BAW 6/03_1

Undergraduate Education in

Electrical Engineering at Stanford

Bruce Wooley

June 2003

BAW 6/03_2

Changing Education in EE

• Two factors are driving a major restructuring of undergraduate education in EE

– Expansion of the field, with a shift in emphasis toward systems

– Changing student backgrounds

• EE at Stanford

– Undergraduate education is ultimately driven by results of graduate research, here and elsewhere

– Begin with a broad overview of the Department and its strategic vision

BAW 6/03_3

Stanford EE Department

• 54 tenure-line faculty members (44.5 billets)– 30 Professors, 14 Associate Professors, 10 Assistant Professors

– 20 joint faculty (with CS, AP, MgS&E, MSE, Geophysics, Statistics)

• 8 research faculty members (3 joint faculty)

• 97 declared undergraduate students – UG admissions through University

• 890 graduate students (443 PhD students)– 15% of Stanford’s graduate students

– Graduate admissions through Department

• 63 PhD, 228 MS and 39 BS degrees in 2001-02

BAW 6/03_4

Research in EE

CSL: Computer architecture / VLSI, core system software, networking, information management, graphics, CAD

ISL: Communications/coding, signal processing, control, information theory, optimization, image processing, medical imaging

ICL: Semiconductor devices and technology, technology CAD, integrated transducers/MEMS, mixed-signal and RF IC design, digital signal processing, neuroengineering

SSPL: Optoelectronic devices and systems, microoptics, scanning microscopy, acoustic sensors and transducers, ultrafast optics, nanotechnology, quantum electronics

STAR: Wireless and optical communications, ionospheric and magnetospheric physics, remote sensing, planetary exploration, signal processing

BAW 6/03_5

What is Electrical Engineering?

• Department is attempting to define what it means to be an EE in the 21st century

– EE includes almost anything “electrical engineers” decide to do– Much of what we do is increasingly defined by applications

• At its core, EE is the discipline that provides the technology for sensing, processing, storing and communicating information

• The future of EE is being impacted by:

– growth in the importance of information technology

– increasing breadth of interactions with the physical sciences

– cross-discipline convergence and the importance of interdisciplinary activity

– increasing levels of complexity

– increasingly rapid change

BAW 6/03_6

A Changing Environment

• Changing student backgrounds

– Engineering art is less “visible” than for previous generations

– Incoming students more likely to have “taken apart” the software that runs a system than the physical implementation

• Increasing complexity of systems and tools

– Changes the kind of research that is both interesting and possible

– Can “raise the bar” for what qualifies as “good” research

– Increasing emphasis on finding new applications of technology

• Compression of time between theoretical concepts and commercial realization

– What is “long term”?

– Many challenging problems are not only intellectually interesting, but also result in useful artifacts

BAW 6/03_7

Emerging Research Themes

• Exploiting progress in hardware and information technologies to collect more data about the world

• Extracting meaning from large amounts of data

• Controlling large distributed systems

• Broadening the interface to the physical sciences beyond solid-state electronics to include photonics and biology

• Extending strength in semiconductor circuits and technology upward to support systems-on-a-chip, downward to understand nanoscale devices and laterally to encompass inexpensive, large-scale electronics

BAW 6/03_8

“Recent” EE Faculty Appointments

– Balaji Prabhakar (systems & control)

– Andrea Goldsmith (wireless communications)

– Dawson Engler (software systems)

– Nick Bambos (network architectures & performance)

– Olav Solgaard (applications of microelectonrics technology)

– Ben Van Roy (dynamic programming & control)

– Bernd Girod (digital imaging & video)

– Krishna Shenoy (neuroengineering)– Shanhui Fan (photonic crystals)– John Pauly (medical imaging)– Yoshio Nishi (micro-fabrication technology)– Christos Kozyrakis (computer & systems architecture)– Jelena Vuckovic (photonic crystal structures)– Joe Kahn (photonic systems)

BAW 6/03_9

Diffractive Optical MEMS – O. Solgaard

• MEMS technology enables diffractive optical elements that can be dynamically reconfigured on s timescales

• Diffractive optical MEMS are used in a multitude of device architectures and applications

hmax

h Optional lens to bring the far field closer

Outgoing light

DMDarray

outputcoupler

Phased arrays

for scanning

and free-space

laser comm.

Adaptive optics

mirror for wavefront

control in laser

communications,

ophthalmology, and

astronomy

Diffractive optical filter

for synthesis of optical

spectra in correlation

spectroscopy

Gires-Tournois

interferometer for

filtering, dispersion

compensation, and

coding in WDM optical

fiber systems

BAW 6/03_10

Microinstruments for RNA-i Experiments – O. Solgaard

• Double-stranded RNA (ds-RNA) is a powerful tool for genetic studies

• ds-RNA inhibits the expression of the corresponding gene through a process know as RNA interference (RNA-i)

• We are building microinstruments for studies of development in Drosophila embryos based on RNA-i

– Microinjectors for precise injection in specific locations with low damage– Integrated sensors for improved speed, reliability, and calibration of injections– Microfluidic systems for embryo handling, positioning, diagnostics, and sorting

Detail of microinjector

Drosophila embryo

Injector array for parallel injection. The Pyrex substrate has channels to bring ds-RNA to the microinjectors.

20 m

Injection into drosophila embryo. The flow rate is 10 pl/s for a total injected volume of 300 pl in 30 seconds.

