynamics: Wave equation; Electromagnetic waves; Phasor form of Maxwell's equations.nSolution of the wave equation in 1D free space: Wavelength, wavevector, forward and backward propagating plane waves.Poynting's theorem. Propagation in lossy media, skin depth. Reflection and refraction at planar boundaries, total internal reflection. Solutions of wave equation for various 1D3D problems: Electromagnetic resonators, waveguides periodic media, transmission lines. Formerly EE 141. Prerequisites: Phys 43 or EE 42, CME 100, CME 102 (recommended)
Terms: Spr

Units: 3

UG Reqs: GER:DBEngrAppSci, WAYFR, WAYSMA

Grading: Letter (ABCD/NP)
EE 153:
Power Electronics (EE 253)
Addressing the energy challenges of today and the environmental challenges of the future will require efficient energy conversion techniques. This course will discuss the circuits used to efficiently convert ac power to dc power, dc power from one voltage level to another, and dc power to ac power. The components used in these circuits (e.g., diodes, transistors, capacitors, inductors) will also be covered in detail to highlight their behavior in a practical implementation. A lab will be held with the class where students will obtain hands on experience with power electronic circuits. For WIM credit, students must enroll in EE 153 for 4 units. No exceptions. Formerly EE 292J. Prerequisite: EE 101B.
Terms: Spr

Units: 34

UG Reqs: WAYSMA

Grading: Letter (ABCD/NP)
EE 155:
Green Electronics (EE 255)
Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energyconserving control systems have at their heart intelligent, highpower electronics. This course examines this technology and uses greentech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steadystate analysis, control, motors and drives, photovoltaic systems, and design of magnetic components. The course involves a handson laboratory and a substantial final project. Formerly EE 152. Required: EE101B, EE102A, EE108. Recommended: ENGR40 or EE122A.
Terms: not given this year

Units: 4

Grading: Letter or Credit/No Credit
EE 168:
Introduction to Digital Image Processing
Computer processing of digital 2D and 3D data, combining theoretical material with implementation of computer algorithms. Topics: properties of digital images, design of display systems and algorithms, time and frequency representations, filters, image formation and enhancement, imaging systems, perspective, morphing, and animation applications. Instructional computer lab exercises implement practical algorithms. Final project consists of computer animations incorporating techniques learned in class. For WIM credit, students must enroll for 4 units. No exceptions. Prerequisite: Matlab programming.
Terms: Win

Units: 34

Grading: Letter or Credit/No Credit
EE 178:
Probabilistic Systems Analysis
Introduction to probability and statistics and their role in modeling and analyzing real world phenomena. Events, sample space, and probability. Discrete random variables, probability mass functions, independence and conditional probability, expectation and conditional expectation. Continuous random variables, probability density functions, independence and expectation, derived densities. Transforms, moments, sums of independent random variables. Simple random processes. Limit theorems. Introduction to statistics: significance, estimation and detection. Prerequisites: basic calculus.
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci

Grading: Letter or Credit/No Credit
EE 180:
Digital Systems Architecture
The design of processorbased digital systems. Instruction sets, addressing modes, data types. Assembly language programming, lowlevel data structures, introduction to operating systems and compilers. Processor microarchitecture, microprogramming, pipelining. Memory systems and caches. Input/output, interrupts, buses and DMA. System design implementation alternatives, software/hardware tradeoffs. Labs involve the design of processor subsystems and processorbased embedded systems. Formerly EE 108B. Prerequisite: CS107 (required) and EE108 (recommended but not required).
Terms: Spr

Units: 4

UG Reqs: GER:DBEngrAppSci, WAYSMA

Grading: Letter or Credit/No Credit
EE 190:
Special Studies or Projects in Electrical Engineering
Independent work under the direction of a faculty member. Individual or team activities involve lab experimentation, design of devices or systems, or directed reading. Course may be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Satisfactory/No Credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
EmamiNaeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Giovangrandi, L. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Paulraj, A. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Thompson, N. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wooley, B. (PI);
Wootters, M. (PI);
Yamamoto, Y. (PI);
Zebker, H. (PI)
EE 191:
Special Studies and Reports in Electrical Engineering
Independent work under the direction of a faculty member given for a letter grade only. If a letter grade given on the basis of required written report or examination is not appropriate, enroll in 190. Course may be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Letter (ABCD/NP)
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
EmamiNaeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Moslehi, M. (PI);
Murmann, B. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 191A:
Special Studies and Reports in Electrical Engineering
EE191A is part of the Accelerated Calculus for Engineers program. Independent work under the direction of a faculty member given for a letter grade only. EE 191A counts as a Math one unit seminar course: it is this unit that constitutes the ACE program.
Terms: Aut, Win, Spr

Units: 1

Grading: Letter (ABCD/NP)
EE 191W:
Special Studies and Reports in Electrical Engineering (WIM)
WIMversion of EE 191. For EE students using special studiesn(e.g., honors project, independent research project) to satisfy thenwritinginmajor requirement. A written report that has gone through revision with an advisor is required. An advisor from the Writing Center is recommended.
Terms: Aut, Win, Spr, Sum

Units: 310

Grading: Letter (ABCD/NP)
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur Aydin, A. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
RivasDavila, J. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 195:
Electrical Engineering Instruction
Students receive training from faculty or graduate student mentors to prepare them to assist in instruction of Electrical Engineering courses. The specific training and units of credit received are to be defined in consultation with one of the official instructors of EE 195. Note that University regulations prohibit students from being paid for the training while receiving academic credit for it. Enrollment limited.
Terms: Aut, Win, Spr

Units: 13

Grading: Satisfactory/No Credit
EE 205:
Product Management for Electrical Engineers and Computer Scientists
Successful products are the highest impact contribution anyone can make in product development. Students will learn to build successful products using fundamental concepts in Product Management. These include understanding customers, their job to be done, Identifying new product opportunities, and defining what to build that is technically feasible, valuable to the customer, and easy to use The course has two components, Product Management Project with corporate partners, and casebased classroom discussion of PM concepts and application. Prerequisite: Students must be currently enrolled in a MS or PhD engineering degree program.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
EE 212:
Integrated Circuit Fabrication Processes
For students interested in the physical bases and practical methods of silicon VLSI chip fabrication, or the impact of technology on device and circuit design, or intending to pursue doctoral research involving the use of Stanford's Nanofabrication laboratory. Process simulators illustrate concepts. Topics: principles of integrated circuit fabrication processes, physical and chemical models for crystal growth, oxidation, ion implantation, etching, deposition, lithography, and backend processing. Required for 410.
Terms: Aut

