News

Nikhil Garg, EE PhD '20 interdisciplinary research using machine-learning
April 2018

Lead author Nikhil Garg (PhD candidate '20) demonstrates that word embeddings can be used as a powerful tool to quantify historical trends and social change. His research team developed metrics based on word embeddings to characterize how gender stereotypes and attitudes toward ethnic minorities in the United States evolved during the 20th and 21st centuries starting from 1910. Their framework opens up a fruitful intersection between machine learning and quantitative social science.

Nikhil co-authored the paper with history Professor Londa Schiebinger, linguistics and computer science Professor Dan Jurafsky and biomedical data science Professor James Zou.

Their research shows that, over the past century, linguistic changes in gender and ethnic stereotypes correlated with major social movements and demographic changes in the U.S. Census data.

The researchers used word embeddings – an algorithmic technique that can map relationships and associations between words – to measure changes in gender and ethnic stereotypes over the past century in the United States. They analyzed large databases of American books, newspapers and other texts and looked at how those linguistic changes correlated with actual U.S. Census demographic data and major social shifts such as the women's movement in the 1960s and the increase in Asian immigration, according to the research.

"Word embeddings can be used as a microscope to study historical changes in stereotypes in our society," said James Zou, a courtesy professor of electrical engineering. "Our prior research has shown that embeddings effectively capture existing stereotypes and that those biases can be systematically removed. But we think that, instead of removing those stereotypes, we can also use embeddings as a historical lens for quantitative, linguistic and sociological analyses of biases."

"This type of research opens all kinds of doors to us," Schiebinger said. "It provides a new level of evidence that allow humanities scholars to go after questions about the evolution of stereotypes and biases at a scale that has never been done before."

"The starkness of the change in stereotypes stood out to me," Garg said. "When you study history, you learn about propaganda campaigns and these outdated views of foreign groups. But how much the literature produced at the time reflected those stereotypes was hard to appreciate." 

The new research illuminates the value of interdisciplinary teamwork between humanities and the sciences, researchers said.

"This led to a very interesting and fruitful collaboration," Schiebinger said, adding that members of the group are working on further research together. "It underscores the importance of humanists and computer scientists working together. There is a power to these new machine-learning methods in humanities research that is just being understood." 


 

Proceedings of the National Academy of Sciences, "Word embeddings quantify 100 years of gender and ethnic stereotypes" April 3,2018.  

Excerpted from Stanford News, "Stanford researchers use machine-learning algorithm to measure changes in gender, ethnic bias in U.S." April 3, 2018.

 

 

 

Ana Klimovic, EE PhD '19
April 2018

Congratulations to Ana Klimovic (PhD candidate '19), Professor Christos Kozyrakis, and postdoc Heiner Litz. They won the 2018 Memorable Paper Award for System Architecture and Applications at the 9th Annual Non-Volatile Memories Workshop (NVMW) hosted by the University of California, San Diego. Their paper, "ReFlex: Remote Flash == Local Flash" was one of six finalists for the award selected from over 80 papers submitted to the workshop.

About The Memorable Paper Award

The Memorable Paper Award recognizes the best recent research on non-volatile memories published throughout the world. It is given annually to outstanding research published in the last two years that is expected to have substantial impact on the study of non-volatile memories. To be eligible, the paper must have been published in peer-reviewed venue in the last two years and the lead researcher must have been a student at the time.

About the Non-Volatile Memories Workshop

The Non-Volatile Memories Workshop is the world's premier venue for research into how to use non-volatile memory technology to improve the performance, reliability, and efficiency of computing systems. It was founded in 2010 by Dr. Paul Siegel and Dr. Steven Swanson of the University of California, San Diego's Jacob School of engineering. The workshop is a co-production of the Center for Magnetic Recording Research and the Non-Volatile Systems Laboratory at UC San Diego. More information, including a detailed program, is available at nvmw.ucsd.edu.

