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Groundbreaking study that served as the foundation for securing implantable medical devices earns IEEE Test of Time Award

Members of the team that examined the privacy and security risks of implantable medical devices in 2008. UW News Office

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.”

Chest x-ray showing an implanted cardioverter defibrillator (ICD).

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.

Equipment used in the 2008 study to test the security of a commercially available ICD.

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.

Professor Tadayoshi Kohno (left) and Daniel Halperin

“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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Have you heard? UW researchers developed a new smartphone app that screens for ear infections in children

Dr. Randall Bly checks his daughter’s ear for fluid using a new smartphone app and paper funnel. Dennis Wise/University of Washington

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.

The app offers instructions for assembling a paper funnel to use with the app. Dennis Wise/UW

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.”

Co-lead authors Dr. Sharat Raju (left) and Allen School Ph.D. student Justin Chan. Dennis Wise/UW

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.

Allen School professor Shyam Gollakota (left) and Ph.D. student Rajalakshmi Nandakumar. Mark Stone/UW

“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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Allen School’s Richard Ladner honored with 2019 Harrold and Notkin Research and Graduate Mentoring Award

Left to right: Emma Notkin, Richard Ladner, and Cathy Tuttle smiling with trees and campus buildings in background
Ladner (center) with late friend and colleague David Notkin’s daughter, Emma (left), and widow Cathy Tuttle (not pictured: son Akiva).

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.”

Harrold and Notkin Research and Graduate Mentoring Award certificate recognizing Richard Ladner
The Harrold and Notkin Research and Graduate Mentoring Award recognizes Ladner’s commitment to outstanding research, graduate mentoring, and diversity.

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.”

Richard Ladner seated on a red chair in front of NCWIT poster containing photos of people and line drawings in varying shades of blue and green
Ladner at NCWIT’s 2019 Summit on Women and IT held in Nashville, Tennessee earlier this week.

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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Allen School students recognized for excellence in computing research by the National Science Foundation

NSF GRFP logo in blue and green

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

Christine Chen smiling in front of water with a grassy hill and building in background

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

Benjamin Lee in glasses and red jacket smiling in front of industrial building

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

Nelson Liu smiling

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 Nyaz smiling in glasses and plaid shirt

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

Nicholas Nuechterlein smiling with trees in background

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

Ewin Tang smiling in glasses and a jacket in a building hallway

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

Matthew Whitehill smiling with streetscape in background

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

Erin Wilson in a hat smiling with foliage in background

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

Peter West smiling in a scarf with trees in background

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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Allen School student and “Geek of the Week” Mitali Palekar aims high while elevating the voices of others

When Computer Science major Mitali Palekar graduates next month, she can start a new chapter as a software engineer at LinkedIn knowing that she has made a difference in the community she has called home for the past four years. An accomplished student researcher, mentor and campus leader, Palekar has combined her love of programming and a passion for diversity to elevate the voices of students around her and help build a more welcoming and inclusive community within the field of computing.

A 2019 Husky 100 honoree and former TUNE House scholar, Palekar was most recently featured as GeekWire’s Geek of the Week for her many achievements during her time as a University of Washington student. These include serving as a past president and adviser to the UW chapter of the Society of Women Engineers, peer adviser and mentor for students in the Allen School, College of Engineering, and Interdisciplinary Honors Program, and a research assistant in the Allen School’s Security and Privacy Research Lab. She has also taken multiple opportunities to apply what she has learned through internships at Facebook, LinkedIn, Uber, and Stripe, and as a contributor to Bottomline, a compensation analytics startup that advanced to the Sweet 16 of the regional Dempsey Startup Competition hosted by the UW’s Buerk Center for entrepreneurship.

While she enjoys tackling technical challenges and exploring entrepreneurial opportunities, Palekar is particularly eager to use her position and experience to smooth the way for others. “I hope to play my role in improving representation, inclusion and belonging of underrepresented minorities in technology, ensuring that we continue to hone different sorts of talent and perspectives in tech,” Palekar told GeekWire. “Computer science can be for everyone.”

Palekar goes on to say that she draws inspiration from her parents for their hard work coupled with kindness, and from the “strong, fearless and passionate young women” among her friends, roommates and fellow technologists. They would, no doubt, be eager to return the compliment.

Read the full Geek of the Week feature here, an article about Palekar’s inclusion in the Husky 100 here, and the Allen School’s previous Undergraduate Spotlight on Palekar here.