Units: 3

Grading: Letter or Credit/No Credit
EE 214A:
Fundamentals of Analog Integrated Circuit Design (EE 114)
Analysis and simulation of elementary transistor stages, current mirrors, supply and temperatureindependent bias, and reference circuits. Overview of integrated circuit technologies, circuit components, component variations and practical design paradigms. Differential circuits, frequency response, and feedback will also be covered. Performance evaluation using computeraided design tools. Undergraduates must take EE 114 for 4 units. Prerequisite: 101B. GER:DBEngrAppSci
Terms: Aut

Units: 34

Grading: Letter (ABCD/NP)
EE 214B:
Advanced Integrated Circuit Design
Analysis and design of analog integrated circuits in advanced MOS and bipolar technologies. Device operation and compact modeling in support of circuit simulations needed for design. Emphasis on quantitative evaluations of performance using hand calculations and circuit simulations; intuitive approaches to design. Analytical and approximate treatments of noise and distortion; analysis and design of feedback circuits. Design of archetypal analog blocks for networking and communications such as broadband gain stages and transimpedance amplifiers. Prerequisites: EE114/214A.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 216:
Principles and Models of Semiconductor Devices
Carrier generation, transport, recombination, and storage in semiconductors. Physical principles of operation of the pn junction, heterojunction, metal semiconductor contact, bipolar junction transistor, MOS capacitor, MOS and junction fieldeffect transistors, and related optoelectronic devices such as CCDs, solar cells, LEDs, and detectors. Firstorder device models that reflect physical principles and are useful for integratedcircuit analysis and design. Prerequisite: 116 or equivalent.
Terms: Aut, Win, Sum

Units: 3

Grading: Letter or Credit/No Credit
EE 218:
Power Semiconductor Devices and Technology
This course starts by covering the device physics and technology of current silicon power semiconductor devices including power MOSFETs, IGBTs, and Thyristors. Wide bandgap materials, especially GaN and SiC are potential replacements for Si power devices because of their fundamentally better properties. This course explores what is possible in these new materials, and what the remaining challenges are for wide bandgap materials to find widespread market acceptance in power applications. Future clean, renewable energy systems and high efficiency power control systems will critically depend on the higher performance devices possible in these new materials. Prerequisites: EE 116 or equivalent.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 222:
Applied Quantum Mechanics I (MATSCI 201)
Emphasis is on applications in modern devices and systems. Topics include: Schrödinger's equation, eigenfunctions and eigenvalues, solutions of simple problems including quantum wells and tunneling, quantum harmonic oscillator, coherent states, operator approach to quantum mechanics, Dirac notation, angular momentum, hydrogen atom, calculation techniques including matrix diagonalization, perturbation theory, variational method, and timedependent perturbation theory with applications to optical absorption, nonlinear optical coefficients, and Fermi's golden rule. Prerequisites: MATH 52 and 53, EE 65 or PHYSICS 65 (or PHYSICS 43 and 45).
Terms: Aut

Units: 3

Grading: Letter or Credit/No Credit
EE 223:
Applied Quantum Mechanics II
Continuation of 222, including more advanced topics: quantum mechanics of crystalline materials, methods for onedimensional problems, spin, systems of identical particles (bosons and fermions), introductory quantum optics (electromagnetic field quantization, coherent states), fermion annihilation and creation operators, interaction of different kinds of particles (spontaneous emission, optical absorption, and stimulated emission). Quantum information and interpretation of quantum mechanics. Other topics in electronics, optoelectronics, optics, and quantum information science. Prerequisite: 222.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 225:
Biochips and Medical Imaging (MATSCI 382, SBIO 225)
The course covers stateoftheart and emerging biosensors, biochips, imaging modalities, and nanotherapies which will be studied in the context of human physiology including the nervous system, circulatory system and immune system. Medical diagnostics will be divided into biochips (invitro diagnostics) and medical and molecular imaging (invivo imaging). Indepth discussion on cancer and cardiovascular diseases and the role of diagnostics and nanotherapies.
Terms: not given this year

Units: 3

Grading: Letter or Credit/No Credit
EE 233:
Analog Communications Design Laboratory (EE 133)
Design, testing, and applications of Radio Frequency (RF) electronics: Amplitude Modulation (AM), Frequency Modulation (FM) and concepts of Software Define Radio (SDR) systems. Practical aspects of circuit implementations are developed; labs involve building and characterization of subsystems as well as integration of a complete radio system and a final project. Total enrollment limited to 25 students¿undergraduate and graduate levels. Prerequisite: EE101B. Undergraduate students enroll in EE133 for 4 units and Graduate students enroll in EE233 for 3 units. Recommended: EE114/214A.
Terms: Win

