Allen School News

Allen School senior Hannah Werbel is among four undergraduates to earn the prestigious Dean’s Medal from the University of Washington’s College of Arts & Sciences. Werbel, who will receive her bachelor’s in Computer Science with minors in Physics and Mathematics this month, was named a Dean’s Medalist in the Natural Sciences category for her academic excellence, leadership, and service.

From the moment she stepped on campus, Werbel has distinguished herself through a rigorous program of study and her participation in a variety of extra-curricular and volunteer activities. In her sophomore year, she earned the Freshman Medal as part of the UW President’s Medalist Awards in recognition of her high academic standing and campus involvement. Outside of the classroom, Werbel has played the piccolo as part of the Husky Marching Band for the past four years, frequently volunteering her time and talents for smaller alumni and charity functions in addition to her regular band duties. Her efforts earned her the Bill Bissel Memorial Award last year, which recognizes the student who most embodies the band’s “touch of class” motto.

Werbel, who is legally blind, has made accessibility a centerpiece of her campus engagement. She has served as president of the Washington Association of Blind Students since her freshman year and also worked as a student assistant for the DO-IT Center, which focuses on empowering people with disabilities to succeed through education and technology. In that role, Werbel planned events for high school students participating in the center’s summer college preparatory program and spoke at a variety of events about accessibility in higher education and the STEM (science, technology, engineering, and mathematics) fields. In 2017, Werbel was selected to participate in the Lime Connect Fellowship Program, which offers professional and leadership development opportunities to outstanding juniors with disabilities.

In addition to being an accomplished student, accessibility advocate, and musician, Werbel excelled in research. Even before her arrival on campus, Werbel completed a summer research internship in the UW BioRobotics Lab during her junior year of high school. As part of her internship, she programmed software modules in MATLAB to analyze data generated from experiments with brain-computer interfaces. The research team was so impressed with Werbel’s work, she was invited to continue working in the lab after her internship ended. Werbel also spent two quarters as a teaching assistant for the Allen School’s introductory computer science class, CSE 142. She was recognized with the Outstanding Female Engineer Award from the UW chapter of the Society of Women Engineers in 2017.

“Hannah’s time at UW has been marked by interdisciplinary academic excellence and leadership inside and outside of the classroom,” said Hank Levy, Director of the Allen School and Wissner-Slivka Chair. “She is humble, intelligent, hard-working, and inspirational. Hannah joined our undergraduate program as an interest-changer after her sophomore year, and she has only reached the beginning of her potential in the field of computer science. She likely doesn’t quite know how special she is and how far her talent will take her, and I hope this recognition pushes her to even greater heights.”

Alternately described as “dedicated,” “selfless,” and “an ambassador for the University,” Werbel has helped make the campus community a better place than when she found it. Following her graduation from the Allen School, Werbel will spend the summer as a research intern with Microsoft Quantum Computing before joining Facebook full-time as a software engineer.

Read GeekWire’s Geek of the Week profile of Werbel here and our previous Undergrad Spotlight featuring Werbel here.

Congratulations, Hannah, and thank you for your commitment to excellence and service to your fellow students inside and outside of the Allen School!

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When we hear the term “fake news,” more often than not it refers to false narratives written by people to distort the truth and poison the public discourse. But new developments in natural language generation have raised the prospect of a new potential threat: neural fake news. Generated by artificial intelligence and capable of adopting the particular language and tone of popular publications, this brand of fake news could pose an even greater problem for society due to its ability to emulate legitimate news sources at a massive scale. To fight the emerging threat of fake news authored by AI, a team of researchers at the Allen School and Allen Institute for Artificial Intelligence (AI2) developed Grover, a new model for detecting neural fake news more reliably than existing technologies can.

Until now, the best discriminators could correctly distinguish between real, human-generated news content and AI-generated fake news 73% of the time; using Grover, the rate of accuracy rises to 92%. What makes Grover so effective at spotting fake content is that it learned to be very good at producing that content itself. Given a sample headline, Grover can generate an entire news article written in the style of a legitimate news outlet. In an experiment, the researchers found that the system can also generate propaganda stories in such a way that readers rated them more trustworthy than the original, human-generated versions.

“Our work on Grover demonstrates that the best models for detecting disinformation are the best models at generating it,” explained Yejin Choi, a professor in the Allen School’s Natural Language Processing group and a researcher at AI2. “The fact that participants in our study found Grover’s fake news stories to be more trustworthy than the ones written by their fellow humans illustrates how far natural language generation has evolved — and why we need to try and get ahead of this threat.”

Choi and her collaborators — Allen School Ph.D. students Rowan Zellers, Ari Holtzman, and Hannah Rashkin; postdoctoral researcher Yonatan Bisk; professor and AI2 researcher Ali Farhadi; and professor Franziska Roesner — describe their results in detail in a paper recently published on the preprint site arXiv.org. Although they show that Grover is capable of emulating the style of a particular outlet and even writer — for example, one of the Grover-generated fake news pieces included in the paper is modeled on the writing of columnist Paul Krugman of The New York Times — the researchers point out that even the best examples of neural fake news are still based on learned style and tone, rather than a true understanding of language and the world. So, that Krugman piece and others like it will contain evidence of the true source of the content.

“Despite how fluid the writing may appear, articles written by Grover and other neural language generators contain unique artifacts or quirks of language that give away their machine origin,” explained Zellers, lead author of the paper. “It’s akin to a signature or watermark left behind by neural text generators. Grover knows to look for these artifacts, which is what makes it so effective at picking out the stories that were created by AI.”

