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:DB-EngrAppSci, WAY-SMA
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. On-site 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.
Last offered: Winter 2017
| Units: 3
| UG Reqs: GER:DB-EngrAppSci
EE 17N:
Engineering the Micro and Nano Worlds: From Chips to Genes
Preference to freshmen. The first part is hands-on micro- and nano-fabrication including the Stanford Nanofabrication Facility (SNF) and the Stanford Nanocharacterization Laboratory (SNL) and field trips to local companies and other research centers to illustrate the many applications; these include semiconductor integrated circuits ('chips'), DNA microarrays, microfluidic bio-sensors and microelectromechanical systems (MEMS). The second part is to create, design, propose and execute a project. Most of the grade will be based on the project. By the end of the course you will, of course, be able to read critically a New York Times article on nanotechnology. More importantly you will have experienced the challenge (and fun) of designing, carrying out and presenting your own experimental project. As a result you will be better equipped to choose your major. This course can complement (and differs from) the seminars offered by Profs Philip Wong and Hari Manoharan in that it emphasizes laboratory work and an experimental student-designed project. Prerequisites: high-school physics.
Last offered: Spring 2016
| Units: 3
| UG Reqs: GER:DB-EngrAppSci
EE 21N:
What is Nanotechnology?
Nanotechnology is an often used word and it means many things to different people. Scientists and Engineers have some notion of what nanotechnology is, societal perception may be entirely different. In this course, we start with the classic paper by Richard Feynman ("There's Plenty of Room at the Bottom"), which laid down the challenge to the nanotechnologists. Then we discuss two classic books that offer a glimpse of what nanotechnology is: Engines of Creation: The Coming Era of Nanotechnology by Eric Drexler, and Prey by Michael Crichton. Drexler's thesis sparked the imagination of what nano machinery might do, whereas Crichton's popular novel channeled the public's attention to this subject by portraying a disastrous scenario of a technology gone astray. We will use the scientific knowledge to analyze the assumptions and predictions of these classic works. We will draw upon the latest research advances to illustrate the possibilities and impossibilities of nanotechnology.
Terms: Win
| Units: 3
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
EE 22N:
Medical Imaging Systems
Preference to freshmen. The technology of major imaging modalities used for disease diagnosis: x-ray, ultrasound, and magnetic resonance; their history, societal impact, and clinical applications. Field trips to a medical center and an imaging research lab. Term paper and presentation. Prerequisites: high school physics and calculus.
Last offered: Winter 2016
| Units: 3
| UG Reqs: GER:DB-EngrAppSci
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
EE 29N:
Electromagnetic Sensors for the Internet of Things
Have you ever wondered how your phone know what way is up? How the traffic light know your car is there? How you can monitor your health with a smart bracelet? If so, you want to learn about electromagnetic sensors. In this course we will the electromagnetic principles that allows us to sense things and communicate with things at a distance. You will learn the fundamentals of electromagnetic sensing and build practical sensors in the laboratory.
Last offered: Winter 2016
| Units: 3
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, one-dimensional wave equation, electromagnetic waves, transmission lines, and one-dimensional resonators. Pre-requisites: MATH 42 or MATH 51 or CME 100 or equivalent.
Terms: Win
| Units: 5
| UG Reqs: GER:DB-EngrAppSci
EE 46:
Engineering For Good: Save the World and Have Fun Doing It
Projects that provide immediate and positive impact on the world. Focus is on global health by learning from experts in this field. Students work on real-world projects with help from members of NGOs and social entrepreneurial companies as part of the hand-on learning experience. Prerequisite: ENGR 40 or EE 122A or CS 106B or consent of instructor.
Terms: Win
| Units: 3
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:DB-EngrAppSci
Terms: Aut
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
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). Pre-requisite: Physics 41. Pre- or co-requisite: Math 53 or CME 102.
Terms: Spr
| Units: 4
| UG Reqs: GER: DB-NatSci, GER:DB-EngrAppSci, WAY-SMA
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
EE 101A:
Circuits I
Introduction to circuit modeling and analysis. Topics include creating the models of typical components in electronic circuits and simplifying non-linear models for restricted ranges of operation (small signal model); and using network theory to solve linear and non-linear circuits under static and dynamic operations. Prerequisite: ENGR40 or ENGR40M is useful but not strictly required.
Terms: Win, Sum
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
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:DB-EngrAppSci, WAY-SMA
EE 102A:
Signal Processing and Linear Systems I
Concepts and tools for continuous- and discrete-time 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. Frequency-domain representations: Fourier series and Fourier transforms. Filtering and signal distortion. Time/frequency sampling and interpolation. Continuous-discrete-time signal conversion and quantization. Discrete-time signal processing. Prerequisite: MATH 53 or CME 102.
Terms: Win, Sum
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR
EE 102B:
Signal Processing and Linear Systems II
Continuation of EE 102A. Concepts and tools for continuous- and discrete-time 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:DB-EngrAppSci, WAY-AQR, WAY-FR
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 k-means algorithm. Matrices, left and right inverses, QR factorization. Least-squares and model fitting, regularization and cross-validation. Constrained and nonlinear least-squares. Applications include time-series 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, Spr
| Units: 3-5
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
Instructors: ;
Boyd, S. (PI);
Osgood, B. (PI);
Tse, D. (PI);
Angeris, G. (TA);
Chang, S. (TA);
Daniel, J. (TA);
Degleris, A. (TA);
Go, C. (TA);
Harvey, B. (TA);
Jani, T. (TA);
Jimenez, S. (TA);
Kamath, G. (TA);
Li, L. (TA);
Lin, J. (TA);
Nishimura, M. (TA);
Patel, N. (TA);
Pathak, R. (TA);
Prakash, L. (TA);
Sholar, J. (TA);
Spear, L. (TA)
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. In this initial offering, enrollment is limited to 50 students. 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: 3-5
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: Aut
| Units: 3
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:DB-EngrAppSci, WAY-AQR, WAY-SMA
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
EE 114:
Fundamentals of Analog Integrated Circuit Design (EE 214A)
Analysis and simulation of elementary transistor stages, current mirrors, supply- and temperature-independent 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 computer-aided design tools. Undergraduates must take EE 114 for 4 units. Prerequisite: 101B. GER:DB-EngrAppSci
Terms: Aut
| Units: 3-4
| UG Reqs: GER:DB-EngrAppSci
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) co-requisite: EE 65 or equivalent.
Terms: Spr
| Units: 3
| UG Reqs: GER:DB-EngrAppSci
EE 118:
Introduction to Mechatronics (ME 210)
Technologies involved in mechatronics (intelligent electro-mechanical systems), and techniques to apply this technology to mecatronic system design. Topics include: electronics (A/D, D/A converters, op-amps, filters, power devices); software program design, event-driven programming; hardware and DC stepper motors, solenoids, and robust sensing. Large, open-ended team project. Prerequisites: ENGR 40, CS 106, or equivalents.
Terms: Win
| Units: 4
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, neuro-MEMS and measurement systems, experimental design and statistical data analysis, information encoding and decoding, clinical diagnostic systems, and fully-implantable neural prosthetic systems design. Prerequisite: EE 101A and EE 102A.
Terms: Win
| Units: 3
| UG Reqs: WAY-SMA
EE 133:
Analog Communications Design Laboratory (EE 233)
Design, testing, and applications. Amplitude modulation (AM) using multiplier circuits. Frequency modulation (FM) based on discrete oscillator and integrated modulator circuits such as voltage-controlled oscillators (VCOs). Phased-lock loop (PLL) techniques, characterization of key parameters, and their applications. Practical aspects of circuit implementations. Labs involve building and characterization of AM and FM modulation/demodulation circuits and subsystems. Enrollment limited to 30 undergraduates and coterminal EE students. Prerequisite: EE101B. Undergraduate students enroll in EE133 and Graduate students enroll in EE233. Recommended: EE114/214A.
