EE Student Information


prof Krishna Shenoy
October 2021

Congratulations to Professor Krishna Shenoy for his Howard Hughes Medical Institute (HHMI) investigatorship renewal. Krishna's research is in the area of fundamental cortical motor control and brain-computer interface design.

HHMI is a 60-year old non-profit biomedical research organization (>$21B endowment) and is unique in providing long-term flexible funding to relatively few people (~250 total; Krishna and Karl Deisseroth are our SOE HHMI Investigators). HHMI's philosophy is "people, not projects" due to the belief in the power of Investigators to make breakthroughs through sustained, focused and fundamental research."


Please join us in congratulating Krishna on his renewal term and extraordinary research.



prof Priyanka Raina
September 2021

For decades, the general-purpose central processing unit—the CPU—has been the workhorse of the computer industry. It could handle any task—literally—even if most of those capabilities were unnecessary.

This model was all well and good as chips grew smaller, faster and more efficient by the day, but less so as the pace of progress has slowed, says Professor Priyanka Raina, an expert in chip design. Priyanka says that to keep chips on their ever-improving trajectory, chip makers have shifted focus to chips that do specific tasks very well. The graphics processing unit (GPU), which handles the intense mathematics necessary for video and gaming graphics, is a perfect example.

Soon, there’ll be a faster, more efficient chip for every task, but it’ll take industry-wide cooperation to get there, as Priyanka tells listeners to this episode of Stanford Engineering’s The Future of Everything podcast with host Russ AltmanListen and subscribe here.



Source: The Future of Everything Series, "Priyanka Raina: How computer chips get speedier through specialization."


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Prof. Eric pop
September 2021

Professor Eric Pop's lab - Pop Lab - took a long shot adapting phase-change memory (PCM) to plastic substrates – turns out the energy-efficiency significantly improved compared to PCM on conventional silicon substrates.

Phase change materials leverage changes in structure into differences in electrical resistance that are attractive for computer memory and processing applications. Khan et al. developed a flexible phase change memory device with layers of antimony telluride and germanium telluride deposited directly on a flexible polyimide substrate. The device shows multilevel operation with low switching current density. The combination of phase change and flexible mechanical properties is attractive for the large number of emerging applications for flexible electronics.

"It's the same atoms as conventional phase-change memory but in beautiful striped alternating thin layers, also known as a superlattice," says Professor Eric Pop.

Eric's group put arrays of memory cells made of superlattices of alternating layers of antimony telluride and germanium telluride on flexible plastic substrates. They were curious whether they could make it work—flexible memory is a key enabling technology for electronic skin, lightweight environmental sensors, and other unconventional electronics. Once grad student Asir Intisar Khan and postdoc Alwin Daus figured out how to make these devices at temperatures that would not melt the polyimide substrate, the researchers were surprised by what they found.

"The flexible substrate provides an extra advantage we did not anticipate," reports Eric Pop. The current density required to switch the flexible memory cells is 10 to 100x lower than any previously reported phase-change memory, and the memory cells maintain their performance when the substrate is bent. After seeing the results, the team was "scrambling," he continues. "Why is this better?" The Stanford group believes that the layers in the superlattice, the cell's "pore-like" design, as well as the insulating properties of the plastic substrate, help confine the energy applied to the memory cells, making them heat up more efficiently and spurring a phase change at lower electrical currents.

Excerpted from c&en (Chemical & Engineering News), "Flexible memory uses less power" and IEEE Spectrum, "This Memory Tech Is Better When It's Bendy



image of prof Shanhui Fan and Aaswath Raman
August 2021

Professor Shanhui Fan and EE alum, Professor Aaswath Raman (UCLA) are using their technology to potentially reduce heat-related deaths. As higher temperatures become more frequent, the use of air conditioning increases, resulting in a cycle of baking the planet in an attempt to keep people cool.

Pictured are Aaswath Raman as a graduate student (on the left) with Professor Shanhui Fan in 2011.

Shanhui and Aaswath developed a film that was both highly reflective of visible light—so it wouldn't warm up in the sun—and an excellent emitter of infrared radiation at just the right wavelengths to pass through the atmosphere unimpeded. If the film covered the hood of a car, it would conduct heat away from the hood, cooling it without using any electricity.

Since they published their findings in 2014, other researchers have designed paints, gels, and wood that can remain cool in daylight. In 2020, their film was installed on a supermarket roof, resulting in energy savings of 15-20 percent.