Although Grover will naturally recognize its own quirks, which explains the high success rate in the team’s study, the ability to detect evidence of AI-generated fake news is not limited to its own content. Grover is better at detecting fake news written by both human and machine than any system that came before it, in large part because it is more advanced than any neural language model that came before. The researchers believe that their work on Grover is only the first step in developing effective defenses against the machine-learning equivalent of a supermarket tabloid. They plan to release two of their models, Grover-Base and Grover-Large, to the public, and to make the Grover-Mega model and accompanying dataset available to researchers upon request. By sharing the results of this work, the team aims to encourage further discussion and technical innovation around how to counteract neural fake news.

According to Roesner, who co-directs the Allen School’s Security and Privacy Research Laboratory, the team’s approach is a common one in the computer security field: try to determine what adversaries might do and the capabilities they may have, and then develop and test effective defenses. “With recent advances in AI, we should assume that adversaries will develop and use these new capabilities — if they aren’t already,” she explained. “Neural fake news will only get easier and cheaper and better regardless of whether we study it, so Grover is an important step forward in enabling the broader research community to fully understand the threat and to defend the integrity of our public discourse.”

Roesner, Choi and their colleagues believe that models like Grover should be put to practical use in the fight against fake news. Just as sites like YouTube rely on deep neural networks to scan videos and flag those containing illicit content, a platform could employ an ensemble of deep generative models like Grover to analyze text and flag articles that appear to be AI-generated disinformation.

“People want to be able to trust their own eyes when it comes to determining who and what to believe, but it is getting more and more difficult to separate real from fake when it comes to the content we consume online,” Choi said. “As AI becomes more sophisticated, a tool like Grover could be the best defense we have against a proliferation of AI-generated fake news.”

Read the arXiv paper here, and see coverage by TechCrunch, GeekWire, New Scientist, The New York Times, ZDNet, and Futurism. Also check out a previous project by members of the Grover team analyzing the language of fake news and political fact checking here.

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Bottomline, a startup co-founded by students in the Allen School and Foster School of Business at the University of Washington, earned third place at the recent Dempsey Startup Competition hosted by the UW Foster School’s Buerk Center for Entrepreneurship. The company provides data analytics that empowers job candidates and employers in the technology sector to evaluate the value and competitiveness of multiple job offers. Bottomline was co-founded by Allen School seniors Lukas Joswiak and Mitali Palekar, sophomore Adam Towers, professional master’s student Elton Carr, and Mayank Maheshwari and Jeremy Peronto of the Foster School’s evening MBA program.

Working under the motto “no two offers are created equally,” the team behind Bottomline focused on bringing more transparency and equity to technology recruitment and compensation practices. To that end, they developed a service that breaks down the various components of complex job offers to enable candidates to compare their relative value. The resulting “bottom line” for each offer accounts for variables that contribute to a candidate’s overall compensation, including base salary, stock options, bonuses, benefits, and more. Candidates can adjust the comparison to account for external factors, such as regional cost of living and local taxes, to understand how these will affect their take-home pay.

The same data that helps individual candidates to assess the value of each offer received can also be used by recruiters, hiring managers, and businesses interested in analyzing how their company’s compensation packages measure up to those of their peers. With the help of Bottomline, employers are able to gauge how their offers compare to the rest of the industry and stay abreast of compensation trends to ensure they remain competitive in the quest for talent. The service is also useful for ensuring that companies are offering fair and equitable compensation across their workforce.

“Given the increasing focus on hiring, promotion and compensation practices across the tech industry, the concept behind Bottomline couldn’t be more timely,” noted Allen School professor Ed Lazowska. “Not only that, but the team executed on that idea in a way that benefits those on both sides of the interview table, bringing more clarity and transparency to what can be a fraught — not to mention opaque — process. It is great to see our students take on this challenge and come up with a service that will not only empower job seekers and inform recruiters, but also encourage equitable practices across the industry as a whole.”

Bottomline grew out of a class project for the Allen School’s entrepreneurship course, CSE 599, taught by Lazowska and Greg Gottesman, Managing Director of Pioneer Square Labs. The course, which is open to students in the Allen School, Foster School MBA program, Human-Centered Design & Engineering master’s program, and Interaction Design program, provides a hands-on, team-based experience in what it takes to build a company, from startup to exit. Along the way, students learn how to validate an idea with potential customers, assess potential financing strategies, hone their investor pitch, develop a product as well as a go-to-market and operating plan, and deal with legal issues associated with launching a new business. Those lessons would prove invaluable to the Bottomline founders as they progressed through the competition.

“We would not have been anywhere without this class,” said Palekar, one of Bottomline’s student co-founders who will graduate from the Allen School this month. “Throughout the quarter, we iterated week after week on our idea based on feedback from experienced entrepreneurs, whose insights helped us understand what would and wouldn’t work. Moreover, we received an immense amount of constructive criticism and guidance in terms of our pitch as well as our business models — things that had previously not been our strong suit. We are immensely grateful for this class for giving us the platform to come up with an idea, refine our product, and create a sustainable business over the long term.”

The class instructors were just as impressed with the team’s work ethic and entrepreneurial spirit. “I love this team, it’s just a perfect mix of computer science students and MBAs,” said Gottesman. “The interesting part of the Bottomline story is how entrepreneurial they were as a team. The compensation and offer-analytics idea was not even the first one they worked on in the class — they killed an earlier project based on customer feedback and pivoted to this new space, because several of the team members had direct experience comparing multiple offers. They then executed on the product like rabid dogs.”

