Allen School News

Frequent readers of the blog may be familiar with our Undergraduate Spotlight, an occasional feature in which we highlight an Allen School student who represents the next generation of innovators and leaders in the field of computing. For our latest feature, we shine the spotlight on a group of students who are among the first in their families to attend college as part of a nationwide celebration of the contributions that first-generation students make to our campus communities.

Meet Allen School undergraduates Shariya Ali, Simplicio DeLeon, and Dilraj Devgun — three trailblazers who are on their way to academic success.

Shariya Ali

Shariya Ali is a junior majoring in Computer Science at the Allen School, where she serves as a member of the CSE Student Advisory Council representing the voices of undergraduate and master’s students on issues ranging from diversity and social responsibility to student wellness. Ali arrived at UW by way of the San Francisco Bay area, where she was born after her family immigrated to the United States from Suva in the Fiji Islands. As both a mother and full-time college student, she is determined to make the most of her opportunity at the Allen School and looks forward to mentoring other young women and supporting a more diverse and inclusive technology community.

Allen School: What does being a first-generation student mean to you?

Shariya Ali: Being a first-generation student means that I won’t have to struggle to provide for my family like my mom struggled to provide for me. She had to put in so much work and make so many sacrifices to give me a good life, but for most of my childhood that still meant we lived paycheck to paycheck. My mother has since passed away, and graduating from UW will be the best way I can honor her memory.

Allen School: What advice do you have for future first-gen students?

SA: My advice to future first generation students is to stop listening to other people’s opinions about your life. If you have a dream, go for it. It’s your life, and it’s up to you to make it the life you want. If I had listened to everyone about my chances of being admitted to the Allen School, I would have been too scared to move to Seattle and I wouldn’t be here today. Never let your fears dictate your life, and always believe in yourself!

Allen School: What is your favorite part about being an Allen School student?

SA: My favorite part about being an Allen School student is seeing the surprised faces people make when I tell them my major. People have an image in their minds about what software engineers should look like, and I love being an example of someone outside of that mold. I hope I can become an inspiration to other young women and show them they can be whatever they want to be.

Simplicio DeLeon

Simplicio DeLeon is a junior majoring in Computer Engineering at the Allen School. Hailing from Harrah, Washington, DeLeon is an alumnus of the Washington State Academic RedShirt (STARS) program, which helps first-generation students and those from low-income and underserved backgrounds to navigate the transition to college-level engineering and computer-science coursework. DeLeon recently completed an Explorer Internship at Microsoft, where he was a member of the Business Application Platform Team. DeLeon is active in the Society of Hispanic Professional Engineers, the UW Salsa Club, and Husky ADAPT, a program that supports accessible design and play in collaboration with the Allen School’s Taskar Center for Accessible Technology and Mechanical Engineering’s Ability & Innovation Lab.

Allen School: What does being a first-generation student mean to you?

Simplicio DeLeon: To me, being a first-gen student means doing my best in school in order to pay back for all of the sacrifices my parents made for me.

Allen School: What advice do you have for future first-gen students?

SD: Everything might be really new and difficult but hang in there. You are capable and it’ll be worth it.

Allen School: What is your favorite part about being an Allen School student?

SD: My favorite part is being able to explore such a vast field. There are so many opportunities to check out different parts of computer science like the Internet of Things, artificial intelligence, and cloud computing. We have really talented and knowledgeable staff who you can talk to in order to learn more or find ways to explore further. My other favorite part of the Allen School is the people. There are so many different clubs and student groups here that I think everyone should look into. Aside from that, it’s always great to meet people either in classes, in the Allen Center atrium, or in the labs.

Dilraj Devgun

Dilraj Devgun is in his final year at UW, where he is majoring in Computer Science at the Allen School and pursuing a minor in Mathematics. Devgun has served as a teaching assistant for the Allen School’s introductory courses since 2017 and spent the past summer as a software engineering intern at Microsoft. Outside of the classroom, Devgun has engaged in systems research alongside Allen School professor Tom Anderson and served as lead iOS developer for the Stroke Research Team at the UW Medical Center. As a high school student in Bellevue, Washington, he co-founded Clockwork Development, LLC, an iOS app development company. Originally from Bracknell, England in the United Kingdom, Devgun has also lived in Canada and the U.S. states of Florida and Georgia.

Allen School: What does being a first-generation student mean to you?