BAW 6/03_11

f = 0.361 c/a

f = 0.360 c/a

wa

w

Theory of Micro and Nano-Scale Photonics – S. Fan

Displacement Sensor

PMD Compensator Photonic Crystal Waveguide

Propagation in Photonic Crystals

BAW 6/03_12

Visual Motor

Spinal cord injury

Prosthetic Arm

Neural signals to move real arm

Shenoy GroupControl signals to move prosthetic arm

120 spikes/s

Cue ReachPlan

1 second

H E

Batista, Buneo, Snyder, Andersen (1999) Science 285.

120 spikes/s

Cue ReachPlan

1 second

H EH E

Batista, Buneo, Snyder, Andersen (1999) Science 285.

Estimate desired arm movement

(algorithms, circuits and systems)

Neural prosthetic experiments with behaving monkeys

Neural Control of Prosthetic Devices – K. Shenoy

BAW 6/03_13

Optical Switch Core

625 160Gb/s Linecards

Optical links

External 160Gb/sConnections

Motivating Example: 100Tb/s Internet Router

Professors Mark Horowitz, Nick McKeown, David Miller, Olav Solgaard

1. Novel architectures with optical switch and no scheduler.2. 160Gb/s Packet buffers using hybrid SRAM/DRAM.3. Fast Internet address lookup (one packet every 2ns).4. Low-cost, low-power parallel optical serial links.

5. Direct-attach of optics onto silicon.6. Low-power integrated drivers for bumped optical transmitters.7. Integrated optical modulators.8. Novel MEMs switches.9. Drive circuitry for MEMs switches.

Research Problems

Optics in Internet Routers – N. McKeown

BAW 6/03_14

Polymorphic Computing Architectures – C. Kozyrakis

• Goal: next-generation computing substrate– Performance and power/energy of ASIPs– Programmability and flexibility of general-purpose CPUs

• Technical approach– Modular design based on simple processing cores

• Simple to design, scalable, no long wires

– Support for multiple programming models• Thread-level, data-level, and instruction-level parallelism

– Configurable on-chip memories• Can use as caches, local memories, specialized buffers, etc

– Allow software to create the optimal processor configuration for each application

• Faculty: Horowitz, Olukotun, Kozyrakis

BAW 6/03_15

Possible Future Areas of Emphasis

• Embedded systems and signal processing

• Semiconductor devices and circuits

• Sensing, including biosensing, and actuation

• Biology / EE (e.g. biophotonics)

• Distributed asynchronous control

• Radio, radar and optical remote sensing

• Experimental wireless systems

• Data mining and large scale optimization

• Information storage systems

• Internet-scale systems

BAW 6/03_16

Teaching Electrical Engineering

• Traditional curriculum follows a “sequence” structure

– Results in “delayed gratification”

– Fails to address the need for broad competency required by the rapid expansion of the field

• Need for courses that introduce the “ideas and methods” of a subject

– Response to two trends: an increasing knowledge base and the move to higher levels of abstraction

• Undergraduate curriculum

– Beginning a major restructuring of the undergraduate EE curriculum

BAW 6/03_17

Changing the Undergraduate Curriculum

• Driven by the information revolution and changing student backgrounds

• Students don’t build radios anymore

– Most haven’t built anything physical– But they have a much better software background

• More comfortable in the virtual world

– Early courses need to provide physical intuition – Used to an environment with abundant information

• Little tolerance for delayed gratification

• Some unique constraints– Undergraduates admitted to the University– Large number of required units

• 68 in EE and engineering, 45 in math & science, 48 general education requirements

BAW 6/03_18

Current Undergraduate EE Core

Intro toElectron

Intro Ckts101

Sig & Sys 102

Electr 1111

Electr 2112

Dig Lab121

Anal Lab122

EM141

Sig Proc 103

Elec Ckts113

BAW 6/03_19

EE Undergraduate Core

• Traditional core is too large and too linear

• Too long to get to the fun stuff

• Need to:– Motivate students to “sample” different areas– Emphasize fundamental principles that cut across areas– Include motivating examples for all material in the core– Take advantage of the students’ familiarity with a “virtual”

environment– Arouse interest in and curiosity about “hardware”– Broaden students’ appreciation of system issues– Familiarize students with different levels of system

abstraction

BAW 6/03_20

Goals of the New Undergrad Curriculum

• Alter focus of initial classes to emphasize applications– Make the classes more interesting

• Decrease the longest chain in the core by making the requirements more parallel– Enable more options in class selection

• Include lab components in the core classes– Provide immediate utility of material, leverage comfort with

virtual world (simulation) and grow coupling to physical world

• Include digital systems content in the core

BAW 6/03_21

New Undergraduate EE Core

Intro toElectron

Sig & Sys1

Sig & Sys 2

Electron1

Electron2

Dig Sys1

Dig Sys2

Circuits Lab

EngrPhysics

BAW 6/03_22

Specialty Areas in EE

Current specialty areas:

• Computer Hardware

• Computer Software

• Controls

• Electronics

• Fields and Waves

• Signal Processing and Communications

New specialty areas:

• Digital Systems

– Hardware

– Software Systems

• Signals, Systems and Control

– Control

– Signal Processing / Commun

• Electronics

– Analog and RF

– Digital Electronics

• E & M

– Field and Waves

– Solid State and Photonics

BAW 6/03_23

What’s Next?

• Begin to focus on the lower division curriculum– Retain rigor while making EE more appealing for today’s, and

tomorrow’s, incoming students

• Reconsider how and when math and science are taught– Need to provide more motivation– Are the traditional sequences relevant to modern electrical

engineering?– Can math and science be taught as needed throughout the

four year program, depending on the area pf specialization?