Please join us in congratulating Ana, Christos, and Heiner on their award! 


Award winner Ana Kilmovic (center) with general chairs of NVMW'18 Professor Steven Swanson (left) and Professor Paul Siegel (right), both of UCSD.

Paper Summary:

Internet companies such as Facebook and Google host trillions of messages, photos, and videos for their users. Hence, they need storage systems that are massive in scale, fast to access, and cost effective. Scale is achieved by hosting internet services in datacenters with thousands of machines, each contributing its local storage to the global data pool. Speed is achieved by selectively replacing slow hard disks in machines with Flash storage devices that can serve data accesses with 100x lower latency and 10,000x higher throughput.

However, Flash makes it difficult to build a cost-effective storage system. Flash devices are typically underutilized in terms of capacity and throughput due to the imbalance in the compute and storage requirements of the internet services running on each machine. In the past, datacenter operators dealt with the same challenge for disks by allowing services running on each machine to allocate storage over the network on any disk with spare capacity and bandwidth in the datacenter. Remote (over the network) access to disks enables utilizing all available capacity and throughput. Past efforts to implement similar remote access systems for Flash devices have run into significant challenges. Network protocol processing at the throughput of Flash devices requires a large number of processor cores and adds overheads that cancel out the latency advantages of using Flash. Moreover, when two remote machines access the same Flash device, interference between the two access streams can lead to unpredictable performance degradation.

To address these challenges, researchers Ana Klimovic, Heiner Litz and Christos Kozyrakis developed a software system called ReFlex. ReFlex enables high performance access to remote Flash storage with minimal compute resources and provides predictable performance for multiple services sharing a Flash device over the network. Using a single processing core, the system can process up to 850,000 requests per second which is 11x more than a traditional Linux network storage system. ReFlex makes remote Flash look like local Flash to applications, making it easy for a service running on a particular machine to use spare Flash capacity and bandwidth on other machines in the datacenter. To provide predictable performance when multiple remote machines access the same Flash device, ReFlex uses a novel scheduler to process incoming requests in an interference-aware manner.

ReFlex is having an increasing impact in industry and, in collaboration with IBM Research, has been integrated into the Apache Crail distributed storage system. This integration allows popular data analytics frameworks to leverage ReFlex to improve their resource efficiency while maintaining high, predictable performance. ReFlex is also being ported to a system on chip (SoC) platform by Broadcom Limited. ReFlex is open-source software and available at: https://www.github.com/stanford-mast/reflex.

 

Excerpted from the full NVMW'18 press release.

April 2018

The 2018 EE Admit Weekend welcomed 60 newly admitted PhD graduate students. The 2-day event connected admitted students with current students, faculty and staff. Several student-faculty sessions occurred throughout the 2 days, fostering a range of discussions from research topics to housing. Admitted students also participated in research lab and campus tours. Friday concluded with a PhD student research poster session and dinner with faculty.

Twenty-two PhD research projects were presented in this year's poster session. The posters are judged on oral presentation, visual quality, and clarity of presentation – all within a one minute timeframe. Judges include staff, faculty and students, and select one entry from EE's core research areas.

The 2018 poster award winners are:

  • Spyridon Baltsavias (PhD candidate '21), Hardware/Software Systems, for his poster, "Ingestible and Implantable Ultrasonic Sensors for GI-Tract Real-Time Monitoring"
  • Joseph Landry (PhD candidate '19), Physical Technology & Science, for his poster, "Structured Illumination Light Sheet Microscopy for High Throughput Imaging of Thick Tissue"
  • David Lindell (PhD candidate '22), Information Systems & Science, for his poster titled, "Confocal Non-Line-of-Sight Imaging based on the Light Cone Transform"

The winning student researchers were presented with a gift card and certificate from the EE Student Life Committee.

