EE Student Information

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EE Student Information, Spring Quarter through Academic Year 2020-2021: FAQs and Updated EE Course List.

Updates will be posted on this page, as well as emailed to the EE student mail list.

Please see Stanford University Health Alerts for course and travel updates.

As always, use your best judgement and consider your own and others' well-being at all times.

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image of prof Gordon Wetzstein and EE PhD candidate David Lindell
September 2020

Professor Gordon Wetzstein and EE PhD candidate David Lindell, have created a system that reconstructs shapes obscured by 1-inch-thick foam. Their tests are detailed in, "Three-dimensional imaging through scattering media based on confocal diffuse tomography", published in Nature Communications.

Gordon Wetzstein reports, "A lot of imaging techniques make images look a little bit better, a little bit less noisy, but this is really something where we make the invisible visible. This is really pushing the frontier of what may be possible with any kind of sensing system. It's like superhuman vision."

"We were interested in being able to image through scattering media without these assumptions and to collect all the photons that have been scattered to reconstruct the image," said David Lindell, EE PhD candidate and lead author of the paper. "This makes our system especially useful for large-scale applications, where there would be very few ballistic photons."

In order to make their algorithm amenable to the complexities of scattering, the researchers had to closely co-design their hardware and software, although the hardware components they used are only slightly more advanced than what is currently found in autonomous cars. Depending on the brightness of the hidden objects, scanning in their tests took anywhere from one minute to one hour, but the algorithm reconstructed the obscured scene in real-time and could be run on a laptop.

"You couldn't see through the foam with your own eyes, and even just looking at the photon measurements from the detector, you really don't see anything," said David. "But, with just a handful of photons, the reconstruction algorithm can expose these objects – and you can see not only what they look like, but where they are in 3D space."

Excerpted from Stanford News, "Stanford researchers devise way to see through clouds and fog", September 2020.


Related News

image of REU 2020 cohort
August 2020

Congratulations to the 26 undergraduate students who participated in Electrical Engineering's Research Experience for Undergraduates (REU) program, 2020. Students worked remotely to participate in their selected research projects. Faculty advisors and graduate student mentors met with and guided the program participants during research team meetings and one on one. The undergraduate researchers also attended weekly seminars featuring faculty, industry experts, and a graduate student panel to explore advanced degrees and research.

 
Thursday will be the student’s final presentations, demonstrating their findings. The community is invited to attend. 2020’s research projects are grouped into three main areas: circuits and physical systems, signals and information systems, and materials and devices. 
 
The project and researchers are listed below in order of presentation. 
Please email reu@ee.stanford.edu if you have questions, or plan to attend the event (password is required). 
 

Research Experience for Undergraduates (REU) program participants 2020

[Photo credit: Marisa Cheng]

 

CIRCUITS AND PHYSICAL SYSTEMS
1. Understanding and Measuring Troubleshooting Ability in Regards to Physical Circuits (ATINDRA JHA)
2. MOCHA: A Modular and Open-source Control and Hardware Library for Power Electronics (BRIAN KAETHER)
3. Modular FPGA and Programmable SoC Environment for ASIC Verification and Evaluation (JOHN KUSTIN)
4. Communicating Olfaction Using Frugal Device Design (ERIK LUNA)
5. Creating a Cost Function for Optimizing Loop Fusion in Clockwork (ISABELA DAVID RODRIGUES)
6. Running Accelerated Halide Programs End-to-End on an SoC (CHARLES TSAO)

SIGNALS AND INFORMATION SYSTEMS
7. Complex multiple feedback filter feasibility (BURCU ALICI)
8. Generative Adversarial Networks for Vehicle Models (EVA BATELAAN)
9. Producing digital puppetry (RACHEL CAREY)
10. Enabling selective neuron stimulation for brain machine interfaces (ISAAC CHERUIYOT)
11. Optimization of LiCoRICE: A Realtime Computational Platform for Systems Neuroscience (HELEN GORDAN)
12. Human Inspired Music Compression Through Transcription (ZACHARY HOFFMAN)
13. Visualizing the Effects of Polarity on Persistent Scatterers and Land Cover (PARKER KILLION)
14. Neural Network Confidence Intervals with Unbiased Risk Estimators (KAO KITICHOTKUL)
15. Julia on Embedded Systems (ALBERT LANDA)
16. Developing user interfaces for reinforcement learning tasks (NIKESH MISHRA)
17. Performance of Monostatic and Bistatic Radar Imaging Modalities with Varying Target Geometries (ANNIE NGUYEN)
18. AI-Assisted Wearable Multimodal Lung Monitoring System for Remote and Early Stage Diagnosis (ADRIAN SALDANA)
19. Learning Effective Image Reconstruction through Patch-wise Singular Value Decomposition (BRUCE XU)
20. Quasistatic Simulation for Data-Driven Clothing: from T-Shirts to Capes (KANGRUI XUE)
21. ML Fairness for ML API Joint Optimization (EVA ZHANG)
22. Nanopore FASTQ File Compression (YIFAN ZHU)

