EE 21N:
Making at the nanometer scale: A journey into microchips
Have you ever wondered what is inside your phone and your computer? What physical events happen in between the time you press the 'search' button and the information shows up on the screen? In this course, we start with the classic paper by Richard Feynman, "There's Plenty of Room at the Bottom," which laid down a challenge to the nanotechnologists. Today's microchips are nanotechnology in action. Transistors are nanometer scale. We will introduce students to the tools of nanotechnologists and the basic elements of nanoscale science and engineering such as nanotubes, nanowires, nanoparticles, and self-assembly. We will visit nanotechnology laboratories to consolidate our learning, go into the Stanford Nanofabrication Facility (SNF), and do a four-week project on nanofabrication. Hands-on laboratory work will be introduced (e.g., lithography, seeing things at the nanoscale using electron microscopes). We will learn how to build transistors from scratch and test them.
Terms: Win
| Units: 3
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
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: Win
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
EE 64:
Mechanical Prototyping for Electrical Engineers
This course will give non-mechanical engineers experience designing mechanical assemblies specifically for manufacture with readily accessible tools such as 3D printers and laser cutters. It will also teach students to debug their own mechanical designs, and interface them with other components (such as store bought parts). By the end of the quarter students will feel comfortable independently designing and manufacturing simple assemblies to solve issues in their projects, careers and daily lives. The course will meet in Lab64 (Room 134) on the first floor of Packard. Class website: ee64.stanford.edu
Terms: Win
| Units: 3
EE 84N:
From the Internet for People to the Internet of Things
Driven by the ubiquity of the Internet and advances in various technological fields, all aspects of the physical world in which we live are undergoing a major transformation. Underlying this transformation is a concept known as the Internet of Things (IoT) which envisions that every physical object in the world could be connected to the Internet. This concept is at the root of such developments as the fourth industrial revolution, precision agriculture, smart cities, intelligent transportation, home and building automation, precision medicine, etc. In this seminar, we trace back the origins of the IoT concept in terms of both the vision and pioneering work, identify the building blocks of an IoT system, and explore enabling technologies pertaining to the devices that get attached to things (possibly comprising sensors, actuators, and embedded systems) and the communications capabilities (RFID, Bluetooth, wireless sensor networks, Wi-Fi, Low Power WANs, cellular networks, vehicular communications). Students will apply the acquired knowledge to the design of IoT systems meeting specific objectives in various application domains.
Terms: Win
| Units: 3
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: MATH 20 (or equivalent) is required, and ENGR 40M is strongly recommended.
Terms: Win, Sum
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-SMA
EE 102A:
Signals and 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. Prerequisites: MATH 53 or CME 102. EE 102A may be taken concurrently with either course, provided students have proficiency in complex numbers.
Terms: Win
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR
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: 5
| UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA
Instructors: ;
Kapetanovic, Z. (PI);
Mitra, S. (PI);
Goel, A. (GP);
Iyer, N. (TA);
Manuelito, T. (TA);
Ragins, M. (TA);
Ravipati, S. (TA);
Rosenberg, R. (TA);
Salcedo, W. (TA);
Saldana, A. (TA);
Sokk, C. (TA)
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 133:
Analog Communications Design Laboratory (EE 233)
Design, testing, and applications of Radio Frequency (RF) electronics: Amplitude Modulation (AM), Frequency Modulation (FM) and concepts of Software Define Radio (SDR) systems. Practical aspects of circuit implementations are developed; labs involve building and characterization of subsystems as well as integration of a complete radio system and a final project. Total enrollment limited to 25 students, undergraduate and graduate levels. Prerequisite: EE101B. Undergraduate students enroll in EE133 for 4 units and Graduate students enroll in EE233 for 3 units. Recommended: EE114/214A.