Congratulations and thanks to everyone for participating in the 2018 EE Admit Weekend and research poster session! Additional thanks to the EE Admissions, GSEE, and the EE Student Life Committee for sponsoring the poster contest and generous prizes. 

 

March 2018

The Electrical Engineering staff recognized this month for their outstanding effort are Beverly Davis, Teresa Nguyen, and Helen Niu.

Each were nominated by peers, faculty and/or students who included descriptions of their professionalism that goes above and beyond their everyday roles. Gift card recipients make profound and positive impact in the department's everyday work and academic environment.

 

Please join us in acknowledging Beverly, Teresa, and Helen's extraordinary work! Modified excerpts from their nominations follow.

 

Beverly Davis, Faculty Administrator

  • "Beverly is a rock star!"
  • She is really fun to talk to and does her job flawlessly.

Teresa Nguyen, Student Financial Officer

  • "She has been such a great help to me during grad school!"
  • Teresa is very knowledgeable and kind - I'm so glad she's part of our team.

Helen Niu, Faculty Administrator

  • Helen is extraordinarily capable and diligent.
  • "I am extremely grateful for her!"

Please congratulate them for their outstanding work!

The Staff Gift Card Bonus Program is sponsored by the School of Engineering. Each year, the EE department receives several gift cards to distribute to staff members who are recognized for going above and beyond their role. Each month, staff are chosen from nominations received from faculty, students, and staff. Past nominations are eligible for future months.

Nominate a deserving staff person or group today – nominate individuals or groups that have made a profound improvement in your daily work life. Each recipient receives a $50 Visa card. Nominations can be made at any time.

electrical engineer John Hennessy wins Turing Award
March 2018

Professor John L. Hennessy and retired UC Berkeley professor David Patterson have been named recipients of the 2017 ACM A.M. Turing Award for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry. Hennessy and Patterson created a systematic and quantitative approach to designing faster, lower power, and reduced instruction set computer (RISC) microprocessors. Their approach led to lasting and repeatable principles that generations of architects have used for many projects in academia and industry. Today, 99% of the more than 16 billion microprocessors produced annually are RISC processors, and are found in nearly all smartphones, tablets, and the billions of embedded devices that comprise the Internet of Things (IoT).

John is the James F. and Mary Lynn Gibbons Professor of Computer Science and Electrical Engineering, and Shriram Family Director, Knight-Hennessy Scholars. He was dean of the School of Engineering (1996-2000), university provost (1999-2000), and Stanford University's 10th president (2006-2016).

The ACM Turing Award, often referred to as the "Nobel Prize of Computing," carries a $1 million prize, with financial support provided by Google, Inc. It is named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing. Hennessy and Patterson will formally receive the 2017 ACM A.M. Turing Award at the ACM's annual awards banquet being held this June in San Francisco.

"ACM initiated the Turing Award in 1966 to recognize contributions of lasting and major technical importance to the computing field," said ACM President Vicki L. Hanson. "The work of Hennessy and Patterson certainly exemplifies this standard. Their contributions to energy-efficient RISC-based processors have helped make possible the mobile and IoT revolutions. At the same time, their seminal textbook has advanced the pace of innovation across the industry over the past 25 years by influencing generations of engineers and computer designers."

Attesting to the impact of Hennessy and Patterson's work is the assessment of Bill Gates, principal founder of Microsoft Corporation, that their contributions "have proven to be fundamental to the very foundation upon which an entire industry flourished."

Please join us in congratulating John for this outstanding recognition of quantitative computer architectures and impact on the microprocessor industry.


 

Related News:

"Marty Hellman receives 2015 ACM A.M. Turing Award," March 2016.

ACM press release, "Pioneers of Modern Computer Architecture Receive ACM A.M. Turing Award," March 21, 2018. 

Stanford News, "Former Stanford President wins Turing Award for contributions to computing," March 22, 2018.