Congratulations, Mitali!


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Yin Tat Lee receives Microsoft Research Faculty Fellowship

Portrait of Yin Tat Lee wearing glasses, a white dress shirt, and grey and black patterned tie

Professor Yin Tat Lee of the Allen School’s Theory of Computation group has been named a 2019 Microsoft Research Faculty Fellow. Since 2005, Microsoft has used its Faculty Fellowship program to recognize promising, early-career researchers whose exceptional research talent makes them emerging leaders in their fields. Lee, who joined the University of Washington faculty in 2017, is one of only five recipients selected by Microsoft this year from universities and colleges across North America.

Lee was recognized for his research in theoretical algorithms, convex optimization, convex geometry, spectral graph theory, and online algorithms — work that Microsoft Research considers among some of the most exciting areas of computer science research today. “While I devote my energy on theoretical algorithmic research such as how to solve some decades- or even centuries-old problems faster, I am often surprised how much these ideas can be used to solve difficult modern problems,” Lee told the company. “Theoretical computer scientists are like particle physicists, instead of understanding the limits of physics, we understand the limits of computation. Although it looks impractical for outsiders, it often leads to important useful results.”

This focus on advancing the theoretical underpinnings of computation with real-world applications has been a recurring theme in Lee’s early work. Since joining the University of Washington faculty three years ago, Lee has earned earned a Best Paper Award at the Conference on Neural Information Processing Systems (NeurIPS 2018) for presenting new algorithms for achieving optimal convergence rates for optimizing non-smooth convex functions in distributed networks, and a CAREER Award from the National Science Foundation for his work on more efficient algorithms for solving convex and other optimization problems. As part of that project, Lee aims to advance the scientific community’s understanding of the relationship between convex geometry and optimization algorithms and improve upon current optimization techniques, the results of which will have broad impact across the sciences and in many other fields. Last summer, Lee collected the A.W. Tucker Prize from the Mathematical Optimization Society for his Ph.D. thesis exploring how to combine and improve upon existing optimization techniques to produce faster algorithms for solving a range of problems underpinning the theory and practice of computing.

The Faculty Fellowship comes with an unrestricted annual gift of $100,000 for two years to enable recipients like Lee to pursue their breakthrough research. Lee and his fellow honorees were selected as part of a rigorous, multi-tier process based on their pursuit of cutting-edge research, a demonstrated ability to communicate complex concepts, and the skills required to turn their ideas into impact. Past fellowship winners include Allen School faculty members Shwetak Patel (2011), Luis Ceze (2009), and Magdalena Balazinska (2007).

Read the Microsoft Research announcement here, and learn more about the 2019 Fellows here.

Congratulations, Yin Tat!


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Tribute to CSE leader and professor Hellmut Golde

Hellmut Golde smiling in a plaid shirt with the Sylvan Grove columns in the background
Professor emeritus Hellmut Golde in Sylvan Grove in 2003

The Allen School family is mourning the loss of our friend and colleague Hellmut Golde, who passed away earlier this month after a brave battle against cancer. As one of the founding members of the Computer Science Group at the University of Washington and leader of the team that developed the wildly successful VAX Pascal compiler, Golde’s legacy includes the emergence of the Paul G. Allen School of Computer Science & Engineering as an education and research powerhouse and the emergence of the Seattle region as a hub of computing innovation.

Golde, who grew up in Germany, joined the UW faculty in 1959 as a professor in the Department of Electrical Engineering after earning his Ph.D. from Stanford University. He was one of the founders of the Computer Science Group in 1967, the precursor to the Department of Computer Science, formed in 1974, which evolved into the Department of Computer Science & Engineering in 1989 and eventually into the Paul G. Allen School in 2017. In those early days, Golde played a crucial role in establishing the culture for which the Allen School is widely known — one of friendship, support, and community.

A few years after he helped lead the creation of the Computer Science Group, Golde became director of the Computer Science Laboratory, the research and educational facility that hosted a couple of aspiring computer scientists, Paul Allen and Bill Gates, in the days before they set out to put a computer on every desktop. Back then, the pair would sneak into the lab and “borrow” computer time, as Gates would later describe it. Golde would cement his place in campus lore by famously expelling Allen and Gates from the lab.

Image of Hellmut Golde's letter to Paul Allen
“Dear Mr. Allen….”