Terms: Win
| Units: 3-4
EE 134:
Introduction to Photonics
Optics and photonics underpin the technologies that define our daily life, from communications and sensing to displays and imaging. This course provides an introduction to the principles that govern the generation, manipulation, and detection of light and will give students hands-on lab experience applying these principles to analyze and design working optical systems. The concepts we will cover form the basis for many systems in biology, optoelectronics, and telecommunications and build a foundation for further learning in photonics and optoelectronics. Connecting theory to observation and application is a major theme for the course. Prerequisite: EE 102A and one of the following: EE 42, Physics 43, or Physics 63.
Terms: Win
| Units: 4
| UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA
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: Win
| 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: one of CS107 or CS 107E (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);
Cioffi, J. (PI);
Clark, S. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Giovangrandi, L. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Paulraj, A. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (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);
Rutherford, E. (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);
Cioffi, J. (PI);
Clark, S. (PI);
Congreve, D. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Moslehi, M. (PI);
Murmann, B. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Pauly, J. (PI);
Pease, R. (PI);
Pianetta, P. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI);
Rutherford, E. (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 studies (e.g., honors project, independent research project) to satisfy the writing-in-major requirement. A written report that has gone through revision with an adviser is required. An adviser from the Technical Communication Program 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);
Clark, S. (PI);
Congreve, D. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (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);
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);
Rivas-Davila, J. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, 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);
Wootters, M. (PI);
Zebker, H. (PI);
Rutherford, E. (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 214B:
Advanced Integrated Circuit Design
Analysis and design of analog and digital integrated circuits in advanced CMOS technology. Emphasis on compact modeling of performance limiting aspects and intuitive approaches to design. Analytical treatment of noise; analog circuit sizing using the transconductance to current ratio; analysis and design of feedback circuits. Delay analysis of digital logic gates; decoder design using logical effort. CMOS image sensors are used as a motivating application example. Prerequisites: EE114/214A.
Terms: Win
| 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 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 225, 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 227:
Robot Perception: Hardware, Algorithm, and Application (CS 227A)
Robot Perception is the cornerstone of modern robotics, enabling machines to interpret, understand, and respond to an array of sensory information they encounter. In the course, students will study the basic principles of typical sensor hardware on a robotics system (e.g., vision, tactile, and acoustic sensors), the algorithms that process the raw sensory data, and make actionable decisions from that information. Over the course of the semester, students will incrementally build their own vision-based robotics system in simulation via a series of homework coding assignments. Students enrolling 4 units will be required to submit an additional final written report. Prerequisites: This course requires programming experience in python as well as basic knowledge of linear algebra. Most of the required mathematical concepts will be reviewed, but it will be assumed that students have strong programming skills. All the homework requires extensive programming. Previous knowledge of robotics, machine learning or computer vision would be helpful but is not absolutely required.
Terms: Win
| Units: 3-4
EE 233:
Analog Communications Design Laboratory (EE 133)
Design, testing, and applications of Radio Frequency (RF) electronics: Amplitude Modulation (AM), Frequency Modulation (FM) and concepts of Software Define Radio (SDR) systems. Practical aspects of circuit implementations are developed; labs involve building and characterization of subsystems as well as integration of a complete radio system and a final project. Total enrollment limited to 25 students, undergraduate and graduate levels. Prerequisite: EE101B. Undergraduate students enroll in EE133 for 4 units and Graduate students enroll in EE233 for 3 units. Recommended: EE114/214A.