March 2018

In November 2017, the EE and CS departments hosted the Rising Stars Workshop. We welcomed 70 women from around the world for two days of workshops, panels, and discussions aimed at helping them navigate an academic career.

Rising Stars – now in it's 6th year – was started at MIT with the sole intention of helping women interested in academic careers navigate the process.

At the welcome dinner, Provost Persis Drell encouraged the participants to "always remember that the diversity you bring to the conversation is of enormous value. It's not about them having accepted or allowed you into the room, it's that they desperately need you to be there."

Co-chairs of the event were professors Moses Charikar, Andrea Goldsmith and Fei-Fei Li. They were joined by more than 30 faculty, as well as industry leaders to organize and run the event. The participants were selected from nearly 400 applications.

For the young scholars, hearing from a range of panelists with a variety of backgrounds helped give them the tools and the mindset they need to succeed. Umashanthi Pavalanathan, a doctoral candidate in social computing and natural language processing at Georgia Tech, said that as an international student from Sri Lanka, hearing the experiences of faculty members with similar histories gave her confidence: "When I see role models, I get inspired." Adds Sara Mouradian, a doctoral candidate in quantum information processing at MIT: "When you go to conferences, I'm usually the only one or one of two women in any given room of 50 to 100 people, so it's been great to see all these women." Being here, she says, has been "mind-blowing."

Thanks to all of our participants and support for the 2017 Rising Stars event.

 

Excerpted from "'Rising Stars' workshop raises visibility for women in engineering," Stanford Engineering, March 14, 2018.

Rising Stars 2017 website.

Graduate student David Lindell and Matt O’Toole, a post-doctoral scholar, work in the lab. (Image credit: L.A. Cicero)
March 2018

A driverless car is making its way through a winding neighborhood street, about to make a sharp turn onto a road where a child’s ball has just rolled. Although no person in the car can see that ball, the car stops to avoid it. This is because the car is outfitted with extremely sensitive laser technology that reflects off nearby objects to see around corners.

“It sounds like magic but the idea of non-line-of-sight imaging is actually feasible,” said Gordon Wetzstein, assistant professor of electrical engineering and senior author of the paper describing this work, published March 5 in Nature.

Related Links

February 2018

Oyekunle Olukotun, Cadence Design Systems Professor of Electrical Engineering and Computer Science at Stanford University, has been selected to receive the IEEE Computer Society 2018 Harry H. Goode Award. 

 
The Goode Award was established to recognize achievements in the information processing field which are considered either a single contribution of theory, design, or technique of outstanding significance, or the accumulation of important contributions on theory or practice over an extended time period. 
 
A well-known pioneer in multicore processor design and the leader of the Stanford Hydra Chip Multiprocessor (CMP) research project, Olukotun is being recognized “for fundamental and sustained effort to create and leverage chip-multiprocessors.”
 

Related Links

image credit: L. Cicero
February 2018


Krishna Shenoy and team have been researching the use of brain machine interfaces (BMI) to assist people with paralysis. Recently, one of the researchers changed the task, requiring physical movement from a change in thought. He realized that the BMI would allow study of the mental rehearsal that occurs before the physical expression.

Although there are some important caveats, the results could point the way toward a deeper understanding of what mental rehearsal is and, the researchers believe, to a future where brain-machine interfaces, usually thought of as prosthetics for people with paralysis, are also tools for understanding the brain.

"Mental rehearsal is tantalizing, but difficult to study," said Saurabh Vyas, a graduate student in bioengineering and the paper's lead author. That's because there's no easy way to peer into a person's brain as he imagines himself racing to a win or practicing a performance. "This is where we thought brain-machine interfaces could be that lens, because they give you the ability to see what the brain is doing even when they're not actually moving," he said.

"We can't prove the connection beyond a shadow of a doubt," Krishna said, but "this is a major step in understanding what mental rehearsal may well be in all of us." The next steps, he and Vyas said, are to figure out how mental rehearsal relates to practice with a brain-machine interface – and how mental preparation, the key ingredient in transferring that practice to physical movements, relates to movement.