Delivering his rebuke via a polite yet sternly worded letter, Golde directed Allen to “turn in your keys and terminate your activities” owing to offenses such as “you removed the acoustic coupler from Dr. Hunt’s office without authorization and without leaving at least a note.” At the celebration of the naming of the Allen School more than 40 years later, Allen astonished Golde and the rest of the audience by pulling out the letter and reading it in its entirety as he reminisced about his long-standing affection for UW. Allen subsequently framed two copies of Golde’s letter as mementos for the school and for Golde, while we attempted to make amends for the decades-old rebuke by gifting Allen an acoustic coupler purchased on eBay.

Professor emeritus Richard Ladner, who joined the department in 1971, fondly recounted the ease with which Golde bridged the divide in their academic interests and became not only a colleague but lifelong friend. “Hellmut was one of the first people I met when I interviewed for a faculty position at the University of Washington. We were miles apart in terms our academic interests, me a mathematician and he an electrical engineer,” Ladner recalled. “Nonetheless, we hit it off because of his infectious sense of humor and overall kindness. Some of my fondest memories of days with Hellmut are skiing with him and his family at Alpental, Mount Baker, Stevens Pass, and Big Sky. It was always hard for me to keep up with him on the slopes.”

Golde later stepped in to serve as acting chair of the department from 1976 to 1977. It was a period of transition for our program, and Golde wasn’t given much of a choice in the matter — the first department chair, his dear friend Jerre Noe, had declared himself a sabbatical after coming to the realization that if he didn’t leave town, he might wind up being chair for life. At the time, the department had a grand total of 11 faculty and had graduated 25 students.

Black and white portrait of Hellmut Golde in suit and tie wearing glasses and smiling
Hellmut Golde served as acting chair of UW CSE from 1976 to 1977

As Golde was completing his time as chair, Ed Lazowska arrived to join the UW faculty one week after completing his Ph.D. — and just one week before the start of the school year. His new colleagues tried to reassure him that he didn’t need to worry, because “the course you’ve been assigned has been taught for many years by Hellmut Golde. He’s the best teacher in the department. Ask him for his notes.” Unfortunately for Lazowska, “Hellmut was such a good teacher that those ‘notes’ consisted of a single page, with a single line for each day of the course specifying the topic to be covered that day,” Lazowska laughed. “Let’s just say that my course evaluations were not as good as Hellmut’s had been.”

Although Golde’s time at the helm was short-lived, he had an outsize impact on the program beyond the recruitment of Lazowska and Ladner — each of whom went on to have an outsize impact of their own on the growth of our program and on our emergence as a leader in accessible computing, respectively. In October 1977, Digital Equipment Corporation (DEC) introduced the VAX-11/780 computer, which became the mainstay of many computer science departments and companies nationwide. UW managed to acquire an early VAX on the understanding that Golde and a group of graduate students would write a VAX compiler for the Pascal programming language, which was widely used for introductory programming.

“DEC was willing to give Hellmut a portion of sales for the VAX Pascal compiler because they greatly underestimated the demand for Pascal and the market for the VAX computer in education,” explained Allen School Director Hank Levy, who was a member of DEC’s VAX design and development team at the time. “Partly as a result of the compiler that Hellmut and his team built, the VAX become highly successful in educational institutions, resulting in more than $1 million in royalties flowing from DEC to the department — a not insignificant sum in those days. These funds were crucial in allowing the department to grow during difficult financial times on campus. It was Hellmut’s foresight, technical acumen, and generosity which allowed the department to preserve its momentum — and later, to climb into the ranks of the top 10 computer-science programs in the nation.”

It appears that Hellmut neglected to return a Selectric typewriter that he borrowed in 1976. We trust that UW’s Equipment Inventory Office is on the case!

The VAX-11/780 computer on display in the Allen Center atrium stands as a monument to those days, when this single computer could support the entire department’s computing needs.

As Ladner noted, Golde enjoyed a good joke — even if it came at his own expense. He was particularly amused at people’s inability to reckon with the pronunciation of his German name. “Hellmut used to display on his office door a montage of address labels from letters people sent him on which his name had been butchered,” recalled Lazowska. “He would say ‘Hellmut Golde’ on the phone, and often the person on the other end wouldn’t get it quite right. My personal favorite was the time someone addressed a letter to ‘Hal McGoldy.’”

Always a leader and forever a friend, Hellmut retired from UW as emeritus professor in 1992 but remained actively engaged with his Allen School family. We miss him greatly.