The Dempsey Startup Competition, formerly known as the Business Plan Competition, attracted a total of 113 submissions from teams at 16 schools across the Pacific Northwest and British Columbia. Bottomline advanced through the first stage of competition in April, when it was among 36 teams chosen to compete for a “sweet 16” spot and earn a shot at being among the finalists last month. The students’ third-place finish was the highest of any UW competitor, earning them the “Friends of the Dempsey Startup” Prize and a check for $7,500. Brennan Colberg, a sophomore in the Allen School, contributed to the team in the early stages of the competition.

Read the Buerk Center for Entrepreneurship’s announcement here, and a related GeekWire article here. Learn more about the Dempsey Startup Competition here.

Congratulations to the whole team!

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The following post was authored by Richard E. Ladner, Professor Emeritus at the Allen School and Principal Investigator of AccessComputing

Five students from the Allen School joined a group of 25 students from seven different universities who traveled to Silicon Valley last month to participate in the Teach Access program Study Away Silicon Valley (SASV). I led the group from the University of Washington and served as one of six faculty mentors for the small group projects that participating students completed during the five days of SASV. The students visited the accessibility teams at Walmart, Google, Microsoft, Apple, Verizon Media Group (Yahoo!), and Facebook, where they learned how each of these companies are making their products and services more accessible and usable.

The delegation included Allen School Ph.D. students Venkatesh Potluri and Ather Sharif, fifth-year masters student Nicole Riley, and undergraduates Lucy Jiang and Bryan Lim. In addition to the goal of increasing their knowledge of accessibility practices, these students plan to help the Allen School to improve its curriculum to include more about accessibility-related technologies and practices that these companies are looking for in the people they hire.  

Ather observed that SASV will be helpful for his research. “SASV was a truly remarkable experience. It was fascinating to learn about the efforts and initiatives put forward by the tech companies to improve accessibility in their organizations and products. This knowledge will help me tremendously in my research in not only finding the right problem to target but also targeting it with a pragmatic approach.”

Venkatesh also anticipates that what he learned at SASV will benefit his research. “As a graduate student with research focused in accessibility, it was invaluable to understand the different approaches the industry had towards accessibility. I hope to use these insights from the Study Away as inspiration to solve meaningful accessibility gaps.”

As Bryan noted, there is a gap between what new employees know about accessibility coming into these companies, compared to what they need to know to be effective employees. “Being a part of SASV made me realize the magnitude of the task to make products and services accessible to all. Even more surprising was that almost every company mentioned the existence of a skills gap. New employees consistently had little to no experience with accessibility, and many of the people on their accessibility teams learned on the job. Knowing this, I think that teaching students about accessibility will give them a leg up no matter where they go.”

For her part, Nicole appreciated hearing firsthand about the importance of accessibility to employers and the opportunities available for researchers and technologists who focus in this space. “One thing I learned on the trip was how valuable skills are in accessibility to companies in Silicon Valley. I also learned about the variety of roles available in which you can do accessible work and the diversity of paths to get there, along with new accessible technology that they were developing.”

Lucy also was impressed by each company’s respective commitment to accessibility. “It was so impactful to visit companies like Google, Microsoft, and Facebook and learn about not only their work in accessibility, but their commitment to continual growth and progress. From learning about the importance of universal design, to thinking outside the box and working with a group of people of diverse backgrounds to develop a product idea, I’ll always cherish my newfound friendships with students and faculty from universities across the country. Though this trip was just one week long, I’m inspired to become even more involved in this field — after all, accessibility is our responsibility.”

Next spring, Teach Access is planning another SASV. I am already looking forward to assembling another group of students eager to participate in this enriching learning experience and to incorporate accessibility practices and technologies into their own work. And hopefully we can host a Study Away Puget Sound (SAPS) in the future!

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Allen School undergraduate Asila Maksumova has been selected as the recipient of the 2019 Allen AI Outstanding Engineer Scholarship for Women and Underrepresented Minorities sponsored by the Allen Institute for Artificial Intelligence (AI2). Maksumova, who is majoring in Computer Science, is the second Allen School student to receive the scholarship, which was created by AI2 in 2018 to encourage and support students from underrepresented groups pursuing AI education and careers.

Maksumova is an experienced programmer with a keen interest in artificial intelligence, machine learning, data analytics, and the Internet of Things. During her time at the University of Washington, Maksumova has contributed her talents to the UnderWater Remotely Operated Vehicle Team (UWROV), a group of undergraduate students who design, build, and operate underwater robots. She enjoys mentoring others and has spent the past two quarters as a teaching assistant for the Allen School’s introductory programming course, CSE 142. She is also active in the Sigma Kappa sorority.

Off campus, Maksumova has completed software development internships at General Electric, Kernel Labs, and OSISoft, and spent several months as a researcher at the Northwest National Marine Renewable Energy Center. She begins a new internship at Apple in June.

The Allen AI Outstanding Engineer Scholarship covers full tuition, fees, and textbooks for one academic year. Scholars also have the opportunity to participate in a paid internship working alongside AI2 scientists. In addition to encouraging more diversity in computing, the scholarship program aims to nurture students on the path to a lifelong career. Allen School undergraduate Christine Betts earned the inaugural scholarship last year.