Terms: Win
| Units: 3-4
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: Spr
| Units: 4
| UG Reqs: GER:DB-EngrAppSci
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, Biot-Savart'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, wave-vector, 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 1D-3D problems: Electromagnetic resonators, waveguides periodic media, transmission lines. Formerly EE 141. Pre-requisites: Phys 43 or EE 42, CME 100, CME 102 (recommended)
Terms: Aut
| Units: 3
| UG Reqs: GER:DB-EngrAppSci, WAY-FR, WAY-SMA
EE 151:
Sustainable Energy Systems
Energy demand is expected to grow by 30% by 2025, while at the same time the European Union is demanding a carbon footprint at 1990 levels. We examine energy flow in the US and Europe, and deduce from it a strategy for sustainable growth. Potential solutions include distributed small scale networked energy generation, solar energy, wind and water, as well as nuclear energy. A systems perspective allows optimization. Fundamental concepts will be demonstrated in class through hands-on experiments.
Last offered: Winter 2016
| Units: 3
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.
Terms: Win
| Units: 3-4
| UG Reqs: WAY-SMA
EE 155:
Green Electronics (EE 255)
Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energy-conserving control systems have at their heart intelligent, high-power electronics. This course examines this technology and uses green-tech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steady-state analysis, control, motors and drives, photovol-taic systems, and design of magnetic components. The course involves a hands-on laboratory and a substantial final project. Formerly EE 152. Required: EE101B, EE102A, EE108. Recommended: ENGR40 or EE122A.
Terms: Aut
| Units: 4
EE 168:
Introduction to Digital Image Processing
Computer processing of digital 2-D and 3-D 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. Prerequisite: Matlab programming.
Terms: Win
| Units: 3-4
EE 169:
Introduction to Bioimaging
Bioimaging is important for both clinical medicine, and medical research. This course will provide a introduction to several of the major imaging modalities, using a signal processing perspective. The course will start with an introduction to multi-dimensional Fourier transforms, and image quality metrics. It will then study projection imaging systems (projection X-Ray), backprojection based systems (CT, PET, and SPECT), systems that use beam forming (ultrasound), and systems that use Fourier encoding (MRI). Prerequisites: EE102A, EE102B
Terms: Aut
| Units: 3
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: Aut, Spr
| Units: 4
| UG Reqs: GER:DB-EngrAppSci
EE 179:
Analog and Digital Communication Systems
This course covers the fundamental principles underlying the analysis, design and optimization of analog and digital communication systems. Design examples will be taken from the most prevalent communication systems today: cell phones, Wifi, radio and TV broadcasting, satellites, and computer networks. Analysis techniques based on Fourier transforms and energy/power spectral density will be developed. Mathematical models for random variables and random (noise) signals will be presented, which are used to characterize filtering and modulation of random noise. These techniques will then be used to design analog (AM and FM) and digital (PSK and FSK) communication systems and determine their performance over channels with noise and interference. Prerequisite: 102A.
Terms: Aut
| Units: 3
EE 180:
Digital Systems Architecture
The design of processor-based digital systems. Instruction sets, addressing modes, data types. Assembly language programming, low-level 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 processor-based embedded systems. Formerly EE 108B. Prerequisite: CS107 (required) and EE108 (recommended but not required).
Terms: Win
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
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: 1-15
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Bube, R. (PI);
Cioffi, J. (PI);
DaRosa, A. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Giovangrandi, L. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Goodman, J. (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);
Khuri-Yakub, B. (PI);
Kino, G. (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);
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);
Rivas-Davila, 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);
George, S. (GP);
Gillespie, J. (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: 1-15
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Bube, R. (PI);
Carpenter, D. (PI);
Cioffi, J. (PI);
DaRosa, A. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Giovangrandi, L. (PI);
Girod, B. (PI);
Glover, G. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Huang, K. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lauben, D. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McCluskey, E. (PI);
McKeown, N. (PI);
Meng, T. (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);
Paulraj, A. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Rivas-Davila, 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);
Tyler, G. (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);
Wooley, B. (PI);
Wootters, M. (PI);
Yamamoto, Y. (PI);
Zebker, H. (PI);
George, S. (GP);
Gillespie, J. (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
EE 191W:
Special Studies and Reports in Electrical Engineering (WIM)
WIM-version of EE 191. For EE students using special studiesn(e.g., honors project, independent research project) to satisfy thenwriting-in-major 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: 3-10
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);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Gray, R. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, 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);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Rajagopal, R. (PI);
Rivas-Davila, 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);
Wooley, B. (PI);
Wootters, M. (PI);
Yamamoto, Y. (PI);
Zebker, H. (PI);
George, S. (GP);
Gillespie, J. (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: 1-3
EE 203:
The Entrepreneurial Engineer
Seminar. For prospective entrepreneurs with an engineering background. Contributions made to the business world by engineering graduates. Speakers include Stanford and other engineering and M.B.A. graduates who have founded large and small companies in nearby communities. Contributions from EE faculty and other departments including Law, Business, and MS&E.May be repeated for credit.
Terms: Win
| Units: 1
| Repeatable
for credit
EE 204S:
Business Management for Electrical Engineers and Computer Scientists
For SCPD students including NDOs; see EE204 for description.
Last offered: Spring 2016
| Units: 3
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 case-based 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
EE 207:
Neuromorphics: Brains in Silicon (BIOE 313)
(Formerly EE 304) Neuromorphic systems run perceptual, cognitive and motor tasks in real-time on a network of highly interconnected nonlinear units. To maximize density and minimize energy, these units--like the brain's neurons--are heterogeneous and stochastic. The first half of the course covers learning algorithms that automatically synthesize network configurations to perform a desired computation on a given heterogeneous neural substrate. The second half of the course surveys system-on-a-chip architectures that efficiently realize highly interconnected networks and mixed analog-digital circuit designs that implement area and energy-efficient nonlinear units. Prerequisites: EE102A is required.
Terms: Spr
| Units: 3
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 back-end processing. Required for 410.
Terms: Aut
| Units: 3
EE 213:
Digital MOS Integrated Circuits
Looks a little more deeply at how digital circuits operate, what makes a gate digital, and how to "cheat" to improve performance or power. To aid this analysis we create a number of different models for MOS transistors and choose the simplest one that can explain our the circuit's operation, using both hand and computer analysis. We explore static, dynamic, pulse-mode, and current mode logic, and show how they are are used in SRAM design. Topics include sizing for min delay, noise and noise margins, power dissipation. The class uses memory design (SRAM) as a motivating example. DRAM and EEPROM design issues are also covered. Formerly EE 313. Prerequisites: EE 101B, EE 108. Recommended: EE 271.
Terms: Spr
| Units: 3
EE 214A:
Fundamentals of Analog Integrated Circuit Design (EE 114)
Analysis and simulation of elementary transistor stages, current mirrors, supply- and temperature-independent 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 computer-aided design tools. Undergraduates must take EE 114 for 4 units. Prerequisite: 101B. GER:DB-EngrAppSci
Terms: Aut
| Units: 3-4
EE 214B:
Advanced Analog 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
EE 216:
Principles and Models of Semiconductor Devices
Carrier generation, transport, recombination, and storage in semiconductors. Physical principles of operation of the p-n junction, heterojunction, metal semiconductor contact, bipolar junction transistor, MOS capacitor, MOS and junction field-effect transistors, and related optoelectronic devices such as CCDs, solar cells, LEDs, and detectors. First-order device models that reflect physical principles and are useful for integrated-circuit analysis and design. Prerequisite: 116 or equivalent.
Terms: Aut, Win, Sum
| Units: 3
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
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 time-dependent 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
EE 223:
Applied Quantum Mechanics II
Continuation of 222, including more advanced topics: quantum mechanics of crystalline materials, methods for one-dimensional 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
EE 225:
Biochips and Medical Imaging (MATSCI 382, SBIO 225)
The course covers state-of-the-art and emerging bio-sensors, bio-chips, imaging modalities, and nano-therapies 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 bio-chips (in-vitro diagnostics) and medical and molecular imaging (in-vivo imaging). In-depth discussion on cancer and cardiovascular diseases and the role of diagnostics and nano-therapies.
Terms: Win
| Units: 3
EE 228:
Basic Physics for Solid State Electronics
Topics: energy band theory of solids, energy bandgap engineering, classical kinetic theory, statistical mechanics, and equilibrium and non-equilibrium semiconductor statistics. Prerequisite: course in modern physics.