The film is currently being tested on a few bus shelters in Tempe, Arizona. Preliminary results show that the roofs can be 30 degrees cooler than the surrounding air.

Today, Professor Aaswath Raman is involved in a UCLA project called Heat Resistant Los Angeles. "The idea is, can we go beyond shade?" he says. Historically, cities have focused on providing shade trees, parks, and green belts to help cool urban environments, but such projects often bypass low-income communities and take years to establish. Raman envisions using canopies coated with his film to cool large outdoor spaces; these could be set up quickly at a relatively low cost.

"It's very early days for the project," he says, "so it's still kind of speculative. But I'm hoping in a year or two we'll have some cool results and demos to share."


The World Health Organization estimates that between 1998 and 2017, heat waves killed at least 166,000 people around the world. If we continue to emit greenhouse gases at the current rate, deadly heat will put more than a billion people at risk by the end of the century.

The technology may ultimately help cool our cities, and it may be able to prevent tens or hundreds of thousands of deaths from the brutal heat waves to come, which would be no small feat. But to cool the whole world, we've known for decades what needs to be done: Leave fossil fuels in the ground.


Excerpted from "This new technology could help cool people down—without electricity"

image of prof Dan Boneh
August 2021
Professor Dan Boneh heads the applied cryptography group and co-direct the computer security lab. 
He has been part of an effort to warn about sensitive content without making private communications readable by the process. Coming up with the security measures required a delicate balancing act between cracking down on the exploitation of children while protecting the privacy of users.
Professor Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, web security, security for mobile devices, and cryptanalysis.

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image of Chelsea Finn
July 2021

Assistant Professor Chelsea Finn and her team designed a neural network system solely for Stanford's programming class. They used techniques that could automate student feedback in other situations, including for classes beyond programming.

Chelsea's system spent hours analyzing examples from old midterms, learning from a decade of possibilities. Then it was ready to learn more. When given just a handful of extra examples from the new exam offered this spring, it could quickly grasp the task at hand.

"It sees many kinds of problems," said PhD candidate Mike Wu. "Then it can adapt to problems it has never seen before."

This spring, the system provided 16,000 pieces of feedback, and students agreed with the feedback 97.9 percent of the time, according to a study by the researchers. By comparison, students agreed with the feedback from human instructors 96.7 percent of the time.


Chelsea Finn is an assistant professor of electrical engineering and computer science.



Excerpted from The New York Times, "Can A.I. Grade Your Next Test?"

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image of prof Dorsa Sadigh
July 2021

Congratulations to Assistant Professor Dorsa Sadigh! She is included with MIT's 35 Innovators Under 35.

By developing new ways for computers to anticipate people's actions, Dorsa Sadigh wants to help pave the way for a future in which human and robots do things like share the roads. Her research interests lie at the intersection of robotics, machine learning, and control theory. Dorsa's research group develops algorithms for AI agents that safely and reliably interact with people. Her research group is ILIAD

The MIT Technology Review, 35 Innovators Under 35 looks at where technology is now, and where it's going and who's taking it there. Congratulations to all the innovators!


Please join us in congratulating Dorsa on this recognition!



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image of prof Howard Zebker
June 2021

Venus is often called Earth's sister planet or twin because the two worlds are of similar size and density. Yet the second rock from the sun is hot and inhospitable in the extreme. "That's one of the reasons we know so little about the surface," said Professor Howard Zebker. "If you send a spacecraft to the surface of Venus, which has been done several times, they only last a few minutes until the hot acid burns them up."

Howard is a member of the science team for VERITAS, one of three missions to Venus announced in June 2021 by NASA and the European Space Agency. As part of the VERITAS mission – which is expected to launch around 2028-2030 – instruments aboard the spacecraft will measure how long it takes radar signals to bounce back from a series of precise locations at different times. This will yield pairs of images that can be combined to reveal changes in altitude at the surface using a technique known as interferometric synthetic aperture radar, or InSAR.

Algorithms and techniques pioneered by Howard will help to guide these measurements and translate them into high-resolution 3D maps of any ongoing deformation of Venus' outermost layer. On Earth, InSAR has been used to map uplift and subsidence related to groundwater pumping; to detect sinkholes; and to study glacier movements, earthquakes, volcanic eruptions, landslides and more. But this is the first time the techniques will be used by spacecraft to identify active fault movements beyond our world.