Maksumova was formally recognized at a reception this week featuring remarks from Betts; Allen School alumna Joanna Power (M.S., ‘98), senior software engineer at AI2; and professor Ed Lazowska, Bill & Melinda Gates Chair in Computer Science & Engineering at the Allen School.

Read the AI2 announcement here.

Congratulations, Asila!

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On February 28th, friends and supporters of the Allen School gathered to celebrate the dedication of the new Bill & Melinda Gates Center for Computer Science & Engineering. It was a momentous occasion made possible by the generosity of more than 500 donors, a contribution from Washington state taxpayers…and the careful planning and hard work of nearly two dozen Allen School facilities, operations, and technology support staff responsible for orchestrating the move of people, labs, and equipment into their gleaming new space. Last week, those staff members were formally recognized with the College of Engineering’s 2019 Team Award for having undertaken that monumental — and monumentally successful — assignment.

“To meet the needs of rapidly growing student and faculty populations, the team orchestrated a complex plan to relocate and redistribute the Allen School across two buildings,” the College notes in its award citation. “They demonstrated an exceptional level of organization, efficiency and professionalism to ensure that all faculty, staff and students could access classrooms, laboratories and office spaces from day one.”

The team honored at last Thursday’s award ceremony included the following staff members, all of whom went above and beyond to ensure the Bill & Melinda Gates Center was ready to welcome occupants to their new home:

• Tony Anderson, technology
• Dan Boren, technology
• Nancy Burr, technology
• Joel Cohn, technology
• Adrian Dela Cruz, operations
• Alex Eckerman, technology
• Tracy Erbeck, facilities
• Emma Gebben, technology
• Rebekah Hansen, technology
• Jason Howe, technology
• Alex Lefort, operations
• Mark Murray, technology
• Sophie Ostlund, operations
• John Petersen, technology
• Rod Prieto, technology
• Jan Sanislo, technology
• Stephen Spencer, technology
• Aaron Timss, technology
• Kris Venden, technology
• Fred Videon, technology
• Della Welch, technology
• Voradesh Yenbut, technology

Professors Paul Beame, Associate Director of Facilities for the school, and Ed Lazowska, Associate Director for Development & Outreach, were among the faculty who sang the team’s praises. “We had extremely high expectations for the members of the Move Team based on their prior work in operations and lab support, but executing the move under extremely tight and shifting constraints was truly amazing,” they wrote in support of the team’s nomination. “Their work exemplifies the best qualities of teamwork, planning, and dedication that characterize the staff of the College of Engineering.”

Despite detailed plans that were months — in some cases, years — in the making, the team had to contend with a number of unforeseen circumstances that threatened to throw the move schedule off track. The move was to be done in phases over a period of nearly two months; every step of the way, team members expertly worked around delivery delays, travel schedules, holidays, and even a freak snowstorm that shut down the University to meet their deadlines and ensure that the new building occupants experienced a smooth transition with minimal disruption to their work. This included assisting teams with everything from rolling million-dollar robots across the street to packing up specks of DNA destined for the new wet lab, in addition to coordinating the arrival and proper placement of an entire building’s worth of computers, multimedia displays, furniture, and fixtures.

“The combination of personal commitment and absolute quality focus of the Allen School’s move team turned an enormous challenge into a smooth and successful transition in which occupants of both buildings are incredibly happy,” professor Hank Levy, Director of the Allen School, said. “Their amazing dedication to this task meant that faculty, students, and staff could walk into their new spaces and find them completely ready for occupancy on day one. They have my highest respect for their work.”

Teamwork is the hallmark of the Allen School approach, and it shows; previously, the Allen School’s undergraduate advising team was recognized by the College for providing exceptional service to our growing population of majors, prospective students, parents, and K-12 educators.

Way to go, team!

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In March 2008, Allen School researchers and their collaborators at the University of Massachusetts Amherst and Harvard Medical School revealed the results of a study examining the privacy and security risks of a new generation of implantable medical devices. Equipped with embedded computers and wireless technology, new models of implantable cardiac defibrillators, pacemakers, and other devices were designed to make it easier for physicians to automatically monitor and treat patients’ chronic health conditions while reducing the need for more invasive — and more costly — interventions. But as the researchers discovered, the same capabilities intended to improve patient care might also ease the way for adversarial actions that could compromise patient privacy and safety, including the disclosure of sensitive personal information, denial of service, and unauthorized reprogramming of the device itself.

A paper detailing their findings, which earned the Best Paper Award at the IEEE’s 2008 Symposium on Security and Privacy, sent shock waves through the medical community and opened up an entirely new line of computer security research. Now, just over 10 years later, the team has been recognized for its groundbreaking contribution by the IEEE Computer Society Technical Committee on Security and Privacy with a 2019 Test of Time Award.

“We hope our research is a wake-up call for the industry,” professor Tadayoshi Kohno, co-director of the Allen School’s Security and Privacy Research Laboratory, told UW News when the paper was initially published. “In the 1970s, the Bionic Woman was a dream, but modern technology is making it a reality. People will have sophisticated computers with wireless capabilities in their bodies. Our goal is to make sure those devices are secure, private, safe and effective.”

To that end, Kohno and Allen School graduate student Daniel Halperin (Ph.D., ‘12), worked with professor Kevin Fu, then a faculty member at University of Massachusetts Amherst, and Fu’s students Thomas Heydt-Benjamin, Shane Clark, Benessa Defend, Will Morgan, and Ben Ransford — who would go on to complete a postdoc at the Allen School — in an attempt to expose potential vulnerabilities and offer solutions. The computer scientists teamed up with cardiologist Dr. William Maisel, then-director of the Medical Device Safety Institute at Beth Israel Deaconess Medical Center and a professor at Harvard Medical School. As far as the team was aware, the collaboration represented the first time that anyone had examined implantable medical device technology through the lens of computer security. Their test case was a commercially available implantable cardioverter defibrillator (ICD) that incorporated a programmable pacemaker capable of short-range wireless communication.