Last offered: Spring 2016
| Units: 3
EE 230:
Biophotonics: Light in Biology
This course will provide an introduction to the use of optics in biology, primarily focusing on microscopy from an engineering perspective (i.e., the focus of the course is more on technology than biology). Course material will be interspersed with labs to provide hands-on experience with common techniques in modern microscopy (e.g., brightfield, fluorescence, confocal and phase contrast microscopy). Background in college physics strongly recommended. Programming experience with Matlab required. Suggested prerequisites: EE 134 or EE 236A.
Last offered: Autumn 2016
| Units: 3
EE 233:
Analog Communications Design Laboratory (EE 133)
Design, testing, and applications. Amplitude modulation (AM) using multiplier circuits. Frequency modulation (FM) based on discrete oscillator and integrated modulator circuits such as voltage-controlled oscillators (VCOs). Phased-lock loop (PLL) techniques, characterization of key parameters, and their applications. Practical aspects of circuit implementations. Labs involve building and characterization of AM and FM modulation/demodulation circuits and subsystems. Enrollment limited to 30 undergraduates and coterminal EE students. Prerequisite: EE101B. Undergraduate students enroll in EE133 and Graduate students enroll in EE233. Recommended: EE114/214A.
Terms: Win
| Units: 3-4
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 242 or equivalent. Recommended: EE 236A.
Last offered: Autumn 2016
| Units: 3
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 hands-on laboratory experiments. Students will learn the core principles for designing, implementing and analyzing central experimental methods including polymerase chain reaction (PCR), electrophoresis, immunoassays, and high-throughput 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: Spr
| Units: 3
EE 236A:
Modern Optics
Geometrical optics, aberrations, optical instruments, radiometry. Ray matrices and Gaussian beams. Wave nature of light. Plane waves: at interfaces, in media with varying refractive index. Diffraction and Fourier optics. Interference, single-beam interferometers (Fabry-Perot), multiple-beam interferometers (Michelson, Mach-Zehnder). Polarization, Jones and Stokes calculi.nFormerly EE 268. Prerequisites: EE 142 or familiarity with electromagnetism and plane waves.
Terms: Aut
| Units: 3
EE 236AL:
Modern Optics - Laboratory
The Laboratory Course allows students to work hands-on with optical equipment to conduct five experiments that compliment the lecture course. Examples are Gaussian Beams and Resonators, Interferometers, and Diffraction.
Last offered: Autumn 2016
| Units: 1
EE 236B:
Guided Waves
Maxwell's equations, constitutive relations. Kramers-Kronig 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, III-V semiconductor, metallic. Waveguide devices: fibers, lasers, modulators, arrayed waveguide gratings. Scattering matrix description of passive optical devices, and constraints from energy conservation, time-reversal symmetry and reciprocity. Mode coupling, directional couplers, distributed-feedback structures. Resonators from scattering matrix and input-output perspective. Micro-ring resonators. Prerequisites: EE 236A and EE 242 or familiarity with differential form of Maxwell's equations.
Terms: Win
| Units: 3
EE 236C:
Lasers
Atomic systems, spontaneous emission, stimulated emission, amplification. Three- and four-level systems, rate equations, pumping schemes. Laser principles, conditions for steady-state 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
EE 242:
Electromagnetic Waves
Continuation of 142. Maxwell's equations. Plane waves in lossless and lossy media. Skin effect. Flow of electromagnetic power (Poynting's theorem). Reflection and refraction of waves at planar boundaries. Snell's law and total internal reflection. Reflection and refraction from lossy media. Guided waves. Parallel-plate and dielectric-slab waveguides. Hollow wave-guides, cavity resonators, microstrip waveguides, optical fibers. Interaction of fields with matter and particles. Antennas and radiation of electromagnetic energy. Prerequisites: EE 142 or PHYSICS 120.
Terms: Win
| Units: 3
EE 243:
Semiconductor Optoelectronic Devices
Semiconductor physics and optical processes in semiconductors. Operating principles and practical device features of semiconductor optoelectronic materials and heterostructures. Devices include: optical detectors (p-i-n, avalanche, and MSM); light emitting diodes; electroabsorptive modulators (Franz-Keldysh and QCSE), electrorefractive (directional couplers, Mach-Zehnder), switches (SEEDs); and lasers (waveguide and vertical cavity surface emitting). Prerequisites: semiconductor devices and solid state physics such as EE 216 or equivalent.
Terms: Win
| Units: 3
EE 247:
Introduction to Optical Fiber Communications
Fibers: single- and multi-mode, attenuation, modal dispersion, group-velocity dispersion, polarization-mode dispersion. Nonlinear effects in fibers: Raman, Brillouin, Kerr. Self- and cross-phase modulation, four-wave mixing. Sources: light-emitting diodes, laser diodes, transverse and longitudinal mode control, modulation, chirp, linewidth, intensity noise. Modulators: electro-optic, electro-absorption. Photodiodes: p-i-n, avalanche, responsivity, capacitance, transit time. Receivers: high-impedance, transimpedance, bandwidth, noise. Digital intensity modulation formats: non-return-to-zero, return-to-zero. Receiver performance: Q factor, bit-error ratio, sensitivity, quantum limit. Sensitivity degradations: extinction ratio, intensity noise, jitter, dispersion. Wavelength-division multiplexing. System architectures: local-area, access, metropolitan-area, long-haul. Prerequisites: EE 102A and EE 142.
Last offered: Autumn 2016
| Units: 3
EE 251:
High-Frequency Circuit Design Laboratory
Students will study the theory of operation of instruments such as the time-domain 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 upper-UHF range (e.g., up to about 500MHz), in a running series of laboratory exercises that conclude in a final project. Examples include impedance-matching and coupling structures, filters, narrowband and broadband amplifiers, mixers/modulators, and voltage-controlled oscillators. Prerequisite: EE 114 or EE 214A.
Terms: Aut
| Units: 3
EE 252:
Antennas
This course aims to cover the theory, simulation, and hands-on 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
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.
Terms: Win
| Units: 3-4
EE 254:
Advanced Topics in Power Electronics
In this course, we will study the practical issues related to the practical design of power electronic converters. We will also explore the trade-offs involved in selecting among the different circuits used to convert ac to dc, dc to ac and back to dc over a wide range of power levels suitable for different applications. In Advanced Topics in Power Electronic, as a multidisciplinary field, we will discuss power electronics circuits, extraction of transfer functions in Continuous and discontinuous conduction mode, voltage and current control of power converters, design of input/output filters to meet Electro Magnetic Interference specifications, layout of power electronics circuits and put this knowledge in a very practical context. Prerequisites: EE 153/253.
Last offered: Spring 2017
| Units: 3
EE 255:
Green Electronics (EE 155)
Many green technologies including hybrid cars, photovoltaic energy systems, efficient power supplies, and energy-conserving control systems have at their heart intelligent, high-power electronics. This course examines this technology and uses green-tech examples to teach the engineering principles of modeling, optimization, analysis, simulation, and design. Topics include power converter topologies, periodic steady-state analysis, control, motors and drives, photovol-taic systems, and design of magnetic components. The course involves a hands-on laboratory and a substantial final project. Formerly EE 152. Required: EE101B, EE102A, EE108. Recommended: ENGR40 or EE122A.
Terms: Aut
| Units: 4
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: Aut, Spr, Sum
| Units: 3
EE 262:
Two-Dimensional Imaging
Time and frequency representations, two-dimensional auto- and cross-correlation, 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 projection-slice 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.