MATERIALS AND DEVICES
23. A Detection System for Continuous, Multiplexed Biomarker Monitoring (HAGOP CHINCHINIAN)
24. Motorized Stage Configurations for Optimal Straining of Flexible Electronics (NOOR FAKIH)
25. Using Python to Manipulate and Analyze Atomistic Simulations (SIDRA NADEEM)
26. Towards high specific power transition metal dichalcogenide (TMD) solar cells (FREDERICK NITTA)

image of prof. Gordon Wetzstein
August 2020

Professor Gordon Wetzstein and team use AI to revolutionize real-time holography.

"The big challenge has been that we don't have algorithms that are good enough to model all the physical aspects of how light propagates in a complex optical system such as AR eyeglasses," reports Gordon. "The algorithms we have at the moment are limited in two ways. They're computationally inefficient, so it takes too long to constantly update the images. And in practice, the images don't look that good."


Gordon says the new approach makes big advances on both real-time image generation and image quality. In heads-up comparisons, he says, the algorithms developed by their "Holonet" neural network generated clearer and more accurate 3-D images, on the spot, than the traditional holographic software.

That has big practical applications for virtual and augmented reality, well beyond the obvious arenas of gaming and virtual meetings. Real-time holography has tremendous potential for education, training, and remote work. An aircraft mechanic, for example, could learn by exploring the inside of a jet engine thousands of miles away, or a cardiac surgeon could practice a particularly challenging procedure.

In addition to professor Gordon Wetzstein, the system was created by Yifan Peng, a postdoctoral fellow in computer science; Suyeon Choi, an EE PhD candidate; Nitish Padmanaban, EE PhD '20; and Jonghyun Kim, a senior research scientist at Nvidia Corp.



Excerpted from: "Using AI to Revolutionize Real-Time Holography", August 17, 2020

image of Lei Gu, PhD
July 2020

Congratulations to postdoctoral research fellow Lei Gu, PhD '19. Lei received the IEEE Power Electronics Society (PELS) PhD Thesis Talk Award. His talk, "Design Considerations for Radio Frequency Power Converters" can be viewed online at IEEE-PELS.org.

Dr. Lei Gu is a researcher in professor Juan Rivas-Davila's SUPER Lab.

The IEEE PELS Digital Media Committee invites video submissions for the IEEE PELS Prize Ph.D. Thesis Talk. The goal of this competition is to showcase Ph.D. projects to the entire power electronics community - both in academia and industry. Five IEEE PELS P3 Talks are awarded each year. (source: ieee-pels.org/images/files/pdf/P3_Talks_Write_Up_4-27.pdf

Read more about the P3 award

 

Please join us in congratulating Lei on his award!

 

Image credit: Courtesy Bechtel International Center
July 2020

Congratulations to EE MS candidate Nicolo Zulaybar! He is a recipient of the David L. Boren Fellowship.

As a Boren Fellow, he will study Mandarin at the Inter-University Program for Chinese Studies at Tsinghua University in Beijing. Through the fellowship, he intends to further improve his language skills by auditing Chinese lectures and getting involved with student organizations.

"It's an honor and privilege to receive this Boren Fellowship," Zulaybar said. "In this time of global challenges, it feels all the more urgent that people get involved with government to solve the problems facing their communities. I appreciate how Boren both supports my placement in federal service and prepares me for my role with cultural skills I can use to problem-solve with America's international partners. It complements my technical education in this way."

Zulaybar is from Los Angeles. He graduated from Stanford in 2018 with a bachelor's degree in chemistry. As an undergraduate, he was a research associate in Assistant Professor of Chemistry Yan Xia's Polymer Chemistry Lab, as well as a member of the Alpha Chi Sigma professional fraternity.

Nicolo is one of five Stanford students who are the recipients of the 2020 Boren Awards. Two are graduate students, and will receive David L. Boren Fellowships and three are undergraduates who will receive David L. Boren Scholarships.

Congratulations to Nicolo and his Boren Awards colleagues!

 

Excerpted from "Five Stanford students receive 2020 Boren Awards," June 25, 2020

June 2020

We are proud of our history of innovation and entrepreneurship, and of our ongoing mission to address major societal challenges. This includes diversity in research interests, research styles, and providing supportive mentorship. EE recognizes that we have significant work to do in these areas and we look to the entire EE community to improve our future.