Units: 34

Grading: Letter or Credit/No Credit
EE 234:
Photonics Laboratory
Photonics and fiber optics with a focus on communication and sensing. Experimental characterization of semiconductor lasers, optical fibers, photodetectors, receiver circuitry, fiber optic links, optical amplifiers, and optical sensors and photonic crystals. Prerequisite: EE 236A (recommended).
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
EE 235:
Analytical Methods in Biotechnology
This course provides fundamental principles underlying important analytical techniques used in modern biotechnology. The course comprises of lectures and handson laboratory experiments. Students will learn the core principles for designing, implementing and analyzing central experimental methods including polymerase chain reaction (PCR), electrophoresis, immunoassays, and highthroughput sequencing. The overall goal of the course is to enable engineering students with little or no background in molecular biology to transition into research in the field of biomedicine.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 236A:
Modern Optics
Geometrical optics; lens analysis and design, aberrations, optical instruments, radiometry. ray matrices. Wave nature of light; polarization, plane waves at interfaces and in media with varying refractive index, diffraction, Fourier Optics, Gaussian beams. Interference; singlebeam interferometers (FabryPerot), multiplebeam interferometers (Michelson, MachZehnder). nPrerequisites: EE 142 or familiarity with electromagnetism and plane waves.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
EE 236B:
Guided Waves
Maxwell's equations, constitutive relations. KramersKronig relations. Modes in waveguides: slab, rectangular, circular. Photonic crystals, surface plasmon modes. General properties of waveguide modes: orthogonality, phase and group indices, group velocity dispersion. Chirped pulse propagation in dispersive media and its connection to Gaussian beam propagation. Time lens. Waveguide technologies: glass, silicon, IIIV semiconductor, metallic. Waveguide devices: fibers, lasers, modulators, arrayed waveguide gratings. Scattering matrix description of passive optical devices, and constraints from energy conservation, timereversal symmetry and reciprocity. Mode coupling, directional couplers, distributedfeedback structures. Resonators from scattering matrix and inputoutput perspective. Microring resonators. Prerequisites: EE 236A and EE 242 or familiarity with differential form of Maxwell's equations.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 236C:
Lasers
Atomic systems, spontaneous emission, stimulated emission, amplification. Three and fourlevel systems, rate equations, pumping schemes. Laser principles, conditions for steadystate oscillation. Transverse and longitudinal mode control and tuning. Exemplary laser systems: gas (HeNe), solid state (Nd:YAG, Ti:sapphire) and semiconductors. Elements of laser dynamics and noise. Formerly EE231. Prerequisites: EE 236B and familiarity with modern physics and semiconductor physics. Recommended: EE 216 and EE 223 (either may be taken concurrently).
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 238:
Introduction to Fourier Optics
Fourier analysis applied to optical imaging. Theoretical topics include Fourier transform and angular spectrum to describe diffraction, Fourier transforming properties of lenses, image formation with coherent and incoherent light and aberrations. Application topics will cover image deconvolution/reconstruction, amplitude and phase pupil engineering, computational adaptive optics, and others motivated by student interest. Prerequisites: familiarity with Fourier transform and analysis, EE 102 and EE 142 or equivalent.
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
EE 242:
Electromagnetic Waves
This course will provide an advanced treatment of electromagnetic waves in free space and media. The first part of the course will cover reflection, refraction, resonators, and waveguides. The second part will cover general concepts in finitedifference timedomain (FDTD) computation, and students will be introduced to commercial FDTD software. The third part will cover potentials, Green's functions, farfield radiation, nearfield radiation, and antennas. The fourth part will focus on an analysis of EM waves in matter. In lieu of a final exam, students will perform a quantitative group project based on a technical paper or research idea. This course will serve as a foundation for other specialized 200 and 300level optics courses. Prerequisites: EE 142 or PHYSICS 120.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
EE 247:
Introduction to Optical Fiber Communications
Fibers: single and multimode, attenuation, modal dispersion, groupvelocity dispersion, polarizationmode dispersion. Nonlinear effects in fibers: Raman, Brillouin, Kerr. Self and crossphase modulation, fourwave mixing. Sources: lightemitting diodes, laser diodes, transverse and longitudinal mode control, modulation, chirp, linewidth, intensity noise. Modulators: electrooptic, electroabsorption. Photodiodes: pin, avalanche, responsivity, capacitance, transit time. Receivers: highimpedance, transimpedance, bandwidth, noise. Digital intensity modulation formats: nonreturntozero, returntozero. Receiver performance: Q factor, biterror ratio, sensitivity, quantum limit. Sensitivity degradations: extinction ratio, intensity noise, jitter, dispersion. Wavelengthdivision multiplexing. System architectures: localarea, access, metropolitanarea, longhaul. Prerequisites: EE 102A and EE 142.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 251:
HighFrequency Circuit Design Laboratory
Students will study the theory of operation of instruments such as the timedomain reflectometer, sampling oscilloscope and vector network analyzer. They will build on that theoretical foundation by designing, constructing and characterizing numerous wireless building blocks in the upperUHF range (e.g., up to about 500MHz), in a running series of laboratory exercises that conclude in a final project. Examples include impedancematching and coupling structures, filters, narrowband and broadband amplifiers, mixers/modulators, and voltagecontrolled oscillators. Prerequisite: EE 114 or EE 214A.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
EE 252:
Antennas
This course aims to cover the theory, simulation, and handson experiment in antenna design. Topics include: basic parameters to describe the performance and characteristics of an antenna, link budget analyses, solving the fields from a Hertizian dipole, duality, equivalence principle, reciprocity, linear wire antenna, circular loop antenna, antenna array, slot and patch antennas, helical antennas, wideband antennas, size reduction techniques, wideband small antennas, and circularly polarized (CP) small antennas. Students will learn to use a commercial electromagnetic stimulator in lab sessions. A final project is designed to solve a research antenna design problem in biomedical area or wireless communications. Prerequisite: EE 142 or Physics 120 or equivalent. Enrollment capacity limited to 25 students.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 253:
Power Electronics (EE 153)
Addressing the energy challenges of today and the environmental challenges of the future will require efficient energy conversion techniques. This course will discuss the circuits used to efficiently convert ac power to dc power, dc power from one voltage level to another, and dc power to ac power. The components used in these circuits (e.g., diodes, transistors, capacitors, inductors) will also be covered in detail to highlight their behavior in a practical implementation. A lab will be held with the class where students will obtain hands on experience with power electronic circuits. For WIM credit, students must enroll in EE 153 for 4 units. No exceptions. Formerly EE 292J. Prerequisite: EE 101B.
Terms: Spr

Units: 34

Grading: Letter (ABCD/NP)
EE 255:
Green Electronics (EE 155)
Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energyconserving control systems have at their heart intelligent, highpower electronics. This course examines this technology and uses greentech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steadystate analysis, control, motors and drives, photovoltaic systems, and design of magnetic components. The course involves a handson laboratory and a substantial final project. Formerly EE 152. Required: EE101B, EE102A, EE108. Recommended: ENGR40 or EE122A.
Terms: not given this year

Units: 4

Grading: Letter or Credit/No Credit
EE 261:
The Fourier Transform and Its Applications
The Fourier transform as a tool for solving physical problems. Fourier series, the Fourier transform of continuous and discrete signals and its properties. The Dirac delta, distributions, and generalized transforms. Convolutions and correlations and applications; probability distributions, sampling theory, filters, and analysis of linear systems. The discrete Fourier transform and the FFT algorithm. Multidimensional Fourier transform and use in imaging. Further applications to optics, crystallography. Emphasis is on relating the theoretical principles to solving practical engineering and science problems. Prerequisites: Math through ODEs, basic linear algebra, Comfort with sums and discrete signals, Fourier series at the level of 102A
Terms: Win, Sum

Units: 3

Grading: Letter or Credit/No Credit
EE 262:
TwoDimensional Imaging
Time and frequency representations, twodimensional auto and crosscorrelation, Fourier spectra, diffraction and antennas, coordinate systems and the Hankel and Abel transforms, line integrals, impulses and sampling, restoration in the presence of noise, reconstruction and tomography, imaging radar. Tomographic reconstruction using projectionslice and layergarm methods. Students create software to form images using these techniques with actual data. Final project consists of design and simulation of an advanced imaging system. Prerequisite: EE261. Recommended: EE278, EE279.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 263:
Introduction to Linear Dynamical Systems (CME 263)
Applied linear algebra and linear dynamical systems with applications to circuits, signal processing, communications, and control systems. Topics: leastsquares approximations of overdetermined equations, and leastnorm solutions of underdetermined equations. Symmetric matrices, matrix norm, and singularvalue decomposition. Eigenvalues, left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multiinput/multioutput systems, impulse and step matrices; convolution and transfermatrix descriptions. Control, reachability, and state transfer; observability and leastsquares state estimation. Prerequisites: Linear algebra and matrices as in EE 103 or MATH 104; ordinary differential equations and Laplace transforms as in EE 102B or CME 102.
Terms: Aut, Sum