The researchers first partially reverse-engineered the device’s wireless communications protocol with the aid of an oscilloscope and a commodity software radio. They then commenced a series of computer security experiments targeting information stored and transmitted by the device as well as the device itself. With the aid of their software radio, the team found that they were able to compromise the security and privacy of the ICD in a variety of ways. As their goal was to understand and address potential risks without enabling an unscrupulous actor to use their work as a guide, they omitted details from their paper that would facilitate such actions outside of a laboratory setting. On a basic level, they discovered that they could trigger identification of the specific device, including its model and serial number. This, in turn, yielded the ability to elicit more detailed data about a hypothetical patient, including name, diagnosis, and other sensitive details stored on the device. From there, the researchers tested a number of scenarios in which they sought to actively interfere with the device, demonstrating the ability to change a patient’s name, reset the clock, run down the battery, and disable therapies that the device was programmed to deliver. They were also able to bypass the safeguards put in place by the manufacturer to prevent the accidental issuance of electrical shocks to the patient’s heart, thereby potentially triggering shocks to induce hypothetical fibrillation after turning off the ICD’s automatic therapies.

The team set out to not only identify potential flaws in implantable medical technology, but also to offer practical solutions that would empower manufacturers, providers, and patients to mitigate the potential risks. The researchers developed prototypes for three categories of defenses that could ostensibly be refined and built into future ICD models. They dubbed these “zero-power defenses,” meaning they did not need to draw power from the device’s battery to function but instead harvested energy from external radio frequency (RF) signals. The first, zero-power notification, provides the patient with an audible warning in the event of a security-sensitive event. To prevent such events in the first place, the researchers also proposed a mechanism for zero-power authentication, which would enable the ICD to verify it is communicating with an authorized programmer. The researchers complemented these defenses with a third offering, zero-power sensible key exchange. This approach enables the patient to physically sense a key exchange to combat unauthorized eavesdropping of their implanted device.

Upon releasing the results of their work, the team took great pains to point out that their goal was was to aid the industry in getting ahead of potential problems; at the time of the study’s release, there had been no reported cases of a patient’s implanted device having been compromised in a security incident. But, as Kohno reflects today, the key to computer security research is anticipating the unintended consequences of new technologies. It is an area in which the University of Washington has often led the way, thanks in part to Kohno and faculty colleague Franziska Roesner, co-director of the Security and Privacy Research Lab. Other areas in which the Allen School team has made important contributions to understanding and mitigating privacy and security risks include motor vehicles, robotics, augmented and virtual reality, DNA sequencing software, and mobile advertising — to name only a few. Those projects often represent a rich vein of interdisciplinary collaboration involving multiple labs and institutions, which has been a hallmark of the lab’s approach.

“This project is an example of the types of work that we do here at UW. Our lab tries to keep its finger on the pulse of emerging and future technologies and conducts rigorous, scientific studies of the security and privacy risks inherent in those technologies before adversaries manifest,” Kohno explained. “In doing so, our work provides a foundation for securing technologies of critical interest and value to society. Our medical device security work is an example of that. To my knowledge, it was the first work to experimentally analyze the computer security properties of a real wireless implantable medical device, and it served as a foundation for the entire medical device security field.”

The research team was formally recognized during the 40th IEEE Symposium on Security and Privacy earlier this week in San Francisco, California. Read the original research paper here, and the 2008 UW News release here. Also see this related story from the University of Michigan, where Fu is currently a faculty member, for more on the Test of Time recognition.

Congratulations to Yoshi, Dan, Ben, and the entire team!

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Researchers in the Allen School and UW Medicine have come up with a novel way to determine whether children may be suffering from an ear infection with the help of a smartphone and a piece of paper. In a paper published last week in the journal Science Translational Medicine, the team presents a new app that can detect the presence of fluid behind a child’s eardrum — a telltale sign of infection — anytime, anywhere in a matter of seconds using a smartphone’s microphone and speaker.

It’s a development that is sure to be music to parents’ ears. And given that the software can be used on virtually any smartphone without the need for specialized equipment, the app’s potential should resonate with providers, as well.

“Designing an accurate screening tool on something as ubiquitous as a smartphone can be game changing for parents as well as health care providers in resource-limited regions,” professor Shyam Gollakota, director of the Allen School’s Networks & Mobile Systems Laboratory, said in a UW News release. “A key advantage of our technology is that it does not require any additional hardware other than a piece of paper and a software app running on the smartphone.”

As Gollakota and his co-authors point out, acute otitis media (AOM) — the condition commonly referred to as an “ear infection” — is a leading cause of pediatric healthcare visits. Fluid in the ear can indicate a child has AOM or otitis media with effusion (OME), a condition in which fluid is present without an acute infection. The latter affects up to 80 percent of children and increases their chances of developing AOM in addition to other complications. Current methods for determining the presence of middle ear fluid, such as pneumatic otoscopy, require a visit to the doctor’s office, but is used by less than one-third of providers; tympanometry requires a referral to an audiologist and relies on expensive, specialized equipment.