Dilraj Devgun: Being a first-generation student isn’t something I think about on a daily basis now, but when I first started at UW and I was still trying to find my community, it was a defining factor about how I viewed myself in relation to everyone around me. I was left to rely largely on myself. I felt like I didn’t belong, and to this day I still shy away from telling anyone the full story about my upbringing; however, I wouldn’t trade the experience for any other. My father never finished high school because he left India as a refugee from the Sikh massacre. My Mum, having dealt with a hearing disability since birth, also never had much of an education — which left a large burden on me, as the environment I grew up in treated me with hostility. Education was largely seen as an escape, but we don’t have the guidance many others have. I feel proud to be where I am and to me the title of a first-generation student is a humbling fact since it gives me the time to reflect on who I am and where I came from.

Allen School: What advice do you have for future first-gen students?

DD: Don’t compare yourself to anyone around you. Focus on yourself and put in the work. Put aside pride and any lack of privilege, because hard work doesn’t discriminate. Everyone has to put in the effort and some people just have to work harder than the rest, but as long as you’re focused on your passion you can outwork anyone around you. There’s no guarantee of success, but the only thing you have control over is to do your best, so don’t give anything less than your best.

Allen School: What is your favorite part about being an Allen School student?

DD: I owe so much to the Allen School. They took a chance on me and offered me an education and community that I feel so proud to say that I’m a part of. Firstly, I love the classes that I take — I always learn something new each quarter. In addition to the education, the Allen School has provided opportunities for me to explore what my specific passion is within the field and to give back to other students in the form of teaching or mentoring. That is something I am really happy I have the chance to do.

“As a first-generation student myself, I know how transformative higher education can be for these students and their families,” said Allen School Director Hank Levy. “I also know that it can be challenging to overcome any obstacles along the way. We are thrilled to count Shariya, Simplicio, Dilraj and the many other first-gen students at the Allen School as members of our extended family and appreciate the diverse experiences and talents they bring to our campus and our field.”

Learn more about the National First-Generation College Celebration here.

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From left: Team members Halden Lin, Dominik Moritz, and Jeffrey Heer accept the Best Paper Award from committee member Niklas Elmqvist.

A team of researchers in the Allen School’s Interactive Data Lab (IDL) collected the Best Paper Award at InfoVis 2018 for Draco, an open-source, constraint-based system that formalizes guidelines for visualization design and their application in visualization tools. Draco provides a one-stop shop for researchers and practitioners to apply and test a set of accepted design principles and preferences and to make adjustments to their visualizations based on the results.

“There is a robust, ongoing line of research devoted to understanding how people interpret visualizations, but that guidance is ever-changing and tends to make its way very slowly into practical application,” said Allen School Ph.D. student Dominik Moritz, lead author on the paper. “Draco formalizes that knowledge into a tool that enables researchers and practitioners to build effective visualizations that are grounded in the latest research, while offering the flexibility to make design trade-offs based on user preference.”

Draco encodes the building blocks of visualization, such as input data and visualization type, into a set of logical facts based on an extension of Vega-Lite, a high-level language for describing interactive visualizations. It combines that with an encoding of accepted design principles and preferences as a set of hard and soft constraints that govern the appearance of those facts. The system employs a constraint solver to reason about visualization design based on the encoded guidelines and user inputs. While Draco requires that hard constraints — such as the use of a valid mark type like bar, line, point, etc. — must be satisfied, the soft constraints are assigned varying weights based on visual perception experiments and generally accepted best practices. This allows for a degree of flexibility for the user to make design trade-offs based on their own preferences or the conventions of their particular field.

A graphic recording of Dominik Moritz’ presentation on Draco completed live at the conference by artist Benjamin Felis

The constraint-based approach has another advantage in that it allows Draco to actively assist the user by recommending and ranking visualization designs based on a query, or partial specification, in which the user has left some attributes of their desired visualization blank. The user can also test their visualizations in Draco, which will alert them to violations of the encoded guidelines “similarly to how the automatic spell-check function operates in a word processing program,” Moritz explained. The user can then decide whether and how to adjust their graphic based on the severity of the violation. As people’s preferences and formal design theory evolve, the team envisions the design community adding new constraints — and adjusting the relative weights of existing ones — to incorporate the latest best practices.