While NASA's Jet Propulsion Laboratory in Pasadena, Calif. will manage the VERITAS (Venus Emissivity, Radio Science, InSAR, Topography & Spectroscopy) mission, students working in Professor Zebker's lab – Radar Remote Sensing & Radar Interferometry Group will help to refine algorithms for the mission over the next several years and work to interpret the data that come in once VERITAS makes it into orbit.

Howard Zebker is a professor of geophysics and electrical engineering. He discusses his role in the VERITAS mission; how InSAR will help to answer key questions about volcanic activity and tectonic plates on Venus; why our hothouse twin may hold insights relevant to modeling of climate change on our own planet; and paths for interested students to get involved.


Excerpted from Stanford News, "Is Venus still geologically active? Stanford expert explains technology powering NASA's quest to understand Earth's twin", June 29, 2021.

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image of professor Eric Pop
June 2021

Professor Eric Pop and team describe the ability to produce nanoscale flexible electronics In their paper, "High-Performance Flexible Nanoscale Transistors Based on Transition Metal Dichalcogenides," published in Nature Electronics. Flexible electronics promise bendable, shapeable, yet energy-efficient computer circuits that can be worn on or implanted in the human body to perform myriad health-related tasks. Future variations future of the circuits will communicate wirelessly with the outside world – another large leap toward viability for flextronics, particularly those implanted in the human body or integrated deep within other devices connected to the internet of things.

With a prototype and patent application complete, postdoc Alwin Daus and Professor Eric Pop have moved on to their next challenges of refining the devices. They have built similar transistors using two other atomically thin semiconductors (MoSe2 and WSe2) to demonstrate the broad applicability of the technique.

Meanwhile, Alwin said that he is looking into integrating radio circuitry with the devices, which will allow future variations to communicate wirelessly with the outside world – another large leap toward viability for flextronics, particularly those implanted in the human body or integrated deep within other devices connected to the internet of things.

Eric reports, "This is more than a promising production technique. We've achieved flexibility, density, high performance and low power – all at the same time. This work will hopefully move the technology forward on several levels."

Co-authors include postdoctoral scholars Sam Vaziri and Kevin Brenner, EE doctoral candidates Victoria Chen, Çağıl Köroğlu, Ryan Grady, Connor Bailey and Kirstin Schauble, and research scientist Hye Ryoung Lee. Pop Lab People


Excerpted from "Stanford researchers develop new manufacturing technique for flexible electronics" Stanford News

image of Londa Schiebinger and James Zou
June 2021

Debiasing artificial intelligence (AI)

In the medical field, AI encompasses a suite of technologies that can help diagnose patients’ ailments, improve health care delivery and enhance basic research. The technologies involve algorithms, or instructions, run by software. These algorithms can act like an extra set of eyes perusing lab tests and radiological images; for instance, by parsing CT scans for particular shapes and color densities that could indicate disease or injury.

Problems of bias can emerge, however, at various stages of these devices’ development and deployment, James explained. One major factor is that the data for forming models used by algorithms as baselines can come from nonrepresentative patient datasets.

By failing to properly take race, sex and socioeconomic status into account, these models can be poor predictors for certain groups. To make matters worse, clinicians might lack any awareness of AI medical devices potentially producing skewed results. 

In a new perspective paper, James Zou and Londa Schiebinger discuss sex, gender and race bias in medicine and how these biases could be perpetuated by AI devices. 
James and Londa suggest several short- and long-term approaches to prevent AI-related bias, such as changing policies at medical funding agencies and scientific publications to ensure the data collected for studies are diverse, and incorporating more social, cultural and ethical awareness into university curricula.

“The white body and the male body have long been the norm in medicine guiding drug discovery, treatment and standards of care, so it’s important that we do not let AI devices fall into that historical pattern,” said Londa Schiebinger, the John L. Hinds Professor in the History of Science in the School of Humanities and Sciences and senior author of the paper published in the journal EBioMedicine.

“As we’re developing AI technologies for health care, we want to make sure these technologies have broad benefits for diverse demographics and populations,” said James Zou, assistant professor of biomedical data science and, by courtesy, of computer science and of electrical engineering and co-author of the study.

The matter of bias will only become more important as personalized, precision medicine grows in the coming years, said the researchers. Personalized medicine, which is tailored to each patient based on factors such as their demographics and genetics, is vulnerable to inequity if AI medical devices cannot adequately account for individuals’ differences.

“We’re hoping to engage the AI biomedical community in preventing bias and creating equity in the initial design of research, rather than having to fix things after the fact,” said Londa Schiebinger.

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