Units: 3

Grading: Letter or Credit/No Credit
EE 264:
Digital Signal Processing
Digital signal processing (DSP) techniques and design of DSP applications. Topics include: discretetime random signals; sampling and multirate systems; oversampling and quantization in AtoD conversion; properties of LTI systems; quantization in fixedpoint implementations of filters; digital filter design; discrete Fourier Transform and FFT; spectrum analysis using the DFT; and LMS adaptive filtering. The course also covers applications of DSP in areas such as speech, audio and communication systems. The optional (1 extra credit hour) lab provides a handson opportunity to explore the application of DSP theory to practical realtime applications in an embedded processing platform. See ee264.stanford.edu for more information. The optional lab is not available to remote SCPD students. Prerequisites: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)
Terms: Spr, Sum

Units: 34

Grading: Letter or Credit/No Credit
EE 264W:
Digital Signal Processing (WIM)
EE 264W: Digital Signal Processing (WIM)nWriting in the Major (WIM) version of the 4unit EE 264 theory + lab/project course. This course also meets the EE design requirement. Topics include: discretetime random signals; sampling and multirate systems; oversampling and quantization in AtoD conversion; properties of LTI systems; quantization in fixedpoint implementations of filters; digital filter design; discrete Fourier Transform and FFT; spectrum analysis using the DFT; and LMS adaptive filtering. The course also covers applications of DSP in areas such as speech, audio and communication systems. The optional (1 extra credit hour) lab provides a handson opportunity to explore the application of DSP theory to practical realtime applications in an embedded processing platform. See ee264.stanford.edu for more information. The optional lab is not available to remote SCPD students. Prerequisite: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)
Terms: Spr

Units: 5

Grading: Letter or Credit/No Credit
EE 266:
Introduction to Stochastic Control with Applications (MS&E 251)
Focuses on conceptual foundation and algorithmic methodology of Dynamic Programming and Stochastic Control with applications to engineering, operations research, management science and other fields. Elaborates on the concept of probing, learning and control of stochastic systems, and addresses the practical application of the concept and methodology through the use of approximations. Prerequisites: 201, 221, or equivalents.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 267:
Virtual Reality
OpenGL, realtime rendering, 3D display systems, display optics & electronics, IMUs and sensors, tracking, haptics, rendering pipeline, multimodal human perception and depth perception, stereo rendering, presence. Emphasis on VR technology. Handson programming assignments. The 3unit version requires a final programming assignment in which you create your own virtual environment. The 4unit version requires a final course project and written report in lieu of the final assignment. Prerequisites: Strong programming skills, EE 103 or equivalent. Helpful: basic computer graphics / OpenGL.
Terms: Spr

Units: 34

Grading: Letter or Credit/No Credit
EE 267W:
Virtual Reality (WIM)
Writing in the Major (WIM) version of the 4unit EE 267 theory + lab/project course. This course also meets the EE design requirement. Topics include: OpenGL, realtime rendering, 3D display systems, display optics & electronics, IMUs and sensors, tracking, haptics, rendering pipeline, multimodal human perception and depth perception, stereo rendering, presence. Emphasis on VR technology. Handson programming assignments. The 5unit WIM version requires everything the 4unit version does, i.e. a final course project and written report in lieu of the final assignment. The 5unit WIM version additional requires participation in 2 writing in the major workshops, and weekly writing assignments. Prerequisites: Strong programming skills, EE 103 or equivalent. Helpful: basic computer graphics / OpenGL.
Terms: Spr

Units: 5

Grading: Letter or Credit/No Credit
EE 269:
Signal Processing for Machine Learning
This course will introduce you to fundamental signal processing concepts and tools needed to apply machine learning to discrete signals. You will learn about commonly used techniques for capturing, processing, manipulating, learning and classifying signals. The topics include: mathematical models for discretetime signals, vector spaces, Fourier analysis, timefrequency analysis, Ztransforms and filters, signal classification and prediction, basic image processing, compressed sensing and deep learning. This class will culminate in a final project. Prerequisites: EE 102A and EE 102B or equivalent, basic programming skills (Matlab). EE 103 and EE 178 are recommended.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 271:
Introduction to VLSI Systems
Provides a quick introduction to MOS transistors and IC fabrication and then creates abstractions to allow you to create and reason about complex digital systems. It uses a switch resistor model of a transistor, uses it to model gates, and then shows how gates and physical layout can be synthesized from Verilog or SystemVerilog descriptions. Most of the class will be spent on providing techniques to create designs that can be validated, are low power, provide good performance, and can be completed in finite time. Prerequisites: 101A, 108A and 108B; familiarity with transistors, logic design, Verilog and digital system organization
Terms: Aut

Units: 3

Grading: Letter or Credit/No Credit
EE 272:
Design Projects in VLSI Systems
An introduction to mixed signal design. Working in teams you will create a small mixedsignal VLSI design using a modern design flow and CAD tools. The project involves writing a Verilog model of the chip, creating a testing/debug strategy for your chip, wrapping custom layout to fit into a std cell system, using synthesis and place and route tools to create the layout of your chip, and understanding all the weird stuff you need to do to tapeout a chip. Useful for anyone who will build a chip in their Ph.D. Prerequsiites: EE271 and experience in digital/analog circuit design.
Terms: Win

Units: 34

Grading: Letter or Credit/No Credit
EE 273:
Digital Systems Engineering
Electrical issues in the design of highperformance digital systems, including signaling, timing, synchronization, noise, and power distribution. Highspeed signaling methods; noise in digital systems, its effect on signaling, and methods for noise reduction; timing conventions; timing noise (skew and jitter), its effect on systems, and methods for mitigating timing noise; synchronization issues and synchronizer design; clock and power distribution problems and techniques; impact of electrical issues on system architecture and design. Prerequisites: EE101A and EE108A. Recommended: EE114/214A.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 278:
Introduction to Statistical Signal Processing
Review of basic probability and random variables. Random vectors and processes; convergence and limit theorems; IID, independent increment, Markov, and Gaussian random processes; stationary random processes; autocorrelation and power spectral density; mean square error estimation, detection, and linear estimation. Formerly EE 278B. Prerequisites: EE178 and linear systems and Fourier transforms at the level of EE102A,B or EE261.
Terms: Aut, Sum

Units: 3

Grading: Letter or Credit/No Credit
EE 279:
Introduction to Digital Communication
Digital communication is a rather unique field in engineering in which theoretical ideas have had an extraordinary impact on the design of actual systems. The course provides a basic understanding of the analysis and design of digital communication systems, building on various ideas from probability theory, stochastic processes, linear algebra and Fourier analysis. Topics include: detection and probability of error for binary and Mary signals (PAM, QAM, PSK), receiver design and sufficient statistics, controlling the spectrum and the Nyquist criterion, bandpass communication and up/down conversion, design tradeoffs: rate, bandwidth, power and error probability, coding and decoding (block codes, convolutional coding and Viterbi decoding). Prerequisites: 179 or 261, and 178 or 278
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 282:
Computer Systems Architecture
Course focuses on how to build modern computing systems, namely notebooks, smartphones, and data centers, covering primarily their hardware architecture and certain system software aspects. For each system class, we cover the system architecture, processor technology, advanced memory hierarchy and I/O organization, power and energy management, and reliability. We will also cover topics such as interactions with system software, virtualization, solid state storage, and security. The programming assignments allow students to explore performance/energy tradeoffs when using heterogeneous hardware resources on smartphone devices. Prerequisite: EE108B. Recommended: CS 140.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 284:
Introduction to Computer Networks
Structure and components of computer networks; functions and services; packet switching; layered architectures; OSI reference model; physical layer; data link layer; error control; window flow control; media access control protocols used in local area networks (Ethernet, Token Ring, FDDI) and satellite networks; network layer (datagram service, virtual circuit service, routing, congestion control, Internet Protocol); transport layer (UDP, TCP); application layer.
Terms: Aut