Last offered: Winter 2015
| Units: 3
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: least-squares approximations of over-determined equations, and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm, and singular-value decomposition. Eigenvalues, left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input/multi-output systems, impulse and step matrices; convolution and transfer-matrix descriptions. Control, reachability, and state transfer; observability and least-squares 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
EE 264:
Digital Signal Processing
Digital signal processing (DSP) techniques and design of DSP applications. Topics include: discrete-time random signals; sampling and multi-rate systems; oversampling and quantization in A-to-D conversion; properties of LTI systems; quantization in fixed-point implementations of filters; digital filter design; discrete Fourier Transform and FFT; and spectrum analysis using the DFT. In the design part of the course, students develop basic DSP applications on an embedded processing platform. The 4-unit version of the course, which meets the EE design requirement, adds a final 4-week project and report. See ee264.stanford.edu for more information. Prerequisite: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)
Terms: Win, Sum
| Units: 3-4
EE 264W:
Digital Signal Processing (WIM)
Writing in the Major (WIM) version of the 4-unit EE 264 theory + lab/project course. This course also meets the EE design requirement. Digital signal processing (DSP) techniques and design of DSP applications. Topics include: discrete-time random signals; sampling and multi-rate systems; oversampling and quantization in A-to-D conversion; properties of LTI systems; quantization in fixed-point implementations of filters; digital filter design; discrete Fourier Transform and FFT; and spectrum analysis using the DFT. In the design part of the course, students complete basic labs and a 4 week final project and report. See ee264.stanford.edu for more information. Prerequisite: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)
Terms: Win
| Units: 5
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
EE 267:
Virtual Reality
OpenGL, real-time 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. Hands-on programming assignments. The 3-unit version requires a final programming assignment in which you create your own virtual environment. The 4-unit 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: 3-4
EE 267W:
Virtual Reality (WIM)
Writing in the Major (WIM) version of the 4-unit EE 267 theory + lab/project course. This course also meets the EE design requirement. Topics include: OpenGL, real-time 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. Hands-on programming assignments. The 5-unit WIM version requires everything the 4-unit version does, i.e. a final course project and written report in lieu of the final assignment. The 5-unit 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
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: Win
| Units: 3
EE 272:
Design Projects in VLSI Systems
An introduction to mixed signal design. Working in teams you will create a small mixed-signal 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 tape-out a chip. Useful for anyone who will build a chip in their Ph.D. Pre-requsiites: EE271 and experience in digital/analog circuit design.
Last offered: Spring 2012
| Units: 3-4
EE 273:
Digital Systems Engineering
Electrical issues in the design of high-performance digital systems, including signaling, timing, synchronization, noise, and power distribution. High-speed 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
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, Spr, Sum
| Units: 3
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 M-ary signals (PAM, QAM, PSK), receiver design and sufficient statistics, controlling the spectrum and the Nyquist criterion, bandpass communication and up/down conversion, design trade-offs: 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
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.
Last offered: Spring 2017
| Units: 3
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
EE 285:
Embedded Systems Workshop (CS 241)
Project-centric building hardware and software for embedded computing systems. Students work on an existing project of their own or join one of these projects. Syllabus topics will be determined by the needs of the enrolled students and projects. Examples of topics include: interrupts and concurrent programming, deterministic timing and synchronization, state-based programming models, filters, frequency response, and high-frequency signals, low power operation, system and PCB design, security, and networked communication. Prerequisite: CS107 (or equivalent).
Terms: Aut
| Units: 2
| Repeatable
3 times
(up to 9 units total)
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
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
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
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
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
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
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: Win, Spr, Sum
| Units: 1
EE 292A:
Electronic Design Automation (EDA) and Machine Learning Hardware
The class teaches cutting-edge 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 state-of-the-art FPGA board. Prerequisite: EE 108.
Terms: Spr
| Units: 3
EE 292B:
Micro and Nanoscale Biosensing for Molecular Diagnostics
The course covers state-of-the-art and emerging bio-sensors, biochips, microfluidics, which will be studied in the context of molecular diagnostics. Students will briefly learn the relevant biology, biochemistry, and molecular biology pertinent to molecular diag-nostics. Students will also become equipped with a thorough understanding of the interfaces between electronics, fluidics, and molecular biology. Topics will include microfluidics and mass transfer limits, electrode-electrolyte interfaces, electrochemical noise processes, biosensor system level characterization, determination of performance parameters such as throughput, detection limit, and cost, integration of sensor with microfluidics, and electronic readout circuitry architectures. Emphasis will be placed on in-depth quantitative design of biomolecular sensing platforms.
Last offered: Spring 2016
| Units: 3
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; atomic-layer 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 high-density plasmas for rapid gap filling is contrasted with alternative CVD dielectric deposition processes.
Terms: Win
| Units: 1
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
(up to 99 units total)
EE 292G:
NanoBioTechnology, Nanoscience and Sensing
Nanobiotechnology, which may be called a "Fundamental Technology of the 21st Century", is a new frontier for Biology with extremely important applications in medical diagnostics, therapeutics and drug discovery based on the development of new materials and sensors. The goal of this course is to provide an insight into the fundamentals of nanotechnology in biological and biomedical research by providing an overview of current topics in Nanoscience and Engineering and their modern day applications in biotechnology. This course will provide a bridge for students from a non-biology background at all levels to the world of Nanobiotechnology. Basic biological molecules and the importance of their detection as well as a thorough understanding of the interfaces between electronics, fluidics, and molecular biology are discussed. Focus is also provided on solid-state materials, Nanostructures and Nano devices and systems as related to biological applications especially detection and sensing, covering top-down MEMS fabrication and integration of sensors with microfluidics to bottom-up biochemistry, applications of Nanostructures and Nanobiotechnology in drug discovery, delivery, and controlled release andnNanobiotechnological applications in environment and food detection and mitigation.
Last offered: Winter 2016
| Units: 3
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 warm-up discussion/activity and then deliver a talk in his/her area of expertise. We will wrap up with small-group and full-class discussions of related challenges/opportunities and possible engineering-oriented solutions. Class members are asked to do background reading before each class, to submit a question before each lecture, and to do in-class brainstorming. May be repeated for credit.
Terms: Aut
| Units: 1
| Repeatable
for credit
EE 292I:
Insanely Great Products: How do they get built?
Great products emerge from a sometimes conflict-laden process of collaboration between different functions within companies. This Seminar seeks to demystify this process via case-studies 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). Pre-requisites: None
Terms: Spr
| Units: 1
EE 292L:
Nanomanufacturing
Fundamentals of nanomanufacturing technology and applications. Topics include recent developments in process technology, lithography and patterning. Technology for FinFET transistors, NAND flash and 3D chips. Manufacturing of LEDs, thin film and crystalline solar cells. Flip classroom model is used supplementing classroom lectures with short videos. Guest speakers include distinguished engineers, entrepreneurs and venture capitalists actively engaged in nanomanufacturing. Prerequisite: background in device physics and process technology. Recommended: EE116, EE216, EE212
Last offered: Spring 2016
| Units: 3
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 bi-weekly 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 in-between 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: 1-2
| Repeatable
2 times
(up to 4 units total)
EE 293A:
Solar Cells, Fuel Cells, and Batteries: Materials for the Energy Solution (ENERGY 293A, MATSCI 156)
Operating principles and applications of emerging technological solutions to the energy demands of the world. The scale of global energy usage and requirements for possible solutions. Basic physics and chemistry of solar cells, fuel cells, and batteries. Performance issues, including economics, from the ideal device to the installed system. The promise of materials research for providing next generation solutions. Undergraduates register in 156 for 4 units; graduates register in 256 for 3 units. Prerequisites: MATSCI 145 and 152 or equivalent coursework in thermodynamics and electronic properties.
Terms: Win, Sum
| Units: 3-4
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 19-21; PHYSICS 41, 43, 45
Terms: Aut
| Units: 3
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: 1-15
| Repeatable
for credit
Instructors: ;
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Bube, R. (PI);
Cioffi, J. (PI);
Cox, D. (PI);
DaRosa, A. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McCluskey, E. (PI);
McKeown, N. (PI);
Meng, T. (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);
Prabhakar, B. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Tyler, G. (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);
Wooley, B. (PI);
Wootters, M. (PI);
Yamamoto, Y. (PI);
Zebker, H. (PI);
George, S. (GP);
Gillespie, J. (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 catheter-deliverable 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, electrical-tissue interface, and sensing and actuating frontend designs. Prerequisites: EE 252 or equivalent.