For a more convenient — and less costly — solution, the UW team applied the concept of acoustic reflectometry to build a smartphone app that detects the presence of fluid by tapping into the eardrum’s response to sound waves. The researchers take advantage of the co-located microphone and speaker configuration already built into widely available smartphone models to provide a mobile software-based solution, thus negating the need for a separate device. To initiate the test, a user takes a simple, do-it-yourself paper funnel cut from a pattern and affixes it to the smartphone’s speaker. The funnel is placed at the entrance to the outer ear, enabling the phone to emit a series of soft, bird-like chirping sounds into the ear canal. The sound waves from the chirps cause the eardrum to vibrate to varying degrees, depending on whether fluid is present. Those vibrations are then reflected back to the app, which measures the resulting interference with the chirps.

The vibration of a normal eardrum generates a broad-spectrum, soft echo. The presence of fluid, however, restricts the vibration of the eardrum, reflecting sound waves back along the ear canal in a manner that creates more destructive interference. By measuring this interference, the app alerts the user whether fluid — and potentially, infection — is present inside the ear. As Allen School Ph.D. student Justin Chan, co-lead author of the paper, explained, the concept is similar to the different tone one gets from tapping a drinking glass. “Depending on how much liquid is in it, you get different sounds,” he noted. “Using machine learning on these sounds, we can detect the presence of liquid.”

Gollakota and Chan worked with Allen School Ph.D. student Rajalakshmi Nandakumar and physicians Sharat Raju and Randall Bly of UW Medicine on the project. The researchers trained the algorithm that powers their app with data collected from 53 children undergoing surgery at Seattle Children’s Hospital, where Bly practices, with parental consent. Nearly half of the patients, who ranged from 18 months to 17 years of age, were scheduled for a myringotomy, a common procedure to address recurring ear infections in which a small, plastic tube is inserted into the eardrum to prevent a future build-up of fluid in the middle ear. The other patients were undergoing procedures for conditions unrelated to the ear and showed no signs of having middle ear fluid. Each of the 98 patient ears tested with the smartphone app were also tested using a commercially available acoustic reflectometry device for comparison.

The team demonstrated the app could correctly identify the presence or absence of fluid 85 percent of the time, a rate of accuracy comparable to that of standard methods. The researchers also showed that, with minimal training, parents and caregivers can perform the test on any smartphone with a DIY funnel made out of any type of paper — proving that their new app offers a sound approach for screening at home or on the go.

“The medical community has recognized the need for a more efficient yet reliable screening for middle ear fluid in children,” noted Gollakota. “The community also called for new strategies for monitoring fluid at home following a physician’s exam. Our app provides a way to do both, helping to speed diagnosis and improve patient outcomes for two of the most common pediatric ear diseases.”

Gollakota and his collaborators will commercialize their work through a new UW spinout company, Edus Health, with the goal of putting the app in the hands of parents and providers around the world.

Read the journal paper here, UW News release here, and National Science Foundation release here. Check out coverage by NPR, Associated Press, US News & World Report, CNBC, GeekWire, STAT News, New Scientist, Gizmodo, Digital Trends, New Atlas, MobiHealth News, and Mental Floss.

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Richard Ladner, professor emeritus of the Allen School and a recognized leader in accessible technology research and advocacy, accepted the Harrold and Notkin Research and Graduate Mentoring Award this week from the National Center for Women & Information Technology (NCWIT). The award, which recognizes faculty who combine outstanding research contributions with excellence in mentoring the next generation of researchers while promoting diversity in the field, is named in memory of the late Georgia Tech professor Mary Jean Harrold and Allen School professor David Notkin, who served as chair of what was then the University of Washington Department of Computer Science & Engineering from 2001 to 2006. Both Harrold and Notkin passed away after battles with cancer in 2013.

“Mary Jean and David were guiding lights when it comes to prioritizing student mentorship and diversity alongside technical excellence,” Ladner said. “The connection between this award and my good friend and colleague makes this recognition particularly meaningful. It is humbling to be recognized in this way by my peers in the computing community.”

Of the 30 students Ladner has advised or co-advised on their way to earning their Ph.D., 43 percent are women. One of those former students, Cornell Tech professor Shiri Azenkot (Ph.D., ‘14), credits Ladner with providing a supportive environment for people of all genders. “I would look forward to our research group meetings, in which all the students (Ph.D. and undergraduate) and collaborating faculty members would come together to discuss their current research,” Azenkot told NCWIT. “Our group included at least 80 percent women (sometimes more), and our meetings offered a relaxed and friendly place to discuss research and other activities.”

A strong proponent of gender diversity throughout his career, Ladner has also made it his mission to ensure that ensuring access for people with disabilities is part of every conversation about diversity and inclusion in the computing field. While he devoted the first three decades of his faculty career to theoretical computer science  — and made fundamental contributions to complexity theory, parallel computing, and more during that time — Ladner came to the realization that accessibility, not just algorithms, was one of his true passions as both a researcher and a leader. His shift in focus played a significant role in UW’s emergence as a center of accessible technology education and research, and helped expand how his own field thinks about diversity.

“Part of my job as an accessibility researcher is to change people’s mindset about disability,” Ladner explained in a 2017 article looking back on his career. “It presents challenges, yes, but it’s not necessarily a tragedy. It is part of the diversity of life. Our role as researchers and technologists is to embrace this diversity and make sure we reflect that in our work.”