A celebration of Hellmut’s life will be held on Sunday, June 2, 2019 at 2 pm at the Bill & Melinda Gates Center for Computer Science & Engineering at the University of Washington. Please contact Beth Golde (beth at golde.org) for details if needed. Remembrances, in lieu of flowers, may be made to the Hellmut Golde Endowed Scholarship in Computer Science & Engineering at the University of Washington, or the Golde Family Scholarship Fund at Heritage University.

An official obituary may be found here. Photographs of Hellmut through the years may be found here.

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Husky 100 highlights Allen School students making the most of their time at UW

Four Allen School undergraduates are among the 2019 class of the Husky 100, a program that recognizes students from across the University of Washington’s three campuses who are making the most of their Husky Experience — both inside and outside of the classroom. This year’s honorees from the Allen School exemplify a commitment to academic excellence, campus leadership, and service to the community that are the hallmarks of a Husky 100 student.

Caleb Ellington smiles and reaches toward the camera

Caleb Ellington

Caleb Ellington is originally from Austin, Texas but proclaims he “couldn’t be more proud to be a Husky” as he looks to apply his talents at the intersection of biology and computing in developing communities.

After he graduates with degrees in Bioengineering and Computer Science next year, Ellington hopes to build on his past experience as a biomedical engineering ambassador to hospitals across Nepal by helping to develop emergency services in that country. Having completed internships at Boulder, Colorado-based Muse Biotechnology and at Amazon in Seattle during his studies, Ellington is also interested in pursuing entrepreneurial opportunities focused on therapeutics manufacturing.

“I came to UW with a mission to improve health care and medicine using tools available to everyone,” Ellington said.

Alison Ng

Alison Ng smiling with hands in pockets

Alison Ng of Woodinville, Washington will graduate this year with a degree in Computer Engineering. A leader inside the Allen School as well as out, Ng chairs the CSE Student Advisory Council, which represents the undergraduate and master’s student voices within the school, and serves as an officer of the UW chapter of the Society of Women Engineers, an organization that aims to expand educational and career opportunities for women in technical fields.

Ng also represents her fellow students as a member of the Allen School Diversity Committee and serves as a peer adviser helping to guide other CSE majors and prospective students toward academic success. She is currently in her second quarter as a teaching assistant for the Allen School’s Introduction to Digital Design course.

“The University of Washington has provided me with the opportunity to explore my passion for computer engineering and to develop the technical skills necessary to thrive in the industry,” Ng said.

Eugene Oh

Eugene Oh smiling with hands in pockets

Eugene Oh of Federal Way, Washington is pursuing degrees in Computer Science, with a concentration in Data Science, and Social Work.

During his time at UW, Oh has assisted current and prospective CSE majors as a peer adviser and also served as a teaching assistant for the Allen School’s Freshman Direct Admit seminar — in which he focused on the topic of social good — and Computer Science Principles course. When he is not honing his technical skills at a local technology company or as undergraduate research assistant, Oh devotes himself to volunteer service at the Roots Young Adult Shelter and mentoring students at Kent-Meridian High School through the UW Dream Project.

“My time at the UW has taught me to continually push my growing edge in all the spaces that I occupy,” said Oh. “I move forward from the UW hoping to combine my interests in education and technology to work toward empowering the youth of tomorrow.”

Mitali Palekar smiling with hands in pockets

Mitali Palekar

Mitali Palekar will graduate this year with a Computer Science degree with Interdisciplinary Honors. Palekar, who hails from Cupertino, California, describes her Husky Experience as one of transformation from “naive freshman” into an engineer, leader, and advocate.

In addition to serving as an Allen School peer adviser helping her fellow students navigate their own Husky Experience, she has been active in the UW chapter of the Society of Women Engineers as a senior adviser and past president. Palekar has also taken the opportunity to apply her technical skills as an undergraduate research assistant in the Allen School’s Security and Privacy Research Lab and through internships with multiple technology companies in Seattle and Silicon Valley.

“I have developed a passion for building products and communities that uplift the voices of people around me,” Palekar said.

“Through the Husky Experience, students discover their passions in life and work,” said UW Provost Mark Richards. “They become independent thinkers and leaders. They gain the skills they need to prepare for rewarding careers in industry, community and in life. That’s exactly what each of these 100 students is doing.”