Terms: Spr
| Units: 3
EE 308:
Advanced Circuit Techniques
Design of advanced analog circuits at the system level, including switching power converters, amplitude-stabilized and frequency-stabilized oscillators, voltage references and regulators, power amplifiers and buffers, sample-and-hold circuits, and application-specific op-amp compensation. Approaches for finding creative design solutions to problems with difficult specifications and hard requirements. Emphasis on feedback circuit techniques, design-oriented thinking, and hands-on 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
EE 309:
Semiconductor Memory Devices and Technology
The functionality and performance of ULSI systems are increasingly dependent upon the characteristics of the memory subsystem. This course introduces the student to various memory devices: SRAM, DRAM, NVRAM (non-volatile memory). This course will cover various aspects of semiconductor memories, including basic operation principles, device design considerations, device scaling, device fabrication, memory array addressing and readout circuits. Various cell structures (e.g. 1T-1C, 6T, 4T, 1T-1R, 0T-1R, 1S-1R, floating gate FLASH, SONOS, NROM), and memory organization (open bit-line, folded bit-line, NAND, NOR, cross-point etc.). This course will include a survey of new memory concepts (e.g. magnetic tunnel junction memory (MRAM, SST-RAM), ferroelectric memory (FRAM), phase change memory (PCM), metal oxide resistive switching memory (RRAM), nanoconductive bridge memory (CBRAM)). Offered Alternate years. Pre-requisite: EE 216. Preferred: EE 316.
Terms: Aut
| Units: 3
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
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 back-end (interconnect and contact) processing. What are future device structures and materials to maintain progress in integrated electronics? MOS front-end and back-end process integration. Prerequisites: EE 216 or equivalent. Recommended: EE 212.
Terms: Spr
| Units: 3
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: 3-4
EE 314A:
RF Integrated Circuit Design
Design of RF integrated circuits for communications systems, primarily in CMOS. Topics: the design of matching networks and low-noise amplifiers at RF, mixers, modulators, and demodulators; review of classical control concepts necessary for oscillator design including PLLs and PLL-based frequency synthesizers. Design of low phase noise oscillators. Design of high-efficiency (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
EE 314B:
Advanced RF Integrated Circuit Design
Analysis and design of modern communication circuits and systems with emphasize on design techniques for high-frequency (into mm-wave) ICs. Topics include MOS, bipolar, and BiCMOS high-frequency integrated circuits, including power amplifiers, extremely wideband amplifiers, advanced oscillators, phase-locked loops and frequency-translation circuits. Design techniques for mm-wave silicon ICs (on-chip low-loss transmissions lines, unilateralization techniques, in-tegrated antennas, harmonic generation, etc) will also be studied. Prerequisite: EE314A or equivalent course in RF or microwave.
Last offered: Spring 2015
| Units: 3
EE 315:
Analog-Digital 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 micro-electromechanical and biomedical applications. Nyquist and oversampling A/D and D/A converters. Prerequisite: EE 214B.
Terms: Aut
| Units: 3
EE 316:
Advanced VLSI Devices
In modern VLSI technologies, device electrical characteristics are sensitive to structural details and therefore to fabrication techniques. How are advanced VLSI devices designed and what future changes are likely? What are the implications for device electrical performance caused by fabrication techniques? Physical models for nanometer scale structures, control of electrical characteristics (threshold voltage, short channel effects, ballistic transport) in small structures, and alternative device structures for VLSI. Prerequisites: 216 or equivalent. Recommended: EE 212.
Terms: Win
| Units: 3
EE 320:
Nanoelectronics
This course covers the device physics and operation principles of nanoelectric devices, with a focus on devices for energy-efficient computation. Topics covered include devices based on new nanomaterials such as carbon nanotubes, semiconductor nanowires, and 2D layered materials such as graphene; non-FET based devices such as nanoelectromechanical (NEM) relay, single electron transistors (SET) and resonant tunneling diodes (RTD); as well as FET-based devices such as tunnel FET. Devices targeted for both logic and memory applications are covered. Prerequisites: Undergraduate device physics, EE222, EE216, EE316. Recommended courses: EE223, EE228, EE311.
Last offered: Spring 2017
| Units: 3
EE 323:
Energy in Electronics
EE 323 examines energy in modern nanoelectronics, from fundamentals to systems. Fundamental topics include energy storage and transfer via electrons and phonons, ballistic limits of current and heat, meso- to macroscale mobility and thermal conductivity. Applied topics include power in nanoscale devices (1D nanotubes and nanowires, 2D materials, 3D silicon CMOS, resistive memory and interconnects), circuit leakage, temperature measurements, thermoelectric energy conversion, and thermal challenges in densely integrated systems. Basic knowledge of semiconductors, transistors, and Matlab (or similar) are recommended.
Last offered: Autumn 2016
| Units: 3
EE 327:
Properties of Semiconductor Materials
Modern semiconductor devices and integrated circuits are based on unique energy band, carrier transport, and optical properties of semiconductor materials. How to choose these properties for operation of semiconductor devices. Emphasis is on quantum mechanical foundations of the properties of solids, energy bandgap engineering, semi-classical transport theory, semi-conductor statistics, carrier scattering, electro-magneto transport effects, high field ballistic transport, Boltzmann transport equation, quantum mechanical transitions, optical absorption, and radiative and non-radiative recombination that are the foundations of modern transistors and optoelectronic devices. Prerequisites: EE216 or equivalent.
Last offered: Spring 2017
| Units: 3
EE 328:
Physics of Advanced Semiconductor Devices
Principles governing the operation of modern semiconductor devices. Assumptions and approximations commonly made in analyzing devices. Emphasis is on the application of semiconductor physics to the development of advanced semiconductor devices such as heterojunctions, HJ-bipolar transistors, HJ-FETs, nanostructures, tunneling, single electron transistor and photonic devices. Use of SENTARUS, a 2-D Poisson solver, for simulation of ultra-small devices. Examples related to state-of-the-art devices and current device research. Prerequisite: 216. Recommended: 316.
Last offered: Spring 2016
| Units: 3
EE 329:
The Electronic Structure of Surfaces and Interfaces (PHOTON 329)
Physical concepts and phenomena for surface science techniques probing the electronic and chemical structure of surfaces, interfaces and nanomaterials. Microscopic and atomic models of microstructures; applications including semiconductor device technology, catalysis and energy. Physical processes of UV and X-ray photoemission spectroscopy, Auger electron spectroscopy, surface EXAFS, low energy electron diffraction, electron/photon stimulated ion desorption, scanning tunneling spectroscopy, ion scattering, energy loss spectroscopy and related imaging methods; and experimental aspects of these surface science techniques. Prerequisites: PHYSICS 70 and MATSCI 199/209, or consent of instructor.
Terms: Aut
| Units: 3
EE 331:
Biophotonics: Light in Medicine and Biology
Current topics and trends in the use of light in medicine and for advanced microscopy. Course begins with a review of relevant optical principles (basic physics required). Key topics include: light-tissue interactions; sensing and spectroscopy; contrast-enhanced imaging; super-resolution and label-free microscopy; medical applications of light for diagnostics, in-vivo imaging, and therapy; nanophotonics and array technologies. Open to non-majors; programming experience (Matlab and/or C) required.
Terms: Spr
| Units: 3
EE 332:
Laser Dynamics
Dynamic and transient effects in lasers including spiking, Q-switching, mode locking, frequency modulation, frequency and spatial mode competition, linear and nonlinear pulse propagation, pulse shaping. Formerly EE 232. Prerequisite: 236C.
Terms: Aut
| Units: 3
EE 334:
Micro and Nano Optical Device Design
Lecture and project course on design and analysis of optical devices with emphasis on opportunities and challenges created by scaling to the micrometer and nanometer ranges. The emphasis is on fundamentals, combined with some coverage of practical implementations. Prerequisite: EE 242 or equivalent
Last offered: Spring 2016
| Units: 3
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. Sub-wavelength phenomena and plasmonic excitations. Meta-materials. Prerequisite: Electromagnetic theory at the level of 242.
Terms: Aut
| Units: 3
EE 340:
Optical Micro- and Nano-Cavities
Optical micro- and nano-cavities 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 weak-coupling regime, Purcell factor, spontaneous emission control. Applications of optical cavities, including low-threshold lasers, optical modulators, quantum information processing devices, and bio-chemical sensors. Prerequisites: Advanced undergraduate or basic graduate level knowledge of electromagnetics, quantum.