Ladner’s commitment to mentorship has extended to the undergraduate level, where he has advised more than 100 students engaged in research. As his Allen School colleague, Ed Lazowska, attests, that commitment has extended beyond his own program, as Ladner often has tapped into his vast network of colleagues and friends to offer students outside the UW a path into research. “Richard has personally helped place 50 students with disabilities in undergraduate research internships around the nation since 2011,” Lazowska noted. “In the placement process, he phoned each student to try to understand their scholarly interests and abilities, to help find a suitable mentor the student’s summer research experience.”

Ladner has also championed a number of initiatives to engage more students with disabilities in computer science education and careers, including breaking down barriers at the K-12 level. Earlier this year, Code.org and the Computer Science Teachers Association named Ladner a Computer Science Champion in recognition of his work on AccessCSForAll, an initiative that provides curriculum and professional development tools to help teachers in making computer science accessible to students with disabilities in their high school classrooms. AccessCSForAll was an outgrowth of his leadership of AccessComputing, a program Ladner co-founded with frequent collaborator Sheryl Burgstahler, Director of the UW’s Do-IT Center, to increase the participation of people with disabilities in postsecondary computing education and careers by offering resources, mentoring, funding, and networking opportunities. Previously, Ladner led the Summer Academy for Advancing Deaf and Hard of Hearing in Computing, which provided deaf and hard of hearing students from around the country the opportunity to take computing courses for credit and connect with industry professionals who were themselves deaf or hard of hearing.

Ladner collected the Harrold and Notkin Award at NCWIT’s 2019 Summit on Women and IT that took place this week in Nashville, Tennessee. The award is the latest in an impressive list of accolades honoring his leadership in accessibility education, research, and advocacy, including the Richard A. Tapia Achievement Award, the Strache Leadership Award, the SIGACCESS Award for Outstanding Contributions to Computing and Accessibility, the SIGCHI Social Impact Award, the Broadening Participation in Computing Community Award, the Computing Research Association’s A. Nico Habermann Award, and the Presidential Award for Excellence in Science, Mathematics & Engineering Mentoring.

Read the NCWIT announcement here, and learn more about the Harrold and Notkin Award here.

Congratulations, Richard!

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Nine Allen School students were recently honored for excellence in computing-related research by the National Science Foundation as part of the agency’s 2019 Graduate Research Fellowship competition. The NSF Graduate Research Fellowship Program — the oldest fellowship program of its kind — recognizes and supports outstanding graduate students pursuing research in designated science, technology, engineering, and mathematics disciplines. The goal of the GRFP is to assist recipients in becoming lifelong leaders who will contribute to science and engineering education and innovation while advancing the nation’s technological infrastructure, security, and societal well-being.

Over the past five years, the NSF has recognized 46 Allen School student researchers for excellence in the “Computer and Information Science and Engineering” category through the GRFP competition. Read on to discover how the 2019 honorees are helping to shape the future of computing through their work in artificial intelligence, machine learning, natural language processing, computational biology, robotics, security and privacy, ubiquitous computing, and theoretical computer science.

Christine Chen, security and privacy

Fellowship winner Christine Chen is a Ph.D. student in her second year at the Allen School working with professor Franziska Roesner in the Security and Privacy Research Laboratory.

Chen’s research interests lie at the intersection of technology and crime, physical safety, and at-risk populations. Her recent work has focused on technology and survivors of human trafficking. Chen just wrapped up a study in which she interviewed victim service providers (VSPs) to expose how technology can be utilized to re-victimize survivors of trafficking and understand how VSPs mitigate these risks as they interact with and support survivors. As a result of this work, Chen and her collaborators propose privacy and security guidelines for technologists who wish to partner with VSPs to support and empower trafficking survivors. The study will be presented at the upcoming USENIX Security Symposium in August.

Benjamin Lee, artificial intelligence

First-year Ph.D. student Benjamin Lee won a fellowship for his work with professor Daniel Weld in the Allen School’s Artificial Intelligence research group.

Lee’s research spans explainable artificial intelligence and human-AI collaboration. He is particularly interested in the development of explainable, interactive recommender systems that will impart greater understanding and control to users, given that current systems tend to be opaque and offer only limited explanation for why they issued a particular result. To that end, Lee and Weld have partnered with the Semantic Scholar team at the Allen Institute for Artificial Intelligence (AI2) to examine explainable AI in the context of research paper recommendations issued by academic search engines. As part of this project, Lee and his collaborators are exploring how enabling users to act on explanations via more granular up-and-down ratings and natural language feedback could improve the relevance and quality of recommendation results.

Nelson Liu, natural language processing

Undergraduate Nelson Liu earned a fellowship for his work to improve the generalizability and robustness of natural language processing systems with professor Noah Smith of the Allen School’s Natural Language Processing group.

In a recent project undertaken with Smith, research scientists Matt Gardner and Matthew E. Peters of AI2, and Harvard SEAS/MIT CSAIL postdoc Yonatan Belinkov, Liu and Smith examined the linguistic knowledge implicitly encoded within contextualized word vectors by assessing their ability to predict a broad range of linguistic features of their input text. In other work with Smith and former Allen School postdoc Roy Schwartz of AI2, Liu proposes a new approach for characterizing the lack of robustness in NLP methods — a first step towards disentangling failures of models from deficiencies within their training datasets. Liu and his collaborators will present papers on both projects at the upcoming conference of the North American chapter of the Association for Computational Linguistics (NAACL 2019). Liu will continue his research as a Ph.D. student at Stanford University this fall.