Moritz’ co-authors on the paper include fellow Ph.D. students Chenglong Wang and Greg Nelson, fifth-year master’s student Halden Lin, Allen School professor Jeffrey Heer, iSchool professor and Allen School adjunct professor Bill Howe, and former Allen School postdoc Adam Smith, who is now a faculty member at the University of California, Santa Cruz. The team presented Draco at VIS 2018, part of the Institute of Electrical and Electronics Engineers’ annual IEEE VIS conference that brings together researchers in Scientific Visualization, Information Visualization, and Visual Analytics, in Berlin, Germany last month.

Moritz and Heer were also part of the team that developed Vega-Lite, the visualization language that underpins Draco which earned a Best Paper Award at InfoVis 2016. For more on Draco, check out the Interactive Data Lab’s Medium post here, and read the research paper here.

Way to go, team!

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The Paul G. Allen School of Computer Science & Engineering is proud to participate in this weekend’s tribute to Mr. Allen. We re-commit ourselves to fulfilling his vision.

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The UW-led Curious Minded Machine team, clockwise from top left: Sidd Srinivasa, Maya Cakmak, Dieter Fox, and Leila Takayama

A team of researchers led by professor Siddhartha “Sidd” Srinivasa of the Allen School’s Personal Robotics Lab is contributing to an ambitious new project to better understand human curiosity and how that principle can be applied to robot learning. The initiative, Curious Minded Machine, was launched by Honda Research Institute USA to support academic research that will advance artificial cognition by instilling curiosity in intelligent systems — with the ultimate goal of enabling robots to continuously and independently acquire new knowledge and capabilities for the benefit of humankind.

Srinivasa and Allen School professors Maya Cakmak, director of the Human-Centered Robotics Lab, and Dieter Fox, head of the Robotics & State Estimation Lab, will apply their combined expertise in robot manipulation, human-robot interaction, programming by demonstration, and robot perception to develop a mathematical model of curiosity inspired by the concept of child learning through exploration. In collaboration with professor Leila Takayama of the University of California, Santa Cruz — an expert in the psychology of human-robot interaction — they will test their model via implementation in physical systems and through user studies. The group plans to deploy its “curiosity engine” in two kinds of robots: a social robot that engages with people in its environment, to explore the impact on human-robot interaction; and a manipulator robot that engages with objects, to determine its effect on tasks involving manipulation and control.

In addition to overcoming the technical challenges, Srinivasa foresees having to grapple with questions that get at the heart of what it means to be human — and how the emergence of Curious Minded Machines might alter the way in which we relate to our robot counterparts. “What is curiosity? Can we build a rich mathematical model that makes a robot curious?” Srinivasa wondered during an interview with UW News. “Will a curious robot be accepted more? Will we be more tolerant of its mistakes?”

Cakmak, for one, hopes that will be the case, and that curiosity will not only make robots more adaptable and better at their jobs but also more appealing to people. Aside from these practical considerations, Cakmak and her colleagues are interested in discovering whether the lifelong benefits of human curiosity — the ones that accrue beyond the task at hand — can also be transferred to robots. “Humans are intrinsically rewarded by new information even when that information is not necessarily applicable,” she noted, “but curiosity has long-term benefits. We would like to give robots similar benefits for being curious.”

Srinivasa and his colleagues are interested in whether curiosity will enable robots to independently acquire new knowledge and capabilities. Dennis Wise/University of Washington

The University of Washington-led team will receive $2.7 million over three years from the Honda Research Institute to support its work as part of a Network of Excellence that also includes Massachusetts Institute of Technology and the University of Pennsylvania. Each of the partner institutions is tackling a different but complementary challenge; MIT will focus on establishing a causal theory of sensor percepts that will enable intelligent systems to predict future percepts and the effects of future actions, while the University of Pennsylvania team aims to mimic biological learning to aid robots in acquiring representations of the surrounding world and actions.

“Our ultimate goal is to create new types of machines that can acquire an interest in learning and knowledge, and the ability to interact with the world and others,” Soshi Iba, principal scientist at Honda Research Institute USA, explained. “We want to develop Curious Minded Machines that use curiosity to serve the common good by understanding people’s needs, empowering human productivity, and ultimately addressing complex societal issues.”

Read more about today’s announcement in the institute’s press release here and the UW News story here. To learn more about the initiative, visit the Curious Minded Machine website here. Check out a related article by GeekWire here.

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Researchers in the Allen School and University of Washington’s Department of Electrical & Computer Engineering were recognized this week with the IMWUT Vol 1. Distinguished Paper Award for their 2017 paper, “LoRa Backscatter: Enabling the Vision of Ubiquitous Connectivity.” The award, which was announced during the Ubicomp 2018 conference in Singapore, recognizes outstanding research contributions published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.

