Undergraduate Education in Electrical Engineering at Stanford Bruce Wooley June 2003

1. Undergraduate Education in Electrical Engineering at Stanford Bruce Wooley June 2003

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

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

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

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

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

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

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)

9. output coupler Outgoing light DMD array Dh Optional lens to bring the far field closer hmax Diffractive Optical MEMS – O. Solgaard • MEMS technology enables diffractive optical elements that can be dynamically reconfigured on ms timescales • Diffractive optical MEMS are used in a multitude of device architectures and applications Phased arrays for scanning and free-space laser comm. Gires-Tournois interferometer for filtering, dispersion compensation, and coding in WDM optical fiber systems Adaptive optics mirror for wavefront control in laser communications, ophthalmology, and astronomy Diffractive optical filter for synthesis of optical spectra in correlation spectroscopy

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 Drosophila embryo 20 mm Injection into drosophila embryo. The flow rate is 10 pl/s for a total injected volume of 300 pl in 30 seconds. Detail of microinjector Injector array for parallel injection. The Pyrex substrate has channels to bring ds-RNA to the microinjectors.

11. Theory of Micro and Nano-Scale Photonics – S. Fan Displacement Sensor Propagation in Photonic Crystals f = 0.361 c/a f = 0.360 c/a PMD Compensator Photonic Crystal Waveguide

12. Neural Control of Prosthetic Devices – K. Shenoy Neural signals to move real arm Visual Motor Neural prosthetic experiments with behaving monkeys Estimate desired arm movement (algorithms, circuits and systems) Spinal cord injury Prosthetic Arm Control signals to move prosthetic arm Shenoy Group

13. Optics in Internet Routers – N. McKeown Professors Mark Horowitz, Nick McKeown, David Miller, Olav Solgaard Motivating Example: 100Tb/s Internet Router External 160Gb/s Connections Optical links Optical Switch Core 625 160Gb/s Linecards Research Problems • Novel architectures with optical switch and no scheduler. • 160Gb/s Packet buffers using hybrid SRAM/DRAM. • Fast Internet address lookup (one packet every 2ns). • 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.

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

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

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

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

18. Intro Ckts101 Sig & Sys 102 Sig Proc 103 Intro toElectron EM141 Electr 1111 Anal Lab122 Dig Lab121 Electr 2112 Elec Ckts113 Current Undergraduate EE Core

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

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

21. Sig & Sys1 Sig & Sys 2 Intro toElectron Circuits Lab EngrPhysics Electron1 Dig Sys1 Electron2 Dig Sys2 New Undergraduate EE Core

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

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?