Sherdil Niyaz, robotics

Sherdil Niyaz, a second-year Ph.D. student in the Personal Robotics Laboratory, received a fellowship to support his work on motion planning with Allen School professor Siddhartha Srinivasa.

Niyaz is interested in designing graph-based motion planning algorithms for robots deployed in highly challenging and constrained environments, particularly in surgical and manufacturing scenarios. His current work focuses on interleaving these algorithms with gradient-free optimizers to improve the setups of difficult motion planning problems. He is also a strong believer in public education and intends to become a teaching professor after completing his degree. Niyaz previously earned an Honorable Mention in the NSF GRFP competition while an undergraduate student at the University of California, Berkeley.

Nicholas Nuechterlein, machine learning

Ph.D. student Nicholas Nuechterlein earned a fellowship for his research at the intersection of machine learning and medicine with Allen School professor Linda Shapiro and professor Tara Madhyastha of the UW Radiology Department.

Nuechterlein develops ML models for analyzing medical resonance imaging (MRI) and genomic data to improve outcomes for patients with glioblastoma multiforme (GBM), an aggressive form of brain cancer. Current ML methods tend to be ineffective when faced with the high-dimensional, heterogeneous, and incomplete data sets typically associated with GBM. Nuechterlein has developed an automatic segmentation algorithm to scale the analysis of GBM patient datasets containing advanced MRI sequences capable of shedding light on the tumor microenvironment. His goal is to develop an interpretable ML classifier able to distinguish between true progression of GBM tumors, which require immediate, aggressive changes in treatment, and pseudoprogression, which indicates the current treatment is effective. The results of this work will prevent patients from undergoing unnecessary surgeries and could be extended across other medical imaging domains to improve the standard of care.

Ewin Tang, theoretical computer science

Fellowship winner Ewin Tang is a first-year Ph.D. student working with professor James Lee in the Allen School’s Theory of Computation group.

Tang explores the capabilities of “quantum-inspired” classical sublinear-time sampling algorithms to understand where quantum machine learning can and cannot revolutionize data analysis and machine learning practice. She was previously recognized among Forbes’ “30 Under 30” in science for developing an algorithm enabling a classical computer to solve the “recommendation problem” in roughly the same time that a quantum computer can, exponentially faster than previous algorithms. Tang is also interested in extension complexity, a line of research in which she and Lee aim to prove that certain problems are hard for the linear systems solvers and SDP solvers frequently used in practice.

Matthew Whitehill, ubiquitous computing

First-year Ph.D. student Matthew Whitehill earned a fellowship for his work with professor Shwetak Patel in the Allen School’s UbiComp Lab.

Whitehill’s research involves the development of novel sensing systems that leverage creative approaches to signal processing and machine learning, with a particular interest in systems having applications in health and wellness. For example, two of Whitehill’s current projects involve using sound as the sensing medium to better track patient’s pulmonary health. One project involves the use of a deep neural network to identify users by their cough, while the other determines a user’s deviation from their baseline lung functionality based on their speech. In the future, Whitehill hopes to apply his expertise to improving disease diagnosis and monitoring in the developing world.

Erin Wilson, computational biology

Fellowship winner Erin Wilson is a second-year Ph.D. student working in Computational and Synthetic Biology with professors Georg Seelig of the Allen School and Department of Electrical & Computer Engineering, Mary Lidstrom of Microbiology and Chemical Engineering, and David Beck of Chemical Engineering and the eScience Institute.

Wilson’s research spans the intersection of genetics, data science, and sustainability. Her work is largely inspired by her previous experience at biotech companies Amyris and Zymergen, who engineer microorganisms such as yeast and bacteria into tiny, biological factories that can sustainably produce everyday molecules. This is accomplished by editing the microorganisms’ genomes to convert renewable feedstocks (sugar) or waste streams (methane) into a new desired target molecule such as medicine, biofuel, or other molecules found in nature. Wilson’s current research focuses on applying computational methods to better understand the “genetic grammar” underlying how these microorganisms control gene expression and use these insights to more efficiently engineer them for sustainable molecule production.

Peter West, natural language processing

Second-year Ph.D. student Peter West received an honorable mention from NSF in recognition of his research in NLP, particularly where it intersects with questions of cognition, information theory, and machine learning.

West works with Allen School professor Yejin Choi in the xlab, where he aims to answer fundamental questions about how statistical models relate to language and cognition. For his current project, he applies concepts from information theory to summarize sentences unsupervised, without requiring human-written examples. West, whose work is funded by a postgraduate fellowship from Canada’s Natural Sciences & Engineering Research Council (NSERC), has previously conducted research on microfluidic sensors, computational biology, auction simulation, and synthetic biology — experience which continues to shape his approach to his latest research.

Two recent Allen School bachelor’s alumni — Emily Allaway (B.S., ’18) and Ryan Benmalek (B.S., ’17) — were also recognized as part of this year’s NSF GRFP competition. Allaway, currently a graduate student at Columbia University, earned a fellowship for her research in NLP. As an undergraduate, Allaway worked with professor Yejin Choi and graduate students Hannah Rashkin and Maarten Sap of the Allen School’s NLP research group. Benmalek, a second-year graduate student at Cornell University, received a fellowship for his work encompassing computer vision and NLP. During his time at the University of Washington, Benmalek worked with Choi and Allen School professor Ali Farhadi. In addition to the Allen School recipients, Ph.D. student Jenna Register of the UW’s Information School earned a fellowship for her work in human-computer interaction.

Congratulations to all of this year’s honorees!

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