This is the fourth year the UW has recognized students through the Husky 100 program. Past honorees from the Allen School include 2018 recipients Amanda Chalfant, Aishwarya Mandyam, Melissa Medsker (Galloway), and Kimberly Ruth; 2017 recipients Camille Birch and Kelsie Haakenson; and 2016 recipients Krittika D’Silva, Victor Farkas, Karolina Pyszkiewicz and Sarah Yu.

Congratulations to Caleb, Alison, Eugene, and Mitali on this well-deserved recognition — and thank you for devoting your time and talents to helping your fellow students and the community!


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Kira Goldner earns National Science Foundation postdoctoral fellowship

Allen School Ph.D. candidate Kira Goldner has received a Mathematical Sciences Postdoctoral Research Fellowship from the National Science Foundation to advance her work on algorithmic mechanism design for social good. Goldner, who works with professor Anna Karlin in the Allen School’s Theory of Computation group, will take up a postdoc position hosted by professor Tim Roughgarden at Columbia University following her graduation from the University of Washington this spring.

Throughout her studies, Goldner has often focused on theoretical problems that have real-world applications across multiple domains. She launched her research career by focusing on revenue maximization within mechanism design. In one high-profile project, Goldner tackled the so-called FedEx Problem, which deals with determining how to sell a variety of shipping options in order to maximize revenue for FedEx while meeting the expectations on the part of the customer in terms of service quality and cost. The Fedex Problem is a fundamental one that has implications in multiple market sectors, from shipping, to internet service, to cloud computing. Goldner and her collaborators designed the optimal revenue-maximizing auction for situations in which prior information on consumer values are known, contributing new algorithmic techniques and a greater understanding of mechanism design beyond single-parameter settings.

With algorithms playing an increasingly prominent role in systems that impact people’s day-to-day lives, Goldner became interested in algorithmic mechanism design for social good. She is particularly keen to explore how the techniques she honed on classic theoretical problems can be applied in domains such as health care and labor markets to maximize outcomes for both society and individuals — despite participants acting in their own self-interest. Such systems have tangible, sometimes high-stakes effects on people’s physical well-being and economic prospects, as well as on the welfare of society as a whole, via the allocation of resources, the setting of policies, and the regulation of activities to achieve certain outcomes. For instance, the goal of a health care system would be to align providers’ incentives with the dual (and sometimes dueling) goals of minimizing costs while maximizing patient health. Online job recruiting systems should be geared toward identifying optimal employer-employee matches while mitigating discriminatory hiring practices. Goldner aims to bring mathematical formality to these and other pressing social issues, applying her expertise in algorithmic mechanism design and game theory to develop new theoretical approaches for meeting objectives that are motivated by the social good.

To this end, Goldner has also been sharing her vision with the research community. In the fall of 2016, she co-founded the Mechanism Design for Social Good (MD4SG) initiative. That effort spawned a collection of events that Goldner also has co-organized — including an annual workshop, an online research group, and more — and inspired industry-funded grants on the topic. In December 2017, she delivered an invited tutorial on mechanism design for social good at the Conference on Web and Internet Economics.

“Since her arrival at the Allen School, Kira has done outstanding research, for example, studying problems like the FedEx Problem that are helping to advance our understanding of theoretical principles with real-world implications. She is currently tackling problems in health care and labor markets using the tools of algorithmic mechanism design; here the work has the potential to contribute directly to the well-being of society,” said Karlin. “Kira has repeatedly demonstrated outstanding technical expertise in tackling very interesting — and difficult — problems. Other qualities that particularly stand out are her creativity and vision in defining new and interesting research questions and the enthusiasm and thoughtfulness with which she questions standard assumptions.”

Goldner previously was recognized for her work with a Microsoft Research Ph.D. Fellowship and a Google Anita Borg Scholarship. She also was named a finalist for the Facebook Fellowship and earned two Honorable Mentions in the annual NSF Graduate Research Fellowship competition.

Congratulations, Kira!


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UW and Microsoft researchers demonstrate digital microfluidics automation for scaling DNA data storage

Closeup of the PurpleDrop digital microfluidics device
Researchers in the Molecular Information Systems Laboratory are exploring new capabilities in digital microfluidics, programming, and automation to advance DNA data storage

For the past three years, researchers in the Molecular Information Systems Laboratory (MISL) have been on a mission to store the world’s digital data in DNA. A partnership between the University of Washington and Microsoft, the lab has already sparked the imagination of artists, archivists, scientists, and the public with its vision to move beyond traditional data storage media, inspired by the very building blocks of life — what Allen School professor Luis Ceze refers to as “nature’s own perfected storage medium.”