Long-range backscatter is the first system of its kind to enable low-cost, wide-area connectivity for a range of objects and devices while consuming 1000x less power than existing technologies. Until now, devices capable of communicating over long distances were bulky and consumed significant amounts of power, whereas the communication range for lighter, less power-hungry devices was short. Long-range backscatter offers the best of both worlds: a light-weight form factor that requires mere microwatts of power that is also capable of transmitting data over a distance of 2.8 kilometers. It manages this by reflecting radio frequency (RF) signals onto sensors that, in turn, synthesize and transmit data to a receiver for decoding, using chirp spread spectrum (CSS) modulation to amplify the signals over longer distances. Other noteworthy technical contributions include the first backscatter harmonic cancellation mechanism to combat sideband interference, and a link-layer protocol that enables multiple devices to share the spectrum.

The project represented a significant breakthrough in the effort to embed connectivity into everyday objects to enable a range of new applications, from smart agriculture to personalized medicine. It earned the notice of Paul Allen, who highlighted long-range backscatter as one of 10 innovations “making the world a better place” to have emerged from the Allen School during its first year. The project was featured on Allen’s blog back in March to coincide with the anniversary of the founding of the school that bears his name.

The system builds on previous work on backscatter led by Allen School professor Shyam Gollakota, director of the Networks & Mobile Systems Lab, and Allen School and ECE professor Joshua Smith, head of the Sensor Systems Laboratory. ECE Ph.D. alumnus Vamsi Talla and Allen School Ph.D. student Mehrdad Hessar are co-primary authors of the paper. Additional contributors include ECE Ph.D. students Bryce Kellogg and Ali Najafi. UW spinout Jeeva Wireless, where Talla now serves as chief technology officer, is commercializing the technology.

For more on this project, see the original UW News release here and a related blog post here. Visit the project website here.

Congratulations to the entire team!

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It is with great sadness that the faculty, staff, and students of the Paul G. Allen School of Computer Science & Engineering mark the passing of Paul Allen — pioneering innovator, generous philanthropist, and faithful friend. Mr. Allen was a visionary who opened up new frontiers and pushed the limits of scientific discovery. His connection to the University of Washington ran deep. Through his vision, his leadership and his generosity, he transformed our program, our campus, our region, and the world.

“Paul’s vision of the role of science and technology in society coupled scientific discovery with the quest for solutions to humankind’s greatest challenges,” said Allen School professor Ed Lazowska. “It led him to establish the Allen Institutes for Artificial Intelligence, Brain Science, and Cell Science — and to invest in us, the Paul G. Allen School. We are deeply saddened by his death, and we recommit ourselves to the pursuit of this vision.”

When the Allen School was announced in March 2017, Mr. Allen expressed optimism that we were entering a golden age of innovation in computer science. “I look forward to watching the new Paul G. Allen School of Computer Science & Engineering continue to make profound contributions both to the field and to the world,” he said. “I look ahead with anticipation to the advances that will continue to flow from the school — advances that I hope will drive technology forward and change the world for the better.”

We did not have nearly enough time to demonstrate how we would repay his faith, but we will continue to draw inspiration from his words and his belief in what the Allen School could achieve.

“Paul was a truly remarkable person who changed the world multiple times in his lifetime, and whose initiatives will continue to change the world for decades to come,” said Allen School Director Hank Levy. “We can only hope to follow his example, by searching for the most important scientific and societal challenges of our era and applying our energies to solving them.”

Mr. Allen was a giant. As we said on our very first day as the Allen School, his gift will inspire us to reach higher every day.

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A team led by Allen School professor Su-In Lee and Ph.D. student Scott Lundberg has developed a machine-learning system that both predicts and explains why some patients are at risk for developing hypoxemia, a potentially dangerous drop in blood oxygen levels that can occur in people under general anesthesia. A growing number of predictive machine-learning models have shown high accuracy in medical applications, but understanding how they arrive at their predictions remains a challenge. The aptly-named Prescience analyzes factors specific to the patient and procedure that may presage hypoxemia and explains their impact on a patient’s risk in real time to aid anesthesiologists in preventing life-threatening complications during surgery. The project, which was developed in collaboration with physicians at UW Medicine, Seattle Children’s, and the Veterans Affairs Puget Sound Health Care System, is featured on the cover of the latest issue of Nature Biomedical Engineering.