The Department of Electrical Engineering supports Black Lives Matter, inclusion, and diversity. 

As engineers, engineers-in-training, and staff, we build upon and apply systems-thinking to major societal challenges, including climate change, health, and better communication.

 The Department of Electrical Engineering strives to continue its success in innovation and research through the participation and inclusion of students, post-docs, and faculty from diverse backgrounds, experiences, religions, ethnicities, identities, genders, sexual orientation, and perspectives. We recognize diversity as central and critical to our mission to provide an inclusive environment and culture where all are welcomed, respected, and valued. Diversity in EE.

 

The following links are from our students, colleagues and friends. We include them to provide education and support to our community. 

If you have questions, insights, or edits, please contact us via info@ee.stanford.edu.

 

RELATED RESOURCES

Diversity in EE statement 
Black Lives Matter, Stanford Student Affairs
Coalition of Black Student Organizations Asks to University Administration on Campus Police 

Educational resources for anti-racism:

Support for Stanford students: 

Call for reform: Call to reform criminal justice system, police practices and to the end of police brutality:

Demand justice for George Floyd's murder:

  • Call the following Minneapolis officials or email them using this template:
    • Mayor Jacob Frey: (612) 673-2100
    • DA Mike Freeman: (612) 348-5550
    • Hennepin County Attorney Office: (612) 673-2100
  • Join a phone bank organized by Stanford Students for Workers' Rights
  • Sign this petition organized by Color Of Change demanding the prosecution of the officers involved in the murder of George Floyd.

To support and learn more about the following organizations:

  • Color Of Change: https://colorofchange.org/
  • Voting While Black
  • ACLU, which provides legal services to civil rights complaints.
  • George Floyd Memorial Fund
  • Tony McDade GoFund Me started for black transgender man who was murdered by the police last week.
  • The national bail fund network has a list of community bail funds.
  • List of bail funds by city: Bail funds are a way to support frontline protesters who are being arrested - as well as building towards a movement to end cash bail and free hundreds of thousands of people who are in pre-trial detention during a pandemic.
  • NorthStar Health Collective: NorthStar is a Minnesota-based street medic collective, offering first aid and medical support to people on the frontlines right now.
  • Reclaim the Block: Reclaim the Block is a Minneapolis community org providing supplies and support to protesters, as well as pushing Minneapolis to spend less on policing and more on healthcare, housing and education.
  • The Black Visions Collective and Legal Fund: Black Visions Collective, a Black, trans and queer-led organization, is helping lead the protests and advocating to defund the police in Minnesota.
  • Rebuild Lake Street: Lake Street Council is donating 100% of these proceeds to the local business and nonprofits affected by the fires and helping them continue to serve their communities.

image of prof. Gordon Wetzstein and Isaac Kauvar, EE /PhD
June 2020

Professor Gordon Wetzstein and first authors Isaac Kauvar (EE PhD candidate) and postdoctoral researcher Tim Machado, have developed an optical technique that can simultaneously record the activity of neurons spread across the entire top surface of a mouse's cerebral cortex, a key part of the brain involved in making decisions. Their article, "Cortical Observation by Synchronous Multifocal Optical Sampling Reveals Widespread Population Encoding of Actions" was published in the journal Neuron.

The researchers call their system Cortical Observation by Synchronous Multifocal Optical Sampling, or COSMOS. In addition to studying motor control and decision making, the team is also using COSMOS to study sensory perception in animals and as a screening technique to develop better psychiatric drugs.

The prototype COSMOS system is relatively simple to build and costs less than $50,000, which is hundreds of thousands of dollars cheaper than other optical systems for recording neural population dynamics. To encourage further adoption and development of the technique, the authors have built a website with instructions to help other researchers build their own COSMOS systems.

The bifocal microscope uses a single camera to capture two movies of neural activity at the same time: one focused on the sides of the brain, and the other focused on the middle, to provide a side-by-side view shown in a video. The researchers then computationally extract signals – reflecting the timing, intensity and duration of when neurons fire – from both of these movies to obtain a comprehensive measurement of neural activity across the whole surface.

Excerpted from Stanford News, "Stanford researchers develop an inexpensive technique to show how decisions light up the brain", June 2, 2020.

 

"COSMOS Reveals Widespread Population Encoding of Actions", first authors Isaac Kauvar, EE PhD candidate (photo credit: Daphna Spivack) and Tim Machado, Bioengineering postdoctoral researcher.

 

image of prof Shanhui Fan
May 2020

Professor Shanhui Fan and Sid Assawaworrarit (PhD candidate) recently published "Robust and efficient wireless power transfer using a switch-mode implementation of a nonlinear parity-time symmetric circuit" in Nature Electronics.