Terms: Win
| Units: 3-4
EE 235A:
Analytical Methods in Biotechnology I
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: Win
| Units: 3
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 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: Win
| Units: 3
EE 261:
The Fourier Transform and Its Applications
The Fourier transform as a tool for solving physical problems. Fourier series, the Fourier transform of continuous and discrete signals and its properties. The Dirac delta, distributions, and generalized transforms. Convolutions and correlations and applications; probability distributions, sampling theory, filters, and analysis of linear systems. The discrete Fourier transform and the FFT algorithm. Multidimensional Fourier transform and use in imaging. Further applications to optics, crystallography. Emphasis is on relating the theoretical principles to solving practical engineering and science problems. Prerequisites: Math through ODEs, basic linear algebra, Comfort with sums and discrete signals, Fourier series at the level of 102A
Terms: Win, Sum
| Units: 3
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; spectrum analysis using the DFT; parametric signal modeling and adaptive filtering. The course also covers applications of DSP in areas such as speech, audio and communication systems. The optional lab section (Section 02) provides a hands-on opportunity to explore the application of DSP theory to practical real-time applications in an embedded processing platform. See ee264.stanford.edu for more information. Register in Section 02 to take the lab. Undergraduate students taking the lab should register for 4 units to meet the EE design requirement. The optional lab section is not available to remote SCPD students. Prerequisites: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)
Terms: Win
| Units: 3-4
EE 264W:
Digital Signal Processing (WIM)
Writing in the Major (WIM) version of the 4-unit EE 264 theory + lab course. 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; spectrum analysis using the DFT; parametric signal modeling and adaptive filtering. The course also covers applications of DSP in areas such as speech, audio and communication systems. The lab component provides a hands-on opportunity to explore the application of DSP theory to practical real-time applications in an embedded processing platform. See ee264.stanford.edu for more information. Prerequisites: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)
Terms: Win
| Units: 5
EE 272:
Design Projects in VLSI Systems I
This course will introduce you to mixed signal design and the electronic design automation (EDA) tools used for it. Working in teams, you will create a chip with a digital deep neural network (DNN) accelerator and a small analog block using a modern design flow and EDA tools. The project involves writing a synthesizable C++ and a Verilog model of your chip, creating a testing/debug strategy for your chip, wrapping custom layout to fit into a standard 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-requisites: EE271 and experience in digital/analog circuit design.
Terms: Win
| Units: 3-4
EE 276:
Information Theory
(Formerly EE 376A.) Information theory was invented as a mathematical theory for communication but has subsequently found a broad range of applications. We study how to measure, represent, and communicate information effectively: from the foundational concepts of entropy and mutual information to the fundamental role they play in data representation, communication, inference, practical compression and error correction. As time allows, we cover relations and applications to other areas such as probability, statistics, learning and genomics. Prerequisite: a first undergraduate course in probability.
Terms: Win
| Units: 3
EE 285:
Embedded Systems Workshop (CS 241)
Project-centric building hardware and software for embedded computing systems. This year the course projects are on a large interactive light sculpture to be installed in Packard. Syllabus topics will be determined by the needs of the enrolled students and projects. Examples of topics include: interrupts and concurrent programming, mechanical control, state-based programming models, signaling and frequency response, mechanical design, power budgets, software, firmware, and PCB design. Interested students can help lead community workshops to begin building the installation. Prerequisites: one of CS107, EE101A, EE108, ME80.
Terms: Win
| Units: 3
| 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: Aut, Win, Spr, Sum
| Units: 1
EE 290H:
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 290G and instructor consent.
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. This course is open to graduate and professional students only, or with instructor consent.
Terms: Aut, Win, Spr
| Units: 1
| Repeatable
for credit
(up to 99 units total)
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: Win
| Units: 1
| Repeatable
for credit
EE 292J:
Designing for Authenticity
The Internet is at an inflection point. As mis/disinformation abounds and AI and synthetic media explode, the world's digital knowledge faces unprecedented threats. At the same time, a new generation of web technologies known as "Web3" offer new opportunities to protect the security and integrity of data. Our class jumps into this high-stakes moment and equips students with a new framework to understand and deploy methods to restore trust in digital content whether it's news and information, legally admissible evidence, or tamper-proof archives. Open to students of all experience levels, this class will provide an introduction to how advances in cryptography and the decentralized web can allow users to establish the provenance and veracity of data as it moves online. Students will create end-to-end technical prototypes and emerge with a new understanding that authenticity isn't a guaranteed part of information systems. You have to design for authenticity.