Meanwhile, Krishna said, the results demonstrate the potential of an entirely new tool for studying the mind. "It's like building a new tool and using it for something," he said. "We used a brain-machine interface to probe and advance basic science, and that's just super exciting."

Additional Stanford authors are Nir Even-Chen, a graduate student in electrical engineering, Sergey Stavisky, a postdoctoral fellow in neurosurgery, Stephen Ryu, an adjunct professor of electrical engineering, and Paul Nuyujukian, an assistant professor of bioengineering and of neurosurgery and a member of Stanford Bio-X and the Stanford Neurosciences Institute.

Funding for the study came from the National Institutes of Health, the National Science Foundation, a Ric Weiland Stanford Graduate Fellowship, a Bio-X Bowes Fellowship, the ALS Association, the Defense Advanced Research Projects Agency, the Simons Foundation and the Howard Hughes Medical Institute.

Excerpted from Stanford News, "Mental rehearsal prepares our minds for real-world action, Stanford researchers find," February 16, 2018.

 

Related News:

Research by PhD candidate and team detects errors from Neural Activity, November 2017.

Krishna Shenoy's translation device; turning thought into movement, March 2017.

Brain-Sensing Tech Developed by Krishna Shenoy and Team, September 2016.

Krishna Shenoy receives Inaugural Professorship, February 2017.

 

February 2018

Angad Rekhi (PhD candidate) and Amin Arbabian have developed a wake-up receiver that turns on a device in response to incoming ultrasonic signals – signals outside the range that humans can hear. By working at a significantly smaller wavelength and switching from radio waves to ultrasound, this receiver is much smaller than similar wake-up receivers that respond to radio signals, while operating at extremely low power and with extended range.

This wake-up receiver has many potential applications, particularly in designing the next generation of networked devices, including so-called "smart" devices that can communicate directly with one another without human intervention.

"As technology advances, people use it for applications that you could never have thought of. The internet and the cellphone are two great examples of that," said Rekhi. "I'm excited to see how people will use wake-up receivers to enable the next generation of the Internet of Things."

Excerpted from Stanford News, "Stanford researchers develop new method for waking up small electronic devices", February 12, 2018

 

Related news:

Amin's Research Team Powers Tiny Implantable Devices, December 2017.

Stanford Team led by Amin Arbabian receives DOE ARPA-E Award, January 2017.

Amin Arbabian receives Tau Beta Pi Undergrad Teaching Award, June 2016.

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February 2014

Three staff members each received a $50 Visa card in recognition of their extraordinary efforts as part of the department’s 2014 Staff Gift Card Bonus Program. The EE department received several nominations in January, and nominations from 2013 were also considered.

Following are January’s gift card recipients and some of the comments from their nominators:

Ann Guerra, Faculty Administrator

  • “She is very kind to students and always enthusiastic to help students… every time we need emergent help, she is willing to give us a hand.”
  • “Ann helps anyone who goes to her for help with anything, sometimes when it’s beyond her duty.” 

Teresa Nguyen, Student Accounting Associate

  • “She stays on top of our many, many student financial issues, is an extremely reliable source of information and is super friendly.”
  • “Teresa’s cheerful disposition, her determination, and her professionalism seem to go above and beyond what is simply required.”

Helen Niu, Faculty Administrator

  • “Helen is always a pleasure to work with.”
  • “She goes the extra mile in her dealings with me, which is very much appreciated.”

The School of Engineering once again gave the EE department several gift cards to distribute to staff members who are recognized for going above and beyond. More people will be recognized next month, and past nominations will still be eligible for future months. EE faculty, staff and students are welcome to nominate a deserving staff person by visitinghttps://gradapps.stanford.edu/NotableStaff/nomination/create.

Ann Guerra  Teresa Nguyen  Helen Niu

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