Hypoxemia during surgery is associated with a range of adverse medical outcomes, including cardiac arrest, post-operative infection, decreased cognitive function, and more. While operating room personnel are able to continuously monitor a patient’s blood oxygen saturation with the aid of pulse oximetry, such data do not enable them to anticipate a hypoxemic event — only react to one that is in process. Prescience supplements pre-surgery and real-time patient data with minute-by-minute data from more than 50,000 past surgeries to reliably predict when hypoxemia is likely to occur and which combination of factors led to its prediction.

Because it can both anticipate and explain hypoxemia risk, Prescience represents a marked improvement over existing decision support systems — which tend to support interventions that are more reactive than proactive — and over uninterpretable machine learning solutions. By providing both predictions and explanations, this approach can help doctors to establish an appropriate level of trust in the model. It’s this difference, Lee says, that makes Prescience such a powerful tool to improve patient outcomes. “Modern machine-learning methods often just spit out a prediction result. They don’t explain to you what patient features contributed to that prediction,” Lee explained in a UW News release. “Our method opens this black box and actually enables us to understand why two different patients might develop hypoxemia.”

The “why” is determined via a complex combination of factors, including patient physiology, medical history, vital signs, ventilator settings, medication, and time. Prescience relies on feature-importance estimates to weigh the strength of each factor in formulating its prediction, which an anesthesiologist can use to determine the most appropriate intervention. The team tested the ability of anesthesiologists to anticipate hypoxemic events with and without the aid of Prescience and found that, using the system, they could correctly predict whether a patient was at risk nearly 80% of the time.

Prescience team members, left to right: Bala Nair, Su-In Lee, Monica Vavilala, and Scott Lundberg. Mark Stone/University of Washington

Extrapolating the results of their experiments to the roughly 30 million surgeries performed annually in the United States alone, the researchers found that using Prescience could double from 15% to 30% the proportion of hypoxemic events that could be anticipated and potentially prevented — the equivalent of 2.4 million incidents per year. Given that 20% of the predicted risk is driven by settings under an anesthesiologist’s control, Prescience could become an indispensable tool for achieving better post-operative outcomes for a significant number of patients. “Prescience doesn’t treat anyone,” Lundberg noted. “Instead it tells you why it’s concerned, which then enables the doctor to make better treatment decisions.”

Contributors to the paper presenting Prescience include Drs. Bala Nair and Monica Vavilala, and software engineer Shu-Fang Newman of UW Medicine’s Department of Anesthesiology & Pain Management; Dr. Mayumi Horibe of the Veterans Affairs Puget Sound Health Care System; and Drs. Michael Eisses, Trevor Adams, David Liston, Daniel King-Wai Low, and Jerry Kim of Seattle Children’s. Kim and Lee initially conceived of the project. The team is planning to make further refinements to both the system and the interface before Prescience can be deployed in operating rooms around the country.

For more on Prescience, read the Nature Biomedical Engineering paper, “Explainable machine-learning predictions for the prevention of hypoxaemia during surgery,” and the UW News release. Also see related coverage by GeekWire.

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The research team, from left: Vikram Iyer, Shyam Gollakota, Jennifer Mankoff, Ian Culhane, and Justin Chan. Mark Stone/University of Washington

Last year, researchers in the Allen School’s Networks & Mobile Systems Lab unveiled a set of prototypes and schematics that represented the first 3D-printed objects capable of communicating over WiFi without built-in electronics. Now, those smart objects are about to get even smarter thanks to new built-in analytics that can wirelessly track and store data about their use — even when they are out of the range of WiFi.

The new system is the product of a collaboration between the original group, led by professor Shyam Gollakota, and the Allen School’s Make4All Group led by professor Jennifer Mankoff. Together, this multidisciplinary team demonstrated how 3D-printed items imbued with analytic capabilities could be used for a variety of applications to improve quality of life or potentially even save a life, from smart assistive devices that absorb feedback from the user, to smart pill bottles that record when a patient last took their medication.

But first, they had to find a way to perform room-scale sensing while registering a range of bi-directional and rotational movements. The team also needed an effective means of storing and retrieving the collected data even if the object does not maintain a WiFi connection while relying on plastic parts. “Using plastic for these applications means you don’t have to worry about batteries running out for your device getting wet,” Gollakota noted in a UW News release. “But if we really want to transform 3D-printed objects into smart objects, we need mechanisms to monitor and store data.”