Terms: Spr
| Units: 3
EE 346:
Introduction to Nonlinear Optics
Wave propagation in anisotropic, nonlinear, and time-varying media. Microscopic and macroscopic description of electric-dipole susceptibilities. Free and forced waves; phase matching; slowly varying envelope approximation; dispersion, diffraction, space-time analogy. Harmonic generation; frequency conversion; parametric amplification and oscillation; electro-optic light modulation. Raman and Brillouin scattering; nonlinear processes in optical fibers. Prerequisites: 242, 236C.
Terms: Win
| Units: 3
EE 347:
Optical Methods in Engineering Science
Design and understanding of modern optical systems. Topics: geometrical optics; aberration theory; systems layout; applications such as microscopes, telescopes, optical processors. Computer ray tracing program as a design tool. Prerequisite: 236A or equivalent.
Terms: Win
| Units: 3
EE 348:
Advanced Optical Fiber Communications
Optical amplifiers: gain, saturation, noise. Semiconductor amplifiers. Erbium-doped fiber amplifiers. System applications: preamplified receiver performance, amplifier chains. Raman amplifiers, lumped vs. distributed amplification. Group-velocity dispersion management: dispersion-compensating fibers, filters, gratings. Interaction of dispersion and nonlinearity, dispersion maps. Multichannel systems. Wavelength-division multiplexing components: filters, multiplexers. WDM systems, crosstalk. Time, subcarrier, code and polarization-division multiplexing. Comparison of modulation techniques: differential phase-shift keying, phase-shift keying, quadrature-amplitude modulation. Comparison of detection techniques: noncoherent, differentially coherent, coherent. Prerequisite: 247.
Terms: Aut
| Units: 3
EE 349:
Advanced Topics in Nano-Optics and Plasmonics
Electromagnetic phenomena at the nanoscale. Dipolar interactions between emitters and nanostructures, weak and strong coupling, surface plasmon polaritons and localized plasmons, electromagnetic field enhancements, and near-field coupling between metallic nanostructures. Numerical tools will be taught and used to simulate nano-optical phenomena. Prerequisite: EE 242 or equivalent.
Last offered: Spring 2017
| Units: 3
EE 355:
Imaging Radar and Applications (GEOPHYS 265)
Radar remote sensing, radar image characteristics, viewing geometry, range coding, synthetic aperture processing, correlation, range migration, range/Doppler algorithms, wave domain algorithms, polar algorithm, polarimetric processing, interferometric measurements. Applications: surfafe deformation, polarimetry and target discrimination, topographic mapping surface displacements, velocities of ice fields. Prerequisites: EE261. Recommended: EE254, EE278, EE279.
Terms: Win
| Units: 3
EE 356A:
Resonant Converters
Miniaturization of efficient power converters remain a challenge in power electronics whose goal is to improving energy use and reducing waste.nIn this course, we will study the design of Resonant converters which are capable of operating at higher frequencies than their 'hard-switch' counterparts. Resonant converter are found in high performance applications where high control bandwidth and high power density are required. We will also explore practical design issues and trade off in selecting converter topologies in high performance applications. Prerequisites: EE153/EE253.
Terms: Aut
| Units: 3
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.
| Units: 3
EE 359:
Wireless Communications
This course will cover advanced topics in wireless communications as well as current wireless system design. Topics include: an overview of current and future wireless systems; wireless channel models including path loss, shadowing, and statistical multipath channel models; fundamental capacity limits of wireless channels; digital modulation and its performance in fading and under intersymbol interference; techniques to combat fading including adaptive modulation and diversity; multiple antenna (MIMO) techniques to increase capacity and diversity, intersymbol interference including equalization, multicarrier modulation (OFDM), and spread spectrum; and multiuser system design, including multiple access techniques. Course is 3 units but can be taken for 4 units with an optional term project. Prerequisite: 279 or instructor consent.
Terms: Aut
| Units: 3-4
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. Least-squares, linear and quadratic programs, semidefinite programming, and geometric programming. Numerical algorithms for smooth and equality constrained problems; interior-point 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
Instructors: ;
Lall, S. (PI);
Pathak, R. (PI);
Angeris, G. (TA);
Choudhary, D. (TA);
Gu, A. (TA);
Jiang, Q. (TA);
Kim, J. (TA);
Mani, N. (TA);
Momeni, A. (TA);
Pathak, R. (TA);
Shah, K. (TA);
Song, R. (TA);
Tefagh, M. (TA)
EE 364B:
Convex Optimization II (CME 364B)
Continuation of 364A. Subgradient, cutting-plane, 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
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 high-performance computing. Similar trends are observed for modern displays pushing the boundaries of resolution, contrast, 3D capabilities, and immersive experiences through the co-design 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
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
EE 369A:
Medical Imaging Systems I
Imaging internal structures within the body using high-energy radiation studied from a systems viewpoint. Modalities covered: x-ray, computed tomography, and nuclear medicine. Analysis of existing and proposed systems in terms of resolution, frequency response, detection sensitivity, noise, and potential for improved diagnosis. Prerequisite: EE 261
Last offered: Winter 2017
| Units: 3
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
EE 369C:
Medical Image Reconstruction
Reconstruction problems from medical imaging, including magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET). Problems include reconstruction from non-uniform frequency domain data, automatic deblurring, phase unwrapping, reconstruction from incomplete data, and reconstruction from projections. Prerequisite: 369B.
Terms: Aut
| Units: 3
EE 371:
Advanced VLSI Circuit Design
Design of high-performance digital systems, the things that cause them to fail, and how to avoid these problems. Topics will focus on current issues including: wiring resistance and how to deal with it, power and Gnd noise and regulation, clock (or asynchronous) system design and how to minimize clocking overhead, high-speed I/O design, energy minimization including leakage control, and structuring your Verilog code to result in high-performance, low energy systems. Extensive use of modern CAD tools. Prerequisites: EE 213 and EE 271, or consent of instructor.
Last offered: Spring 2011
| Units: 3
EE 372:
Data Science for High Throughput Sequencing
Extraordinary advances in sequencing technology in the past decade have revolutionized biology and medicine. Many high-throughput sequencing based assays have been designed to make various biological measurements of interest. This course explores the various computational and data science problems that arises from processing, managing and performing predictive analytics on this high throughput sequencing data. Specific problems we will study include genome assembly, haplotype phasing, RNA-Seq assembly, RNA-Seq quantification, single cell RNA-seq analysis, multi-omics analysis,nand genome compression. We attack these problems through a combination of tools from information theory, combinatorial algorithms, machine learning and signal processing. Through this course, the student will also get familiar with various software tools developed for the analysis of real sequencing data. Prerequisites: Basic knowledge of probability at the level of EE 178. Some programming experience.
Terms: Win
| Units: 3
EE 373A:
Adaptive Signal Processing
Learning algorithms for adaptive digital filters. Self-optimization. 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 Hebbian-LMS 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: Win
| Units: 3
EE 376A:
Information Theory (STATS 376A)
The fundamental ideas of information theory. Entropy and intrinsic randomness. Data compression to the entropy limit. Huffman coding. Arithmetic coding. Channel capacity, the communication limit. Gaussian channels. Kolmogorov complexity. Asymptotic equipartition property. Information theory and Kelly gambling. Applications to communication and data compression. Prerequisite: EE178 or STATS 116, or equivalent.
Terms: Win
| Units: 3
EE 376B:
Network Information Theory (STATS 376B)
Network information theory deals with the fundamental limits on information flow in networks and the optimal coding schemes that achieve these limits. It aims to extend Shannon's point-to-point information theory and the Ford-Fulkerson max-flow min-cut theorem to networks with multiple sources and destinations. The course presents the basic results and tools in the field in a simple and unified manner. Topics covered include: multiple access channels, broadcast channels, interference channels, channels with state, distributed source coding, multiple description coding, network coding, relay channels, interactive communication, and noisy network coding. Prerequisites: EE376A.
Last offered: Autumn 2014
| Units: 3
EE 376C:
Universal Schemes in Information Theory
Universal schemes for lossless and lossy compression, channel coding and decoding, prediction, denoising, and filtering. Characterization of performance limitations in the stochastic settting: entropy rate, rate-distortion function, channel capacity, Bayes envelope for prediction, denoising, and filtering. Lempel-Ziv lossless compression, and Lempel-Ziv based schemes for lossy compression, channel coding, prediction, and filtering. Discrete universal denoising. Compression-based approach to denoising. The compound decision problem. Prerequisites: EE376A.