Units: 3

Grading: Letter or Credit/No Credit
EE 284A:
Introduction to Internet of Things
Internet of Things (IoT) origin, vision and definition. Application domains, use case scenarios and value propositions. Functional blocks of IoT systems: devices, communications, services, management, security, and application. Architectural reference model and design methodology. IoT Devices: sensors, actuators and embedded systems. Communications aspects of IoT systems: Internet infrastructure; wireless local area networks; radio access networks; wireless personal area networks; wireless sensor networks; wireless communication in vehicular environments; 5G. Current IoT frameworks and underlying architectures. Data storage and analytics. Web services. IoT system management tools. Security aspects of IoT systems. Open issues.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 290A:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in EE290A; for 290C, EE PhD degree candidacy and an "S" grade in EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in EE 290C and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 290B:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in EE290A; for 290C, EE PhD degree candidacy and an "S" grade in EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in EE 290C and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 290C:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in EE290A; for 290C, EE PhD degree candidacy and an "S" grade in EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in EE 290C and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 290D:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in EE290A; for 290C, EE PhD degree candidacy and an "S" grade in EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in EE 290C and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 290E:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: for 290B, EE MS and PhD students who have received a Satisfactory ("S") grade in EE290A; for 290C, EE PhD degree candidacy and an "S" grade in EE 290B; for 290D, EE PhD degree candidacy, an "S" grade in EE 290C and instructor consent; for 290E, EE PhD degree candidacy, an "S" grade in EE 290D and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 290F:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: EE PhD degree candidacy, an "S" grade in EE 290E and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 290G:
Curricular Practical Training for Electrical Engineers
For EE majors who need work experience as part of their program of study. Final report required. Prerequisites: EE PhD degree candidacy, an "S" grade in EE 290F and instructor consent.
Terms: Aut, Win, Spr, Sum

Units: 1

Grading: Satisfactory/No Credit
EE 292A:
Electronic Design Automation (EDA) and Machine Learning Hardware
The class teaches cuttingedge optimization and analysis algorithms for the design of complex digital integrated circuits and their use in designing machine learning hardware. It provides working knowledge of the key technologies in Electronic Design Automation (EDA), focusing on synthesis, placement and routing algorithms that perform the major transformations between levels of abstraction and get a design ready to be fabricated. As an example, the design of a convolutional neural network (CNN) for basic image recognition illustrates the interaction between hardware and software for machine learning. It will be implemented on a stateoftheart FPGA board. Prerequisite: EE 108.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 292C:
Chemical Vapor Deposition and Epitaxy for Integrated Circuits and Nanostructures
Fundamental aspects of CVD are initially considered, first focusing on processes occurring in the gas phase and then on those occurring on the surface. Qualitative understanding is emphasized, with minimal use of equations. Adding energy both thermally and by using a plasma is discussed; atomiclayer deposition is briefly considered. Examples of CVD equipment are examined. The second portion of the tutorial examines layers deposited by CVD. The focus is on group IV semiconductors ¿ especially epitaxial and heteroepitaxial deposition, in which the crystal structure of the depositing layer is related to that of the substrate. Polycrystalline silicon and the IC interconnect system are then discussed. Finally, the use of highdensity plasmas for rapid gap filling is contrasted with alternative CVD dielectric deposition processes.
Terms: Win

Units: 1

Grading: Satisfactory/No Credit
EE 292E:
Seminar Series for Image Systems Engineering
Seminar. For engineering students interested in camera and display engineering, computer vision, and computational imaging. Speakers include Stanford faculty and research scientists as well as industry professionals, mostly from consumer electronics companies.
Terms: Aut, Win, Spr

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 292H:
Engineering, Entrepreneurship & Climate Change
The purpose of this seminar series course is to help students and professionals develop the tools to apply the engineering and entrepreneurial mindset to problems that stem from climate change, in order to consider and evaluate possible stabilizing, remedial and adaptive approaches. This course is not a crash course on climate change or policy. Instead we will focus on learning about and discussing the climate problems that seem most tractable to these approaches. Each week Dr. Field and/or a guest speaker will lead a short warmup discussion/activity and then deliver a talk in his/her area of expertise. We will wrap up with smallgroup and fullclass discussions of related challenges/opportunities and possible engineeringoriented solutions. Class members are asked to do background reading before each class, to submit a question before each lecture, and to do inclass brainstorming. May be repeated for credit.
Terms: Aut

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 292I:
Insanely Great Products: How do they get built?
Great products emerge from a sometimes conflictladen process of collaboration between different functions within companies. This Seminar seeks to demystify this process via casestudies of successful products and companies. Engineering management and businesspeople will share their experiences in discussion with students. Previous companies profiled: Apple, Intel, Facebook, and Genentech  to name a few. Previous guests include: Jon Rubinstein (NeXT, Apple, Palm), Diane Greene (VMware), and Ted Hoff (Intel). Prerequisites: None
Terms: Spr

Units: 1

Grading: Satisfactory/No Credit
EE 292T:
SmartGrids and Advanced Power Systems Seminar (CEE 272T)
A series of seminar and lectures focused on power engineering. Renowned researchers from universities and national labs will deliver biweekly seminars on the state of the art of power system engineering. Seminar topics may include: power system analysis and simulation, control and stability, new market mechanisms, computation challenges and solutions, detection and estimation, and the role of communications in the grid. The instructors will cover relevant background materials in the inbetween weeks. The seminars are planned to continue throughout the next academic year, so the course may be repeated for credit.
Terms: Aut, Win, Spr

Units: 12

Repeatable for credit

Grading: Satisfactory/No Credit
EE 293:
Energy storage and conversion: Solar Cells, Fuel Cells, Batteries and Supercapacitors (ENERGY 293)
This course provides an introduction and engineering exposure to energy storage and conversion systems and will cover the basic physics, chemistry and electrochemistry of solar cells, fuel cells, batteries and supercapacitors, state of the art of such technologies and recent developments. The course will also cover experimental methods and modeling tools for simulation and optimization aimed at characterizing efficiency and performance issues. Prerequisites: Equivalent coursework in thermodynamics, electronic properties, chemical principles, electricity, and magnetism.
Terms: Aut