The members of MISL have worked with DNA synthesis company Twist Bioscience to preserve a range of artifacts, from iconic recordings of the Montreux Jazz Festival, to the Universal Declaration of Human Rights, to your neighbor’s favorite cat photo. Along the way, they used these projects to practice encoding and decoding snippets of digital data in synthetic DNA and demonstrate new capabilities for random access and content-based search. They even revealed plans to launch a DNA-based archive into space next year as part of Arch Mission’s Lunar Library, a unique challenge that will compel the researchers to find a way to protect their precious cargo in the harshest of environments for the sake of posterity.

Now the team, co-led by Ceze and Microsoft Principal Researcher Karin Strauss, is ramping up the innovation — and the scientific “wow” factor — with a series of new projects that have opened up exciting new avenues for exploration at the intersection of biology and computer science. One of those projects, described in detail in a new paper published in the journal Nature Communications last week, may be the clearest indicator yet that a DNA-based storage system is not only an intriguing option for solving the world’s data crunch, but also a practical one.

“Once we outlined a DNA storage system, we began contemplating the practical considerations,” said Strauss, who is also an affiliate professor in the Allen School. “The first milestone was figuring out random access within a single pool of DNA molecules mixed together, to retrieve only the data we want and avoid the time and expense of sequencing what we don’t. Our next challenge was to figure out how to take full advantage of DNA’s incredible density and resiliency while automating as many stages of the process as possible. Our latest step shows how to physically organize multiple DNA pools and retrieve them with liquid droplets controlled digitally.”

Members of the MISL team pose for a group photo
Members of the Molecular Information Systems Laboratory

In their latest paper, Strauss and her colleagues presented a system for achieving high-density data storage in synthetic DNA. By “high-density” they mean one full terabyte of data — the equivalent of 1,000 gigabytes — in a single spot of dehydrated DNA one millimeter in diameter, or roughly the size of a pinhead. Although the information density of DNA molecules is theoretically much higher than that, the team wanted to ensure the ability to retrieve specific data from a particular pool without having to sequence the entire pool.

The team arranged the spots of DNA on glass cartridges, with each cartridge capable of storing up to 50 terabytes based on current DNA storage techniques. Multiple glass cartridges can then be stacked in a space-saving vertical configuration — akin to the approach taken with existing magnetic tape or hard drive-based storage systems to conserve room, albeit much more compact.

“DNA must be in liquid form for sample preparation and sequencing, but isolating liquid samples can be a cumbersome process and requires separate vessels — which would sacrifice a significant amount of density,” explained lead author Sharon Newman, an alumna of UW Bioengineering who is currently pursuing a Ph.D. at Stanford University. “Our dry storage architecture enables us to store data with much higher density compared to other approaches, and allows for physical isolation and data retrieval without risking contamination from other samples.”

To retrieve the data, the researchers rehydrate the DNA with a droplet of water using a digital microfluidics (DMF) device. Newman and her colleagues took a keen interest in DMF technology, which is capable of manipulating liquids in very small quantities with higher precision than humans. By automating biological and chemical protocols with DMF, researchers can scale up the processes involved in implementing DNA data storage. The devices are particularly suited to DNA storage processing, but they have their limitations: not only do DMF platforms tend to be prohibitively expensive, but they are also inflexible, error-prone, and difficult to program.

Luis Ceze (left) examines an early prototype of PurpleDrop with Karin Strauss (center) and Sharon Newman

Recognizing that DNA data storage would remain a pipe dream as long as the combination of cost and complexity made it inaccessible to all but a handful of experts in resource-rich laboratories, a group of MISL researchers developed a low-cost, general-purpose DMF device for holding and manipulating the droplets of DNA, which they dubbed PurpleDrop, and a full-stack DMF automation platform known as Puddle. Together, the projects — which the team will present at the Association for Computing Machinery’s 24th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2019) this week — comprise a complete DMF programming system that will make microfluidic technology more accessible while simultaneously expanding its computational capabilities.

