EE 11SC:
Dream It, Build It!
The world is filled with electronic devices! There seem to be more and more all the time. Wouldn't it be cool to hack and build stuff? Bend electronics to your will? Cloud connect your own stuff? Dream It, Build It is a great place to start. Designed for folks with no experience, it will take you from zero to capable in short order. We will show you some of the worst kept secrets of how things are built and help you build stuff of your own. We'll start out with some basics about how to build things, how to measure things, how to hook stuff together and end up being able to make cloudconnected gizmos. [This is a SOPHOMORE COLLEGE course. Visit soco.stanford.edu for full details.]
Terms: Sum

Units: 2

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 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 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, Sum

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 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 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 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 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);
Corbett, D. (GP)
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);
Corbett, D. (GP)
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);
Corbett, D. (GP)
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 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 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 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 237:
Solar Energy Conversion
This course will be an introduction to solar photovoltaics. Basics of solar energy conversion in photovoltaic devices. Economics of solar energy. Solar cell device physics: electrical and optical. Different generations of photovoltaic technology: crystalline silicon, thin film, multijunction solar cells. Perovskite and silicon tandem cells. Advanced energy conversion concepts like photon upconversion, quantum dot solar cells. Solar system issues including module assembly, inverters, and microinverters. Guest speakers include distinguished engineers, entrepreneurs and venture capitalists actively engaged in solar industry. No prior photovoltaics knowledge is required. Recommended: EE116, EE216 or equivalent.
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 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 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 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

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 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 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 292D:
Machine Learning on Embedded Systems
This is a projectbased class where students will learn how to build modern connected embedded systems that utilize machine learning. The class briefly covers how to create embedded systems to cloud services and dives into details of how to do edge and cloudbased machine learning on timeseries and image data.nIn the final project students are expected to produce a working system that improves the state of machine learning on the edge or solves a useful task by combining many different connected components. Prerequisites: CS 107(required), CS 229 (recommended), CS 230 (recommended).
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
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 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 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);
Pilanci, M. (PI);
Plummer, J. (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);
Corbett, D. (GP)
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 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 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 317:
Special Topics on Wide Bandgap Materials and Devices
Widebandgap (WBG) semiconductors present a pathway to push the limits of efficiency in optoelectronics and electronics enabling significant energy savings, offering new and compact architecture, and more functionality. We will first study the examples set by GaN and SiC in lighting, radiofrequency and power applications, then use it to explore new materials like Ga2O3, AlN and diamond to understand their potential to drive the future semiconductor industry. The term papers will include a short project that may require simulation to conduct device design and analysis. Prerequisites: EE 216 or EE 218
Terms: Spr

Units: 3

Grading: Letter (ABCD/NP)
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 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, Sum

Units: 3

Grading: Letter or Credit/No Credit
Instructors: ;
Boyd, S. (PI);
Diamond, S. (PI);
Agrawal, A. (TA);
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);
Tefagh, M. (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 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 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 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 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 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);
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);
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);
Corbett, D. (GP)
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);
Corbett, D. (GP)
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 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);
Sadigh, D. (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);
Corbett, D. (GP)
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);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
RivasDavila, J. (PI);
Rosenblum, M. (PI);
Sadigh, D. (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);
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);
Xing, L. (PI);
Zebker, H. (PI);
Corbett, D. (GP)