They have been working on improving the distance of a wireless charger. Previously they were able to transmit electricity as an object moved, but it wasn't practical.

In their new paper, the researchers show how to boost the system's wireless-transmission efficiency to 92%. The key, Sid Assawaworrarit explained, was to replace the original amplifier with a far more efficient "switch mode" amplifier. Such amplifiers aren't new but they are finicky and will only produce high-efficiency amplification under very precise conditions. It took years of tinkering, and additional theoretical work, to design a circuit configuration that worked.

The new lab prototype can wirelessly transmit 10 watts of electricity over a distance of two or three feet. Shanhui says there aren't any fundamental obstacles to scaling up a system to transmit the tens or hundreds of kilowatts that a car would need. He says the system is more than fast enough to re-supply a speeding automobile. The wireless transmission takes only a few milliseconds – a tiny fraction of the time it would take a car moving at 70 miles an hour to cross a four-foot charging zone. The only limiting factor, says Shanhui, will be how fast the car's batteries can absorb all the power.

Though it could be many years before wireless chargers become embedded in highways, the opportunities for robots and even aerial drones are more immediate. It's much less costly to embed chargers in floors or on rooftops than on long stretches of highway. Imagine a drone, says Shanhui, that could fly all day by swooping down occasionally and hovering around a roof for quick charges.

Excerpted from "Stanford researchers one step closer toward enabling electric cars to recharge themselves wirelessly as they drive"

 

Related

 

image of EE 276 students in the main quad
April 2020

Because of the COVID-19 pandemic, Professor Tsachy Weissman's Information Theory class transformed their in-person outreach event into a digital version. The students prepared videos that present an aspect of information theory, geared toward middle school students. EE276 students could also create blog entries as part of their coursework.

Students from EE276 created videos for middle school students in lieu of the planned in-person outreach event.

The outreach goal of the class is to teach middle school students a range of topics related to information theory. Some teams talk about mapping political landscapes while others delve into the theory of code breaking. Some groups demonstrate military applications when flying jets and others show information theory through Fortnite (https://www.epicgames.com). Each video presentation is unique and appeal to various interests and learning styles of students in middle school.

Tsachy and EE276 students encourage the use of their videos and blogs to help teach and understand concepts in information theory. Outreach project videos are listed below, those with related blogs are also included.

image of professor Krishna Shenoy
April 2020

Researchers from Professor Krishna Shenoy's Group: Saurabh Vyas (Bioengineering PhD candidate), Daniel O'Shea (EE postdoctoral researcher), and Professor Stephen Ryu, M.D. have found that the brain is deeply interested in what happens before you make a movement. Their paper was published in cell.com's Neuron.

Existing theories focus on the practice part — the repetition — not the preparation.
In fact, prior to this study, neuroscientists had no reason to think this preparatory state played any part in learning, says Krishna Shenoy. "We're saying that preparation not only has something to do with learning, it might actually be one of the biggest parts of it," adds Krishna who is a Howard Hughes Medical Institute investigator.

To arrive at this new understanding, the researchers explored how monkeys learn a relatively simple motion: how to use a videogame joystick. In a series of experiments, they first trained the monkeys to use the joystick to direct a computer cursor toward a target on the screen. Next, the scientists altered how the joystick worked so that when the monkeys moved the joystick in the direction they thought was upward or leftward or rightward, the cursor moved in a different direction than expected. Thus, the animals had to learn to move the joysticks anew to get the cursor to the target.

Saurabh Vyas uses an analogy to explain the significance of these findings. Imagine LeBron practicing free throws. He shoots the ball, and gets close, and his learning system uses the error to make some changes in the brain. But if his brain activity is disrupted during the planning period — or he doesn't take an instant to pre-visualize the shot — his next attempt will not do as well because he wasn't mindful enough during the critical, pre-movement period.

These findings significantly advance our understanding of the neurological underpinnings of learning. It has long been known that motor and other areas in the brain become active prior to movement. During this preparatory phase, brain activity reflects precise details of how the body should complete a movement.

Consequently, giving the mind more time to prepare — more time to visualize the task at hand — substantially improves learning. From a purely practical standpoint, the findings could reshape how athletes, artists, musicians or anyone who moves their body gets better at what they do.

Ultimately, Krishna and Saurabh hope to apply this new understanding to their specialty: developing prosthetic devices that are controlled by chips implanted in the brain that transform an individual's thoughts into movement. Krishna adds, "The more we understand about how the brain learns new motor skills and performs movement calculations, the more lifelike and realistic we can make thought-controlled prosthetics."

 

Excerpted from Stanford Engineering,"A team of scientists explore how the brain trains muscles to move" February 26, 2020.

 

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