“Most of the work on microfluidics has focused on automating individual protocols, in which the device is given a fixed set of inputs, and manipulates them in a specified way to produce an output,” explained Allen School Ph.D. student Max Willsey. “Although this is an important component of wet-lab research, it limits the role of DMF to that of a microcontroller. We envision a more expansive and dynamic system that enables scientists to program complex protocols in Python or another language of choice while providing real-time error correction.”

Puddle’s dynamic approach to resource management sets it apart from existing techniques, which take a more static approach to microfluidic programming. Puddle is an application programming interface (API) that  purposefully maximizes expressiveness and ease of use, in exchange for sacrificing some efficiency and ahead-of-time guarantees. This trade-off gives Puddle more flexibility, allowing both the system and the user to react to data from the fluidic domain. These data-driven decisions fall into three categories: protocol-level decisions, such as automatic replenishment of a liquid that has evaporated during an experiment; application-level decisions based on the protocol output, such as what experiment to run next; and execution-level decisions, such as error detection and correction. To enable the latter, the team employed computer vision and a small camera mounted on top of the DMF device. The camera functions as a multi-purpose sensor for detecting the location and volume of droplets to help Puddle decide if an error has occurred.

Members of the microfluidics research team, left to right: Bichlien Nguyen, Max Willsey, Ashley Stephenson, and Chris Takahashi

The built-in error detection enables the robust execution of the system on relatively cheap hardware, meaning the researchers could prioritize simplicity and accessibility in designing the PurpleDrop device. In addition to the camera, PurpleDrop features a Raspberry Pi 3B single-board computer, instead of a microcontroller, to drive the electronics, which enables it to function as a self-sufficient microfluidics platform. Costing about$300 assembled — orders of magnitude less than most fluidics systems — the design is also simple enough for many labs to put together on their own, without requiring access to a clean room.

“Cost considerations are one of the main sticking points when it comes to microfluidics,” noted Allen School research scientist and co-author Ashley Stephenson. “So as we look for ways to expand the capabilities, we want to ensure that scientists and practitioners will be able to access these innovations. This work can be used to advance not just DNA data storage but also many other areas of research, such as medicine.”

Because cost and complexity are probably the two biggest barriers to widespread adoption of DNA as a storage medium, it comes as no surprise that automation has emerged as a recurring theme in MISL’s work. Last month, the world said “hello” to the first fully automated, end-to-end system for storing digital data in synthetic DNA. Lab members took those five letters, represented by five bytes of data, and ran them through a fully functioning prototype incorporating the equipment required to encode, synthesize, pool, sequence, and read back the data — the majority of which, like PurpleDrop, was built using inexpensive, off-the-shelf components. And it performed the cycle without human intervention, which as senior research scientist Chris Takahashi pointed out, will be an advantage when it comes to DNA data storage in the wild.

“You can’t have a bunch of people running around a data center with pipettes,” pointed out Takahashi, lead author of a related paper published in Nature Scientific Reports. “It’s too prone to human error, too costly, and the footprint would be too large.”

The MISL team developed the first automated, end-to-end system for DNA data storage

Takahashi and his colleagues did not set out to demonstrate speed or even affordability at this stage; rather, they built the machine to show that end-to-end automation was possible. The team’s ultimate goal is to develop a system that resembles any other cloud-based storage service, to which end users would be able to upload their data to a storage center. The difference is, instead of staying in digital form, a customer’s data would be converted to the As, Ts, Cs, and Gs of DNA until it is needed again.

“We are developing an entirely new way of storing digital data from scratch, which means building all new hardware, platforms, and techniques,” said Ceze. “There is a lot more to it than solving the technical challenges related to converting those 0s and 1s to DNA molecules, and we have made significant progress in the last three years. With these latest results, we are building a bridge between computation and molecular biology and introducing exciting new capabilities that will benefit both fields.”

The Nature Communications paper on high-density DNA data storage was co-authored by Newman, Stephenson, Willsey, Takahashi, Strauss, Ceze, and Microsoft researcher Bichlien Nguyen.

The ASPLOS paper on Puddle and PurpleDrop was co-authored by Willsey, Stephenson, Takahashi, Nguyen, Newman, Strauss, Ceze, high school intern Pranav Vaid, Allen School master’s students Michal Piszczek and Christine Betts, and Allen School alumnus Sarang Joshi (B.S., ‘18).

The Nature Scientific Reports paper on end-to-end automation of DNA data storage was co-authored by Takahashi, Nguyen, Strauss, and Ceze.

To learn more about the DNA data storage research, visit the MISL website here.

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