Terms: Win
| Units: 1
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 293B:
Fundamentals of Energy Processes (ENERGY 201B)
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: Win
| 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: ;
Achour, S. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI);
Rutherford, E. (GP)
EE 309B:
Emerging Non-Volatile Memory Devices and Circuit Design
The functionality and performance of ULSI systems are increasingly dependent upon the characteristics of the memory subsystem. This course starts off where EE 309A leaves, and introduces students to various emerging non-volatile memory devices: metal oxide resistive switching memory (RRAM), nanoconductive bridge memory (CBRAM), phase change memory (PCM), magnetic tunnel junction memory, spin-transfer-torque random access memory (MRAM, STT-RAM), ferroelectric memory (FRAM) and ferroelectric transistor (FeFET). For each of these memories, the course will cover basic operation principles, device design considerations, device scaling, device fabrication, memory array architecture, and addressing and readout circuits. The course will also introduce students to recent in-memory computing research using these memory technologies. Pre-requisite: EE 216. Preferred: EE 316, EE 309A.
Terms: Win
| 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 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 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 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 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: Win
| Units: 3-4
EE 364A:
Convex Optimization I (CME 364A)
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: ;
Ayazifar, B. (PI);
Boyd, S. (PI);
Ogut, G. (PI);
Bell, L. (TA);
Hofgard, J. (TA);
Holt, G. (TA);
Johansson, K. (TA);
Parshakova, T. (TA);
Tse, D. (TA);
Yang, A. (TA)
EE 364M:
Mathematics of Convexity
This course covers the elegant mathematical underpinnings of convex optimization, with a focus on those analytic techniques central to the successes of the field. Topics include, but are not limited to, convex sets and functions, separation theorems, duality, set-valued analysis, and the mathematical insights central to the development of modern optimization methods. Pre- or co-requisite: EE364A, and mathematical analysis at the level of MATH171.
Terms: Win
| Units: 1
EE 367:
Computational Imaging (CS 448I)
Digital photography and basic image processing, convolutional neural networks for image processing, denoising, deconvolution, single pixel imaging, inverse problems in imaging, proximal gradient methods, introduction to wave optics, time-of-flight imaging, end-to-end optimization of optics and imaging processing. Emphasis is on applied image processing and solving inverse problems using classic algorithms, formal optimization, and modern artificial intelligence techniques. Students learn to apply material by implementing and investigating image processing algorithms in Python. Term project. Recommended: EE261, EE263, EE278.
Terms: Win
| Units: 3
EE 369A:
Medical Imaging Systems I (BMP 269A)
Imaging internal structures within the body using high-energy radiation and ultrasound, studied from a systems viewpoint. Modalities covered: x-ray, computed tomography, nuclear medicine, and ultrasound. Review of linear signals and systems, Fourier transforms, random variables, and noise. Analysis of existing and proposed systems in terms of resolution, frequency response, detection sensitivity, noise, and potential for improved diagnosis. This course covers Fourier transform basics and serves as an alternative prerequisite to EE 261 for EE 369B. Prerequisite: EE 102A (undergraduate-level signals and systems) or similar.
Terms: Win
| Units: 3
EE 370:
Reinforcement Learning: Behaviors and Applications (MS&E 237B)
This course treats reinforcement learning, which addresses the design of agents to operate in environments where actions induce delayed consequences. Concepts generalize those arising in bandit learning, which is covered in EE277/MS&E 237A. The course covers principled and scalable approaches to realizing a range of intelligent learning behaviors. Topics include planning, credit assignment, and learning of models, value functions, and policies. Motivating examples will be drawn from generative artificial intelligence, web services, control, and finance. Prerequisites: EE277.
Terms: Win
| Units: 3
EE 379A:
Data Transmission Design
Data Transmission Design is the first of a two-quarter sequence (leading to EE379B) in MSEE communications depth sequence. Intended students are those interested in research or design of data transmission systems' lower layers. The course includes methods for transmission designs with and without coding and includes basic examples as well as their relationship to modern current/next-generation wireless and wireline transmission systems. The course also develops and uses information measures as generalizations of signal processing and minimum-mean-square-error estimation, developing design intution. Basic phase-locking and synchronization methods also appear. EE379B progresses to multidimensional modulation methods and their use in modern and next-generation multiuser MIMO networks, along with network-design strategies. Prerequisites: EE102B and EE278 (or equivalents). EE279 is helpful but not required.