Units: 34

Grading: Letter or Credit/No Credit
EE 293B:
Fundamentals of Energy Processes (ENERGY 293B)
For seniors and graduate students. Covers scientific and engineering fundamentals of renewable energy processes involving heat. Thermodynamics, heat engines, solar thermal, geothermal, biomass. Recommended: MATH 1921; PHYSICS 41, 43, 45
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 300:
Master's Thesis and Thesis Research
Independent work under the direction of a department faculty. Written thesis required for final letter grade. The continuing grade 'N' is given in quarters prior to thesis submission. See 390 if a letter grade is not appropriate. Course may be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Letter (ABCD/NP)
Instructors: ;
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
EmamiNaeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 303:
Autonomous Implantable Systems
Integrating electronics with sensing, stimulation, and locomotion capabilities into the body will allow us to restore or enhance physiological functions. In order to be able to insert these electronics into the body, energy source is a major obstacle. This course focuses on the analysis and design of wirelessly powered catheterdeliverable electronics. Emphases will be on the interaction between human and electromagnetic fields in order to transfer power to the embedded electronics via electromagnetic fields, power harvesting circuitry, electricaltissue interface, and sensing and actuating frontend designs. Prerequisites: EE 252 or equivalent.
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
EE 308:
Advanced Circuit Techniques
Design of advanced analog circuits at the system level, including switching power converters, amplitudestabilized and frequencystabilized oscillators, voltage references and regulators, power amplifiers and buffers, sampleandhold circuits, and applicationspecific opamp compensation. Approaches for finding creative design solutions to problems with difficult specifications and hard requirements. Emphasis on feedback circuit techniques, designoriented thinking, and handson experience with modern analog building blocks. Several designs will be built and evaluated, along with associated laboratory projects. Prerequisite: EE 251 or EE 314A.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 310:
SystemX: Ubiquitous Sensing, Computing and Communication Seminar
This is a seminar course with invited speakers. Sponsored by Stanford's SystemX Alliance, the talks will cover emerging topics in contemporary hardware/software systems design. Special focus will be given to the key building blocks of sensors, processing elements and wired/wireless communications, as well as their foundations in semiconductor technology, SoC construction, and physical assembly as informed by the SystemX Focus Areas. The seminar will draw upon distinguished engineering speakers from both industry and academia who are involved at all levels of the technology stack and the applications that are now becoming possible. May be repeat for credit
Terms: Aut, Win, Spr

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 311:
Advanced Integrated Circuits Technology
What are the practical and fundamental limits to the evolution of the technology of modern MOS devices and interconnects? How are modern devices and circuits fabricated and what future changes are likely? Advanced techniques and models of MOS devices and backend (interconnect and contact) processing. What are future device structures and materials to maintain progress in integrated electronics? MOS frontend and backend process integration. Prerequisites: EE 216 or equivalent. Recommended: EE 212.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 312:
Integrated Circuit Fabrication Laboratory
Formerly EE 410. Fabrication, simulation, and testing of a submicron CMOS process. Practical aspects of IC fabrication including silicon wafer cleaning, photolithography, etching, oxidation, diffusion, ion implantation, chemical vapor deposition, physical sputtering, and electrical testing. Students also simulate the CMOS process using process simulator TSUPREM4 of the structures and electrical parameters that should result from the process flow. Taught in the Stanford Nanofabrication Facility (SNF). Preference to students pursuing doctoral research program requiring SNF facilities. Enrollment limited to 20. Prerequisites: EE 212, EE 216, or consent of instructor.
Terms: Win

Units: 34

Grading: Letter (ABCD/NP)
EE 314A:
RF Integrated Circuit Design
Design of RF integrated circuits for communications systems, primarily in CMOS. Topics: the design of matching networks and lownoise amplifiers at RF, mixers, modulators, and demodulators; review of classical control concepts necessary for oscillator design including PLLs and PLLbased frequency synthesizers. Design of low phase noise oscillators. Design of highefficiency (e.g., class E, F) RF power amplifiers, coupling networks. Behavior and modeling of passive and active components at RF. Narrowband and broadband amplifiers; noise and distortion measures and mitigation methods. Overview of transceiver architectures. Prerequisite: EE214B.
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
EE 315:
AnalogDigital Interface Circuits
Analysis and design of circuits and circuit architectures for signal conditioning and data conversion. Fundamental circuit elements such as operational transconductance amplifiers, active filters, sampling circuits, switched capacitor stages and voltage comparators. Sensor interfaces for microelectromechanical and biomedical applications. Nyquist and oversampling A/D and D/A converters. Prerequisite: EE 214B.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
EE 336:
Nanophotonics (MATSCI 346)
Recent developments in micro and nanophotonic materials and devices. Basic concepts of photonic crystals. Integrated photonic circuits. Photonic crystal fibers. Superprism effects. Optical properties of metallic nanostructures. Subwavelength phenomena and plasmonic excitations. Metamaterials. Prerequisite: Electromagnetic theory at the level of 242.
Terms: Aut

Units: 3

Grading: Letter or Credit/No Credit
EE 340:
Optical Micro and NanoCavities
Optical micro and nanocavities and their device applications. Types of optical cavities (microdisks, microspheres, photonic crystal cavities, plasmonic cavities), and their electromagnetic properties, design, and fabrication techniques. Cavity quantum electrodynamics: strong and weakcoupling regime, Purcell factor, spontaneous emission control. Applications of optical cavities, including lowthreshold lasers, optical modulators, quantum information processing devices, and biochemical sensors. Prerequisites: Advanced undergraduate or basic graduate level knowledge of electromagnetics, quantum.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 346:
Introduction to Nonlinear Optics
Wave propagation in anisotropic, nonlinear, and timevarying media. Microscopic and macroscopic description of electricdipole susceptibilities. Free and forced waves; phase matching; slowly varying envelope approximation; dispersion, diffraction, spacetime analogy. Harmonic generation; frequency conversion; parametric amplification and oscillation; electrooptic light modulation. Raman and Brillouin scattering; nonlinear processes in optical fibers. Prerequisites: 242, 236C.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 356B:
Magnetics Design in Power Electronics
Inductors and transformers are ubiquitous components in any power electronics system. They are components that offer great design flexibility, provide electrical isolation and can reduce semiconductor stresses, but they often dominate the size and cost of a power converter and are notoriously difficult to miniaturize. In this class we will discuss the design and modeling of magnetic components, which are essential tasks in the development of high performance converters and study advanced applications. Prerequisites: EE153/EE253.
Terms: Aut