Last offered: Autumn 2016
| Units: 3
EE 376D:
Wireless Information Theory
Information theory forms the basis for the design of all modern day communication systems. The original theory was primarily point-to-point, studying how fast information can flow across an isolated noisy communication channel. Until recently, there has been only limited success in extending the theory to a network of interacting nodes. Progress has been made in the past decade driven by engineering interest in wireless networks. The course provides a unified overview of this recent progress made in information theory of wireless networks. Starting with an overview of the capacity of fading and multiple-antenna wireless channels, we aim to answer questions such as: What is the optimal way for users to cooperate and exchange information in a wireless network? How much benefit can optimal cooperation provide over traditional communication architectures? How can cooperation help to deal with interference between multiple wireless transmissions? Formerly EE361. Prerequisites: EE376A
Last offered: Spring 2017
| Units: 3
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, f-divergences. Penalized estimators and minimumndescription length. Online game playing, gambling, no-regret learning. Prerequisites: EE 376A (or equivalent) or STATS 300A.
Last offered: Winter 2016
| Units: 3
EE 378A:
Statistical Signal Processing
Basic concepts of statistical decision theory; Bayes decision theory; HMMs and their state estimation (Forward--backward), Kalman as special case, approximate state estimation (particle filtering, Extended Kalman Filter), unknown parameters; Inference under logarithmic loss, mutual information as a fundamental measure of statistical relevance, properties of mutual information: data processing, chain rules. Directed information. Prediction under logarithmic loss; Context Tree Weighting algorithm; Sequential decision making in general: prediction under general loss functions, causal estimation, estimation of directed information. Non-sequential inference via sequential probability assignments. Universal denoising; Denoising from a decision theoretic perspective: nonparametric function estimation, wavelet shrinkage, density estimation; Estimation of mutual information on large alphabets with applications such as boosting the Chow-Liu algorithm. Estimation of the total variation distance, estimate the fundamental limit is easier than to achieve the fundamental limit; Peetre¿s K-functional and bias analysis: bias correction using jackknife, bootstrap, and Taylor series; Nonparametric functional estimation. Prerequisites: Familiarity with probability theory and linear algebra at the undergraduate level.
Last offered: Spring 2017
| Units: 3
EE 378B:
Inference, Estimation, and Information Processing
Techniques and models for signal, data and information processing, with emphasis on incomplete data, non-ordered index sets and robust low-complexity methods. Linear models; regularization and shrinkage; dimensionality reduction; streaming algorithms; sketching; clustering, search in high dimension; low-rank 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
Last offered: Winter 2017
| Units: 3
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 matched-filter receivers; coherent, differentially coherent and noncoherent methods; error probabilities; comparison of modulation and detection methods. Intersymbol interference: single-carrier channel model; Nyquist requirement; whitened matched filter; maximum likelihood sequence detection; Viterbi algorithm; linear equalization; decision-feedback equalization. Multi-carrier modulation: orthogonal frequency-division multiplexing; capacity of parallel Gaussian channels; comparison of single- and multi-carrier techniques. Prerequisite: EE102B and EE278 (or equivalents). EE279 is helpful but not required.
Last offered: Winter 2017
| Units: 3
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
EE 382A:
Parallel Processors Beyond Multicore Processing
Formerly EE392Q. The current parallel computing research emphasizes multi-cores, but there are alterna-tive array processors with significant potential. This hands-on course focuses on SIMD (Single-Instruction, Multiple-Data) 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, Smith-Waterman), arbitrary-precision operations with fixed-point numbers, reductions, vector and matrix multiplication, image processing algo-rithms, asynchronous algorithms on SIMD ("SIMD Phase Programming Model"), Man-delbrot set, analysis of parallel performance.
Terms: Spr
| Units: 3
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: Aut, Spr
| Units: 3
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
EE 384B:
Multimedia Communication over the Internet
Applications and requirements. Traffic generation and characterization: voice encoding (G.711, G.729, G.723); image and video compression (JPEG, H.261, MPEG-2, H.263, H.264), TCP data traffic. Quality impairments and measures. Networking technologies: LAN technologies; home broadband services (ADSL, cable modems, PONs); and wireless LANs (802.11). Network protocols for multimedia applications: resource reservation (ST2+, RSVP); differentiated services (DiffServ); and real-time transport protocol (RTP, RTCP). Audio-video-data conferencing standards: Internet architecture (SDP, SAP, SIP); ITU recommendations (H.320, H.323 and T.120); and real-time streaming protocol (RTSP). Emphasis will be placed on advances in network infrastructure and new services (VoIP, IPTV, Peer-to-peer communications, etc.) Prerequisite: 284 or CS 144. Recommended: 384A.
Last offered: Spring 2017
| Units: 3
EE 384C:
Wireless Local and Wide Area Networks
Characteristics of wireless communication: multipath, noise, and interference. Communications techniques: spread-spectrum, CDMA, and OFDM. IEEE 802.11 physical layer specifications: FHSS, DSSS, IEEE 802.11b (CCK), and 802.11a/g (OFDM). IEEE 802.11 media access control protocols: carrier sense multiple access with collision avoidance (CSMA/CA), point coordination function (PCF), IEEE802.11e for differentiated services. IEEE 802.11 network architecture: ad hoc and infrastructure modes, access point functionality. Management functions: synchronization, power management and association. IEEE 802.11s Mesh Networks. IEEE 802.16 (WiMAX) network architecture and protocols: Physical Layer (OFDMA) and Media Access Control Layer. Current research papers in the open literature. Prerequisite: EE 284 or CS 244A.
Terms: Spr
| Units: 3
EE 384E:
Networked Wireless Systems
Design and implementation of wireless networks and mobile systems. The course will commence with a short retrospective of wireless communication and initially touch on some of the fundamental physical layer properties of various wireless communication technologies. The focus will then shift to design of media access control and routing layers for various wireless systems. The course will also examine adaptations necessary at transport and higher layers to cope with node mobility and error-prone nature of the wireless medium. Finally, it will conclude with a brief overview of other related issues including emerging wireless/mobile applications. Prerequisites: EE 284
Terms: Spr
| Units: 3
EE 384S:
Performance Engineering of Computer Systems & Networks
Modeling and control methodologies for high-performance 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 high-performance 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
EE 385A:
Robust and Testable Systems Seminar
Student/faculty discussions of research problems in the design of reliable digital systems. Areas: fault-tolerant 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: 1-4
| Repeatable
for credit
EE 386:
Robust System Design
Causes of system malfunctions; techniques for building robust systems that avoid or are resilient to such malfunctions through built-in error detection and correction, prediction, self-test, self-recovery, and self-repair; case studies and new research problems. Prerequisites: EE 108, EE180, and EE 282.
Last offered: Spring 2011
| Units: 3
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; Reed-Solomon and Reed-Muller codes; list-decoding, list-recovery 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
EE 388:
Modern Coding Theory
Tools for analysis and optimization of iterative coding systems. LDPC, turbo and, RA codes. Optimized ensembles, message passing algorithms, density evolution, and analytic techniques. Prerequisite: 376A.