The team began by building on previous, groundbreaking work from Gollakota and colleagues that successfully married mechanical gears and switches with the digital capabilities of backscatter communication. Backscatter enables devices to transmit data by reflecting ambient radio frequency (RF) signals that are decoded by a WiFi receiver. For this project, the researchers aimed to extend the transmission range of their first 3D-printed objects to room scale — a necessity if such devices are to be practical for everyday living. By applying interference cancellation techniques, which enabled the receivers to pick up weaker backscattered signals from farther away, the team demonstrated their devices could successfully transmit data from a distance of four meters.

In 3D-printed smart objects, a switch made of conductive plastic filament, not electronic components, is used to transmit the data when activated by the mechanical turning of a gear. The original design contained a uni-directional switch with a single antenna. But as Vikram Iyer, a Ph.D. student in the Department of Electrical & Computer Engineering who works with Gollakota, explained, they had to switch up their approach to sense bi-directional movement. “This time we have two antennas, one on top and one on bottom, that can be contacted by a switch attached to a gear,” he said. “So opening a pill bottle cap moves the gear in one direction, which pushes the switch to contact one of the two antennas. And then closing the pill bottle cap turns the gear in the opposite direction, and the switch hits the other antenna.”

A 3D-printed e-NABLE prosthetic device that collects and stores data about its use. Mark Stone/University of Washington

To determine the direction of movement, Iyer and his colleagues embedded an asymmetric code into the gear’s teeth. As the gear turns, the specific direction of movement is indicated via the encoded sequence — “like Morse code,” according to Allen School Ph.D. student Justin Chan.

The team, which also includes undergraduate Ian Culhane of the Department of Mechanical Engineering, aimed to produce “anywhere analytics” by enabling the devices to collect and store data over time even as the user moves in and out of WiFi range. To accomplish this, the researchers developed a mechanical data capture and storage mechanism that relies on a ratchet system. The system holds state as data is collected out of range of WiFi; when the device is once again within range, the press of a button releases the ratchet so it can wirelessly transmit the stored data. As proof of concept, the team designed a special insulin pen that employs the ratchet system to store a user’s dosage history, based on how far the syringe’s plunger has been depressed.

Having solved the technical issues, the team was interested in finding out whether its approach could benefit the users of a particular class of 3D-printed objects: customized prosthetic devices. While the growing popularity and affordability of 3D printing has the potential to lower barriers of access to such specialized equipment, there is no practical way to track what happens with the devices once they are with the user — and evidence suggests that the abandonment rate for assistive technologies could be as high as 75%. But armed with embedded analytics, technologies such as the e-NABLE prosthetic limb, which assists children with hand abnormalities, could potentially track frequency of use as well as finer-grained data on rotation angle and direction to paint a fuller picture of how users are – or aren’t – benefiting from these devices.

For Mankoff, who has done extensive work in this area, the combination of 3D printing and backscatter technology is an opportunity to not only get to the root of those statistics, but hopefully, to turn the numbers around. “This system will give us a higher-fidelity picture of what is going on,” Mankoff explained. “Right now we don’t have a way of tracking if and how people are using e-NABLE hands. Ultimately what I’d like to do with these data is predict whether or not people are going to abandon a device based on how they’re using it.”

The team will present its research paper at the Association for Computing Machinery’s Symposium on User Interface Software and Technology (UIST 2018) next week in Berlin, Germany.

For more on this project, read the UW News release here and visit the project page here. Also check out related stories by Engadget, MIT Technology Review, Silicon Republic, and Professional Engineering.

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Irene Zhang (left) with award committee chair Emmett Witchel

Allen School alumna Irene Zhang (Ph.D., ’17) has been recognized with the 2018 Dennis M. Ritchie Doctoral Dissertation Award at the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI) taking place in Carlsbad, California. The award committee selected Zhang’s dissertation, “Towards a Flexible, High–Performance Operating System for Mobile/Cloud Applications,” for its breadth and potential to inspire future research.

Zhang’s thesis makes multiple contributions spanning mobile and cloud computing. Today’s applications have become incredibly difficult to write; no longer simple desktop programs, they are now surprisingly complex distributed systems with components spread across geographically and functionally diverse mobile devices and cloud servers. Zhang presents multiple systems that address the challenges of programming in this space.