Terms: Win
| 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: Win, Sum
| Units: 1
| Repeatable
for credit
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: Win
| 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);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Choi, J. (PI);
Cioffi, J. (PI);
Congreve, D. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Shenoy, K. (PI);
Smith, J. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Trippel, C. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI);
Rutherford, E. (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: ;
Achour, S. (PI);
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Choi, J. (PI);
Chowdhury, S. (PI);
Cioffi, J. (PI);
Congreve, D. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fejer, M. (PI);
Finn, C. (PI);
Flynn, M. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Sadigh, D. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Trippel, C. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI);
Rutherford, E. (GP)
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);
Chowdhury, S. (PI);
Cioffi, J. (PI);
Congreve, D. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Emami-Naeini, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fejer, M. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishi, Y. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Pauly, J. (PI);
Pauly, K. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Sadigh, D. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Trippel, C. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI);
Rutherford, E. (GP)
EE 801:
TGR Project
May be repeated for credit.
Terms: Aut, Win, Spr, Sum
| Units: 0
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Boyd, S. (PI);
Cioffi, J. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levis, P. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Pauly, J. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Sadigh, D. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Zebker, H. (PI)
EE 802:
TGR Dissertation
May be repeated for credit.
Terms: Aut, Win, Spr, Sum
| Units: 0
| Repeatable
for credit
Instructors: ;
Arbabian, A. (PI);
Bambos, N. (PI);
Boahen, K. (PI);
Boneh, D. (PI);
Bowden, A. (PI);
Boyd, S. (PI);
Chowdhury, S. (PI);
Cioffi, J. (PI);
Congreve, D. (PI);
Dally, B. (PI);
Duchi, J. (PI);
El Gamal, A. (PI);
Engler, D. (PI);
Fan, J. (PI);
Fan, S. (PI);
Fraser-Smith, A. (PI);
Gibbons, J. (PI);
Girod, B. (PI);
Hanrahan, P. (PI);
Hennessy, J. (PI);
Hesselink, L. (PI);
Horowitz, M. (PI);
Howe, R. (PI);
Inan, U. (PI);
Kahn, J. (PI);
Kapetanovic, Z. (PI);
Katti, S. (PI);
Kazovsky, L. (PI);
Khuri-Yakub, B. (PI);
Kovacs, G. (PI);
Kozyrakis, C. (PI);
Lall, S. (PI);
Lee, T. (PI);
Levin, C. (PI);
Levis, P. (PI);
Levoy, M. (PI);
McKeown, N. (PI);
Miller, D. (PI);
Mitchell, J. (PI);
Mitra, S. (PI);
Montanari, A. (PI);
Murmann, B. (PI);
Nishimura, D. (PI);
Olukotun, O. (PI);
Osgood, B. (PI);
Ozgur, A. (PI);
Pauly, J. (PI);
Pauly, K. (PI);
Pianetta, P. (PI);
Pilanci, M. (PI);
Plummer, J. (PI);
Poon, A. (PI);
Pop, E. (PI);
Prabhakar, B. (PI);
Raina, P. (PI);
Rajagopal, R. (PI);
Rivas-Davila, J. (PI);
Rosenblum, M. (PI);
Sadigh, D. (PI);
Saraswat, K. (PI);
Schroeder, D. (PI);
Senesky, D. (PI);
Soh, H. (PI);
Solgaard, O. (PI);
Song, S. (PI);
Tobagi, F. (PI);
Tse, D. (PI);
Van Roy, B. (PI);
Vuckovic, J. (PI);
Wang, S. (PI);
Weissman, T. (PI);
Wetzstein, G. (PI);
Widom, J. (PI);
Widrow, B. (PI);
Wong, H. (PI);
Wong, S. (PI);
Wootters, M. (PI);
Xing, L. (PI);
Zebker, H. (PI);
Rutherford, E. (GP)