Terms: Spr
| Units: 3
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: 1-15
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Bayati, M. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Bravman, J. (PI);
Bube, R. (PI);
Byer, R. (PI);
Cheriton, D. (PI);
Cioffi, J. (PI);
Cox, D. (PI);
DaRosa, A. (PI);
Dai, H. (PI);
Dally, B. (PI);
Dill, D. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Enge, P. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Giovangrandi, L. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Guibas, L. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Helms, C. (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);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lam, M. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
Linscott, I. (PI);
McCluskey, E. (PI);
McKeown, N. (PI);
Meng, T. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Napel, S. (PI);
Ng, A. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Paulraj, A. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pelc, N. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Popelka, G. (PI);
Prabhakar, B. (PI);
Pratt, V. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shen, Z. (PI);
Shenoy, K. (PI);
Smith, J. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Spielman, D. (PI);
Thompson, N. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Tyler, G. (PI);
Ullman, J. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wandell, B. (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);
de la Zerda, A. (PI);
George, S. (GP);
Gillespie, J. (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: 1-15
| Repeatable
for credit
Instructors: ;
Abel, J. (PI);
Arbabian, A. (PI);
Bambos, N. (PI);
Bayati, M. (PI);
Bent, S. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Bravman, J. (PI);
Brongersma, M. (PI);
Bube, R. (PI);
Byer, R. (PI);
Cheriton, D. (PI);
Cioffi, J. (PI);
Cox, D. (PI);
Cui, Y. (PI);
DaRosa, A. (PI);
Dally, B. (PI);
Dasher, R. (PI);
Dill, D. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Enge, P. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fejer, M. (PI);
Flynn, M. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, F. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Giovangrandi, L. (PI);
Girod, B. (PI);
Glover, G. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Guibas, L. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Hellman, M. (PI);
Helms, C. (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);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lam, M. (PI);
Lauben, D. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
Manoharan, H. (PI);
McCluskey, E. (PI);
McKeown, N. (PI);
Meng, T. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Napel, S. (PI);
Ng, A. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Palanker, D. (PI);
Paulraj, A. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pelc, N. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Pratt, V. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shen, Z. (PI);
Shenoy, K. (PI);
Smith, J. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Spielman, D. (PI);
Thompson, N. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Tyler, G. (PI);
Ullman, J. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wandell, B. (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);
Yang, D. (PI);
Zebker, H. (PI);
de la Zerda, A. (PI);
George, S. (GP);
Gillespie, J. (GP)
EE 392AA:
Multi-Dimensional Data Transmission
EE 392AA focuses on state-of-the-art data communication systems that use multiple dimensions (parallel antennas, wires, links), including the latest versions of 5G, Wi-Fi, G.MGfast wireline, DOCSIS 3.1, and other systems that stress fundamental transmission limits. Topics include system design, particularly physical-layer modulation/coding for analysis and optimization for specific channels. Included are all vectored designs (MIMO, massive MIMO, SIMO, MISO) and methods to design and adapt both transmitter and receiver to variable channels. This course is approved for satisfying the MSEE Depth Sequence on Communication and Networking. Prerequisites: EE 278, EE 279, EE 379 or instructor consent.
Terms: Spr
| Units: 3
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
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); multi-homed mobile networking, associated data communication and mobile resource trade-offs, and system implementation in smartphones and Android devices.
Terms: Spr
| Units: 1
EE 392K:
Self-Programming 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 Self-Programming 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 (queue-depths, link utilizations and buffer and link compositions) in near real-time 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 team-based project.
Terms: Aut, Win
| Units: 3
EE 392T:
Seminar in Chip Test and Debug
Seminars by industry professionals in digital IC manufacturing test and silicon debug. Topics include yield and binsplit modeling, defect types and detection, debug hardware, physical analysis, and design for test/debug circuits. Case studies of silicon failures. Prerequisite: basic digital IC design (271 or 371).
Last offered: Winter 2017
| Units: 1
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: 1-15
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Bravman, J. (PI);
Bube, R. (PI);
Byer, R. (PI);
Cheriton, D. (PI);
Cioffi, J. (PI);
Cox, D. (PI);
DaRosa, A. (PI);
Dai, H. (PI);
Dally, B. (PI);
Dill, D. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Enge, P. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fejer, M. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Glover, G. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Guibas, L. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Helms, C. (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);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lam, M. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McCluskey, E. (PI);
McConnell, M. (PI);
McKeown, N. (PI);
Meng, T. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Napel, S. (PI);
Ng, A. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Paulraj, A. (PI);
Pauly, J. (PI);
Pauly, K. (PI);
Pease, R. (PI);
Pelc, N. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Pratt, V. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shen, Z. (PI);
Shenoy, K. (PI);
Smith, J. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Spielman, D. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Tyler, G. (PI);
Ullman, J. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wandell, B. (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);
George, S. (GP);
Gillespie, J. (GP)
EE 402A:
Topics in International Technology Management (EASTASN 402A)
Theme for Autumn 2017 is "The Rise of Commercial Space Businesses in Asia." Distinguished guest speakers from industry, governments, and universities present and discuss businesses from Asia related to outer space, including telecommunications, debris removal, payload launch services, space medicine, etc. See syllabus for specific requirements, which may differ from those of other seminars at Stanford.
Terms: Aut
| Units: 1
| Repeatable
for credit
EE 402T:
Entrepreneurship in Asia (EALC 402T, EASTASN 402T)
Distinctive patterns and challenges of entrepreneurship in Asia; update of business and technology issues in the creation and growth of start-up companies in major Asian economies. Distinguished speakers from industry, government, and academia.
Terms: Spr
| Units: 1
| Repeatable
for credit
EE 414:
RF Transceiver Design Laboratory
Students design, build, and test GHz transceivers using microstrip construction techniques and discrete components. The design, construction, and experimental characterization of representative transceiver building blocks: low noise amplifiers (LNAs), diode ring mixers, PLL-based frequency synthesizers, voltage-controlled oscillators (VCOs), power amplifiers (PAs), and microstrip filters and patch antennas. The characteristics of passive microstrip components (including interconnect). Emphasis is on a quantitative reconciliation of theoretical predictions and extensive experimental measurements performed with spectrum and network analyzers, time-domain reflectometers (TDRs), noise figure meter and phase noise analyzers. Prerequisites: EE 314A and EE 251 (or EE 251).
Last offered: Winter 2015
| Units: 3
EE 469B:
RF Pulse Design for Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) and spectroscopy (MRS) based on the use of radio frequency pulses to manipulate magnetization. Analysis and design of major types of RF pulses in one and multiple dimensions, analysis and design of sequences of RF pulses for fast imaging, and use of RF pulses for the creation of image contrast in MRI. Prerequisite: 369B.
Last offered: Autumn 2016
| Units: 3
Terms: Aut, Win, Spr, Sum
| Units: 0
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bahai, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Bube, R. (PI);
Byer, R. (PI);
Cioffi, J. (PI);
Cox, D. (PI);
DaRosa, A. (PI);
Dally, B. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (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);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McCluskey, E. (PI);
McKeown, N. (PI);
Meng, T. (PI);
Miller, D. (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);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shenoy, K. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Tyler, G. (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);
Wooley, B. (PI);
Wootters, M. (PI);
Yamamoto, Y. (PI);
Zebker, H. (PI)
EE 802:
TGR Dissertation
May be repeated for credit.
Terms: Aut, Win, Spr, Sum
| Units: 0
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bahai, A. (PI);
Bambos, N. (PI);
Bent, S. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Bravman, J. (PI);
Bube, R. (PI);
Byer, R. (PI);
Cheriton, D. (PI);
Chichilnisky, E. (PI);
Cioffi, J. (PI);
Cox, D. (PI);
DaRosa, A. (PI);
Dally, B. (PI);
Dill, D. (PI);
Duchi, J. (PI);
Dutton, R. (PI);
El Gamal, A. (PI);
Enge, P. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Franklin, G. (PI);
Fraser-Smith, A. (PI);
Garcia-Molina, H. (PI);
Gibbons, J. (PI);
Gill, J. (PI);
Girod, B. (PI);
Glover, G. (PI);
Goldsmith, A. (PI);
Goodman, J. (PI);
Gray, R. (PI);
Guibas, L. (PI);
Hanrahan, P. (PI);
Harris, J. (PI);
Harris, S. (PI);
Helms, C. (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);
Khuri-Yakub, B. (PI);
Kino, G. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lam, M. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McCluskey, E. (PI);
McConnell, M. (PI);
McKeown, N. (PI);
McNab, J. (PI);
Meng, T. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Napel, S. (PI);
Ng, A. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Paulraj, A. (PI);
Pauly, J. (PI);
Pauly, K. (PI);
Pease, R. (PI);
Pelc, N. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Pratt, V. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Shen, Z. (PI);
Shenoy, K. (PI);
Smith, J. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Spielman, D. (PI);
Thrun, S. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Tyler, G. (PI);
Ullman, J. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wandell, B. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wooley, B. (PI);
Wootters, M. (PI);
Xing, L. (PI);
Yamamoto, Y. (PI);
Zebker, H. (PI);
George, S. (GP);
Gillespie, J. (GP);
Kittiwanich, M. (GP)