The first of Zhang’s contributions, Sapphire, offers both a new methodology for writing distributed applications and a system supporting that methodology. The Sapphire system greatly simplifies programming for distributed applications by separating generic application logic from distributed deployment decisions, such as where data or computation should be located, what data should be cached or replicated, and what consistency guarantees are necessary.

Another system, named Diamond, is concerned with a relatively new property of modern applications: reactivity. Applications such as games and social networking expect changes to distributed state to be propagated automatically and instantly to other users and to durable storage, so that all users see the same values in the same order. With Diamond, changes to shared application variables on any device automatically cause those values to be made durable in the cloud, update the values on other devices sharing them, and trigger those devices to “react” to the changes by updating the user interface so the user quickly sees the change.

Finally, in TAPIR (“Transactional Application Protocol for Inconsistent Replication”), Zhang dissects the protocols used in today’s distributed storage systems to improve the performance of consistency management among replicas. By simplifying the replication protocol with a technique she calls “inconsistent replication,” Zhang is able to provide both lower latency and higher throughput on distributed storage systems without sacrificing transactional properties.

The Dennis M. Ritchie Award was created by the Association for Computing Machinery’s Special Interest Group in Operating Systems (ACM SIGOPS) to recognize and encourage creative research in software systems in honor of A. M. Turing Award winner Dennis Ritchie, who was a pioneer in operating systems theory and implementation of the UNIX operating system. The award is presented during alternating years at OSDI and the ACM Symposium on Operating Systems (SOSP).

Zhang, who earned her Ph.D. working with professors Arvind Krishnamurthy and Hank Levy and is now a researcher at Microsoft Research, is the second Allen School student to be acknowledged by the Ritchie Award. Alumna Roxana Geambasu (Ph.D., ’11) earned an Honorable Mention for her dissertation “Empowering Users with Control over Cloud and Mobile Data” in 2013, the first year in which the award was given.

Congratulations, Irene!

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Silin Zeng (center) with Lisa Simonyi (left) and Charles Simonyi

Every autumn, the Allen School kicks off the new academic year by highlighting the role of women in computing and sending off our delegation to the Grace Hopper Celebration of Women in Computing in style. This year, we broadened the scope of one of our favorite events of the year to celebrate the contributions of all underrepresented groups and highlight our expanding efforts to broaden participation in the field through activities such as the Grace Hopper conference, the ACM Richard Tapia Celebration of Diversity in Computing, the College of Engineering’s STARS program, AccessCSForAll, and more.

Nearly 100 students, faculty, staff, alumni, and friends gathered in the Paul G. Allen Center last night for our Diversity in Computing reception. The Allen School’s Assistant Director for Diversity & Outreach, Raven Avery, provided an overview of our recent activities, and fifth-year master’s students Melissa Hovik and Nicole Riley shared their experiences representing the Allen School at the Grace Hopper and Tapia conferences, respectively. Anat Caspi, Director of the Taskar Center for Accessible Technology, was also on hand to discuss how members of the Allen School community can get involved in the center’s work to promote inclusive design practices and produce technologies that increase independence and improve quality of life for people with motor and speech impairments.

Another of the evening’s highlights came when Charles and Lisa Simonyi, longtime friends and supporters of the Allen School, announced undergraduate Silin Zeng as the winner of the 2018 Lisa Simonyi Prize. The award recognizes a student each year who exemplifies the Allen School’s commitment to excellence, inclusiveness, and leadership. Zeng, who is in her final year at UW majoring in Computer Science and Finance, is an alumna of the UW Academy early entrance program for exceptionally talented students run by the Robinson Center for Young Scholars. She has been an enthusiastic contributor to the campus community as Treasurer of the UW chapter of the Association for Computing Machinery (ACM), Creative Director for the Asian Business Student Association, and a member of ACM-W and the Society of Women Engineers. She also has completed internships at Microsoft and Goldman Sachs — an experience that galvanized her commitment to advancing diversity via her work with ACM and as a mentor to her peers. As Lisa Simonyi noted when announcing the award, Zeng has spunk.

Thanks to the Simonyis for supporting diversity and excellence, and thanks to everyone who came out to celebrate the people who are making our school and our field a more welcoming destination for all. And congratulations to Silin on her well-deserved recognition for putting these values into practice every day!

For more about our efforts to advance diversity in computing, read about the Allen School’s contributions to this year’s Tapia conference in a recent blog post here, and check out our inclusiveness statement here.

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