Units: 3

Grading: Letter (ABCD/NP)
EE 364A:
Convex Optimization I (CME 364A, CS 334A)
Convex sets, functions, and optimization problems. The basics of convex analysis and theory of convex programming: optimality conditions, duality theory, theorems of alternative, and applications. Leastsquares, linear and quadratic programs, semidefinite programming, and geometric programming. Numerical algorithms for smooth and equality constrained problems; interiorpoint methods for inequality constrained problems. Applications to signal processing, communications, control, analog and digital circuit design, computational geometry, statistics, machine learning, and mechanical engineering. Prerequisite: linear algebra such as EE263, basic probability.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
Instructors: ;
Boyd, S. (PI);
Barratt, S. (TA);
CreusCosta, J. (TA);
Dean, J. (TA);
Diamond, S. (TA);
Garg, S. (TA);
Kim, J. (TA);
Mani, N. (TA);
Pathak, R. (TA);
Sholar, J. (TA);
Spear, L. (TA)
EE 364B:
Convex Optimization II (CME 364B)
Continuation of 364A. Subgradient, cuttingplane, and ellipsoid methods. Decentralized convex optimization via primal and dual decomposition. Monotone operators and proximal methods; alternating direction method of multipliers. Exploiting problem structure in implementation. Convex relaxations of hard problems. Global optimization via branch and bound. Robust and stochastic optimization. Applications in areas such as control, circuit design, signal processing, and communications. Course requirements include project. Prerequisite: 364A.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 367:
Computational Imaging and Display (CS 448I)
Spawned by rapid advances in optical fabrication and digital processing power, a new generation of imaging technology is emerging: computational cameras at the convergence of applied mathematics, optics, and highperformance computing. Similar trends are observed for modern displays pushing the boundaries of resolution, contrast, 3D capabilities, and immersive experiences through the codesign of optics, electronics, and computation. This course serves as an introduction to the emerging field of computational imaging and displays. Students will learn to master bits and photons.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 368:
Digital Image Processing (CS 232)
Image sampling and quantization color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration, feature extraction and recognition tasks, image registration. Emphasis is on the general principles of image processing. Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices. Term project. Recommended: EE261, EE278.
Terms: Win

Units: 3

Grading: Letter (ABCD/NP)
EE 369B:
Medical Imaging Systems II
Imaging internal structures within the body using magnetic resonance studied from a systems viewpoint. Analysis of magnetic resonance imaging systems including physics, Fourier properties of image formation, effects of system imperfections, image contrast, and noise. Prerequisite: EE 261
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 373A:
Adaptive Signal Processing
Learning algorithms for adaptive digital filters. Selfoptimization. Wiener filter theory. Quadratic performance functions, their eigenvectors and eigenvalues. Speed of convergence. Asymptotic performance versus convergence rate. Applications of adaptive filters to statistical prediction, process modeling, adaptive noise canceling, adaptive antenna arrays, adaptive inverse control, and equalization and echo canceling in modems. Artificial neural networks. Cognitive memory/human and machine. Natural and artificial synapses. Hebbian learning. The HebbianLMS algorithm. Theoretical and experimental research projects in adaptive filter theory, communications, audio systems, and neural networks. Biomedical research projects, supervised jointly by EE and Medical School faculty. Recommended: EE263, EE264, EE278.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 376A:
Information Theory (STATS 376A)
Projectbased course about how to measure, represent, and communicate information effectively. Why bits have become the universal currency for information exchange. How information theory bears on the design and operation of modernday systems such as smartphones and the Internet. The role of entropy and mutual information in data compression, communication, and inference. Practical compressors and error correcting codes. The information theoretic way of thinking. Relations and applications to probability, statistics, machine learning, biological and artificial neural networks, genomics, quantum information, and blockchains. Prerequisite: a first undergraduate course in probability.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 376B:
Topics in Information Theory and Its Applications (STATS 376B)
Information theory establishes the fundamental limits on compression and communication over networks. The tools of information theory have also found applications in many other fields, including probability and statistics, computer science and physics. The course will cover selected topics from these applications, including communication networks, through regular lectures and student projects. Prerequisites: EE376A
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 377:
Information Theory and Statistics (STATS 311)
Information theoretic techniques in probability and statistics. Fano, Assouad,nand Le Cam methods for optimality guarantees in estimation. Large deviationsnand concentration inequalities (Sanov's theorem, hypothesis testing, thenentropy method, concentration of measure). Approximation of (Bayes) optimalnprocedures, surrogate risks, fdivergences. Penalized estimators and minimumndescription length. Online game playing, gambling, noregret learning. Prerequisites: EE 376A (or equivalent) or STATS 300A.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 378B:
Inference, Estimation, and Information Processing
Techniques and models for signal, data and information processing, with emphasis on incomplete data, nonordered index sets and robust lowcomplexity methods. Linear models; regularization and shrinkage; dimensionality reduction; streaming algorithms; sketching; clustering, search in high dimension; lowrank models; principal component analysis.nnApplications include: positioning from pairwise distances; distributed sensing; measurement/traffic monitoring in networks; finding communities/clusters in networks; recommendation systems; inverse problems. Prerequisites: EE278 and EE263 or equivalent. Recommended but not required: EE378A
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 379:
Digital Communication
Modulation: linear, differential and orthogonal methods; signal spaces; power spectra; bandwidth requirements. Detection: maximum likelihood and maximum a posteriori probability principles; sufficient statistics; correlation and matchedfilter receivers; coherent, differentially coherent and noncoherent methods; error probabilities; comparison of modulation and detection methods. Intersymbol interference: singlecarrier channel model; Nyquist requirement; whitened matched filter; maximum likelihood sequence detection; Viterbi algorithm; linear equalization; decisionfeedback equalization. Multicarrier modulation: orthogonal frequencydivision multiplexing; capacity of parallel Gaussian channels; comparison of single and multicarrier techniques. Prerequisite: EE102B and EE278 (or equivalents). EE279 is helpful but not required.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 380:
Colloquium on Computer Systems
Live presentations of current research in the design, implementation, analysis, and applications of computer systems. Topics range over a wide range and are different every quarter. Topics may include fundamental science, mathematics, cryptography, device physics, integrated circuits, computer architecture, programming, programming languages, optimization, applications, simulation, graphics, social implications, venture capital, patent and copyright law, networks, computer security, and other topics of related to computer systems. May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 382A:
Parallel Processors Beyond Multicore Processing
Formerly EE392Q. The current parallel computing research emphasizes multicores, but there are alternative array processors with significant potential. This handson course focuses on SIMD (SingleInstruction, MultipleData) massively parallel processors. Topics: Flynn's Taxonomy, parallel architectures, Kestrel architecture and simulator, principles of SIMD programming, parallel sorting with sorting networks, string comparison with dynamic programming (edit distance, SmithWaterman), arbitraryprecision operations with fixedpoint numbers, reductions, vector and matrix multiplication, image processing algorithms, asynchronous algorithms on SIMD ("SIMD Phase Programming Model"), Mandelbrot set, analysis of parallel performance.
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
EE 382C:
Interconnection Networks
The architecture and design of interconnection networks used to communicate from processor to memory, from processor to processor, and in switches and routers. Topics: network topology, routing methods, flow control, router microarchitecture, and performance analysis. Enrollment limited to 30. Prerequisite: 282.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 384A:
Internet Routing Protocols and Standards
Local area networks addressing and switching; IEEE 802.1 bridging protocols (transparent bridging, virtual LANs). Internet routing protocols: interior gateways (RIP, OSPF) and exterior gateways (BGP); multicast routing; multiprotocol label switching (MPLS). Routing in mobile networks: Mobile IP, Mobile Ad Hoc Networks (MANET), Wireless Mesh Networks. Prerequisite: EE 284 or CS 144.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 384S:
Performance Engineering of Computer Systems & Networks
Modeling and control methodologies for highperformance network engineering, including: Markov chains and stochastic modeling, queueing networks and congestion management, dynamic programming and task/processor scheduling, network dimensioning and optimization, and simulation methods. Applications for design of highperformance architectures for wireline/wireless networks and the Internet, including: traffic modeling, admission and congestion control, quality of service support, power control in wireless networks, packet scheduling in switches, video streaming over wireless links, and virus/worm propagation dynamics and countermeasures. Enrollment limited to 30. Prerequisites: basic networking technologies and probability.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit
EE 385A:
Robust and Testable Systems Seminar
Student/faculty discussions of research problems in the design of reliable digital systems. Areas: faulttolerant systems, design for testability, production testing, and system reliability. Emphasis is on student presentations and Ph.D. thesis research. May be repeated for credit. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr

Units: 14

Repeatable for credit

Grading: Letter or Credit/No Credit
EE 387:
Algebraic Error Correcting Codes (CS 250)
Introduction to the theory of error correcting codes, emphasizing algebraic constructions, and diverse applications throughout computer science and engineering. Topics include basic bounds on error correcting codes; ReedSolomon and ReedMuller codes; listdecoding, listrecovery and locality. Applications may include communication, storage, complexity theory, pseudorandomness, cryptography, streaming algorithms, group testing, and compressed sensing. Prerequisites: Linear algebra, basic probability (at the level of, say, CS109, CME106 or EE178) and "mathematical maturity" (students will be asked to write proofs). Familiarity with finite fields will be helpful but not required.
Terms: Win

Units: 3

Grading: Letter or Credit/No Credit
EE 390:
Special Studies or Projects in Electrical Engineering
Independent work under the direction of a faculty member. Individual or team activities may involve lab experimentation, design of devices or systems, or directed reading. May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Satisfactory/No Credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
EmamiNaeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur Aydin, A. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Smith, J. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 391:
Special Studies and Reports in Electrical Engineering
Independent work under the direction of a faculty member; written report or written examination required. Letter grade given on the basis of the report; if not appropriate, student should enroll in 390. May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Letter (ABCD/NP)
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
EmamiNaeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fejer, M. (PI);
Flynn, M. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur Aydin, A. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 392B:
Industrial Internet of Things
The seminar will feature guest lectures from the industry to discuss the state of the affairs in the Industrial Internet of Things (IoT) with emphasis on existing and new Data Science, analytics, and Big Data applications. The class will address several verticals. One of them is electrical power industry, which is undergoing transition to renewables and distributed generation. Another one is aerospace industry including airlines and equipment vendors. Other verticals are oil and gas, data centers, and semiconductor manufacturing.
Terms: Spr

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 392I:
Seminar on Trends in Computing and Communications
Lectures series and invited talks on current trends in computing and communications, and ongoing initiatives for research and open innovation. This year's focus on evolving cloud computing architectures and their impact on the enterprise; big data trends and rise of the third platform; software as a service; wireless and cellular network architectures; mobility and mobile data proliferation; open mobile platforms (e.g. Android); multihomed mobile networking, associated data communication and mobile resource tradeoffs, and system implementation in smartphones and Android devices.
Terms: Spr

Units: 1

Grading: Satisfactory/No Credit
EE 392K:
SelfProgramming Networks
This is an advanced topics course on building autonomous networks using data and techniques from machine learning. It covers two major application areas: Cloud Computing Systems and Mobile Wireless Networks. The course introduces the architecture of SelfProgramming Networks for sensing, inferring, learning and control, consisting of (i) a "reflex layer" for inferring at line rate and at scale, and (ii) a "deliberate layer" for efficient resource scheduling and network control. Various sensing and inference algorithms for deriving insights and alerts from the sensed data will be discussed. Methods for synchronizing clocks across a large data center and using this to reconstruct the fine details of network performance (queuedepths, link utilizations and buffer and link compositions) in near realtime will be presented. Similarly, methods for inferring available bandwidth in dynamic mobile networks and using it to drive different application optimizations will be presented. Students will learn the use of neural networks and learning techniques (a) to accelerate inference and control algorithms, (b) for "workload fingerprinting", (c) for predicting wireless link capacities, and (d) for scheduling resources. Finally, the principles of creating an interactive database for detecting anomalies, raising alerts, and serving insights to the user will be discussed. The course involves a teambased project.
Terms: not given this year

Units: 3

Grading: Letter or Credit/No Credit
EE 400:
Thesis and Thesis Research
Limited to candidates for the degree of Engineer or Ph.D.May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 115

Repeatable for credit

Grading: Satisfactory/No Credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
EmamiNaeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fejer, M. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur Aydin, A. (PI);
Pauly, J. (PI);
Pauly, K. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 402A:
Topics in International Technology Management (EALC 402A, EASTASN 402A)
Theme for Autumn 2018 is "AI in Smart Physical Systems: Is Asia Ahead of the U.S.?" Distinguished guest speakers from industry present and discuss practical innovations from Asia related to the use of artificial intelligence in smart physical systems, e.g. smart buildings, autonomous vehicles, drone fleets, smart manufacturing, etc. See syllabus for specific requirements, which may differ from those of other seminars at Stanford.
Terms: Aut

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 402T:
Entrepreneurship in Asian High Tech Industries (EALC 402T, EASTASN 402T)
Distinctive patterns and challenges of entrepreneurship in Asia; update of business and technology issues in the creation and growth of startup companies in major Asian economies. Distinguished speakers from industry, government, and academia.
Terms: Spr

Units: 1

Repeatable for credit

Grading: Satisfactory/No Credit
EE 801:
TGR Project
May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 0

Repeatable for credit

Grading: TGR
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 802:
TGR Dissertation
May be repeated for credit.
Terms: Aut, Win, Spr, Sum

Units: 0

Repeatable for credit

Grading: TGR
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
FraserSmith, A. (PI);
GarciaMolina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
KhuriYakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur Aydin, A. (PI);
Pauly, J. (PI);
Pauly, K. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Xing, L. (PI);
Zebker, H. (PI)