Allen School News

University of Washington professor Thomas Rothvoss, a member of the Allen School’s Theory of Computation group with a joint appointment in the UW Department of Mathematics, has received the 2023 Gödel Prize recognizing outstanding papers in theoretical computer science for “The matching polytope has exponential extension complexity.” In the paper, Rothvoss proved that linear programming — a core technique in combinatorial optimization for modeling a large class of problems that are polynomial-time solvable  — cannot be used to solve the perfect matching problem in polynomial time. He originally presented these results at the 46th Association for Computing Machinery Symposium on Theory of Computing (STOC 2014).

Rothvoss shares this year’s accolade with researchers Samuel Fiorini and Serge Massar of the Université Libre de Bruxelles, Hans Raj Tiwary of Charles University in Prague, Sebastian Pokutta of the Zuse Institute Berlin and Technische Universität Berlin, and Ronald de Wolf of the Centrum Wiskunde & Informatica and the University of Amsterdam. Two years before Rothvoss published his seminal result, that team proved the extension complexity of the polytope for the Traveling Salesperson Problem is exponential — confirming that there is no polynomial-sized extended formulation, and therefore no small linear program, that can be used to solve the TSP. 

That result provided a partial, yet definitive, answer to a problem posed by theoretician Mihalis Yannakakis two decades prior. For Rothvoss and his colleagues in the tight-knit theory community, it was a watershed moment.

“Most of the time in complexity theory, we deal in conjectures but can’t actually prove any of them,” Rothvoss said. “On a good day, we can maybe prove that one conjecture implies another. So it was rather surprising when Sam and the rest of that group proved, completely unconditionally, the exponential extension complexity of the TSP polytope.”

The group further proved that its result extended to the maximum cut and stable-set polytopes, as well. But that proof, significant as it was, only answered the question for problems that are NP-hard. Inspired by the progress Fiorini and his collaborators had made, Rothvoss aimed to settle Yannakakis’ question once and for all when it comes to linear programs applied to polytopes that are not NP-hard — that is, well-understood polytopes, such as that of the perfect matching problem, for which polynomial-time algorithms for optimizing linear functions are known to exist. 

And settle it, he did.

“I focused on it full-time for half a year,” Rothvoss recalled. “A couple of the technical aspects of that 2012 paper were also useful for my purposes, such as a technique drawn from Razborov’s classic paper on communication complexity, while others I had to modify.

“In particular, we knew the so-called rectangle covering lower bound used by Fiorini et al. to great effect in the case of TSP would not suffice for the matching polytope,” he continued. “In fact, the rectangle cover number for matchings is polynomial in the number of vertices, so it turned out that a more general technique — hyperplane separation lower bound — works instead.”

In the process of arriving at his proof, Rothvoss confirmed that Edmonds’ characterization of the matching polytope, made nearly half a century earlier, is essentially optimal. According to Allen School professor James R. Lee, his colleague’s work was — and remains — a significant insight with ramifications in mathematics, algorithm design and operations research.

“Thomas’ work is a masterful combination of ideas from two seemingly disparate areas of TCS,” said Lee. “It’s the synthesis of really profound insights of Yannakakis and Razborov from three decades ago, weaving together polyhedral combinatorics and communication complexity to settle a problem that essentially predates the era of P vs. NP.”

Rothvoss previously received the Delbert Ray Fulkerson Prize from the Mathematical Optimization Society and the American Mathematical Society for the same work. He is also the past recipient of a Packard Fellowship, a Sloan Research Fellowship, a National Science Foundation CAREER Award and Best Paper Awards at STOC, the Symposium on Discrete Algorithms (SODA) organized by the ACM and the Society for Industrial and Applied Mathematics (SIAM), and the Conference on Integer Programming and Combinatorial Optimization (IPCO). 

The Gödel Prize, named for mathematical logician Kurt Gödel, is co-sponsored by the ACM Special Interest Group on Algorithms and Computation Theory (SIGACT) and the European Association for Theoretical Computer Science (EATCS). Rothvoss and his fellow honorees will be formally recognized at STOC 2023 in Orlando, Florida next month. Learn more about the Gödel Prize here. Read more →

Few occasions better illustrate the human experience than sharing stories over a meal. Yet for people with motor impairments, the act of dining itself can invite undue pressure. Caregivers can get distracted while feeding their clients, who may feel self-conscious about interrupting the ongoing conversations to remind their caregiver to feed them a bite. A simple hangout with friends or family can turn into a source of potential embarrassment. The meal becomes more functional than social — and potentially, a process to be endured rather than a time for celebration. 

That’s changing thanks to an innovative partnership between Allen School robotics researchers and the assistive technology nonprofit Tyler Schrenk Foundation. Led by Ph.D. student Amal Nanavati, postdoc Patrícia Alves-Oliveira and community researcher Tyler Schrenk, the group conducted a study using an assistive robot in social dining contexts.

Prior robot-assisted feeding research has focused on the functional aspects of feeding, such as enabling a robot to recognize food on a plate and deliver it to the user’s mouth. But less attention has been devoted to dining’s social aspects, such as etiquette and conversational norms. 

For the Allen School team, it was a chance to bring all parties to the table. The roboticists engaged with target users of the technology throughout the technology design process, not just at the end to evaluate the system.

“Too often, we as roboticists develop tools that work well in a lab, but not in the dynamic, nuanced, social environments that users want to use them in,” Nanavati said. “If we truly want to take a user-centered approach to developing robot-assisted feeding systems, we have to meet users where they are and develop for the contexts in which they want to use the technology.”

Nanavati and his co-authors, which also include Ph.D. student Ethan K. Gordon and professors Maya Cakmak and Siddhartha Srinivasa, won the Best Design Paper Award at the 2023 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2023).

As part of the study, which was developed with support from UW CREATE’s student minigrant, the researchers created videos to familiarize participants with robot-assisted feeding systems and to facilitate the conversations around users’ preferred features. After incorporating feedback from participant interviews, they then developed design principles and an implementation guide for robot-assisted social dining to enable other researchers to easily contribute to this space. The design was wholly collaborative, with researchers and participants working together. 

“It is an honor to be recognized with a Best Paper Award in a competitive international conference with a work about disabilities and robotics,” Alves-Oliveira said. “It shows that the HRI community recognizes the importance of working equally with a community researcher throughout the research process, and that we have much to learn about designing robotic systems for contexts outside of the lab.”

The team’s community researcher, Tyler Schrenk, was paralyzed in a diving accident in 2012. Since then, he’s become an expert in assistive technology, helping companies in the field empower users and provide greater independence through their creations. As president of the Washington state-based foundation that bears his name, he has helped provide more than $110,000 worth of assistive technologies to individuals with mobility impairments across the world. 

Both Nanavati and Alves-Oliveira credited Schrenk for providing crucial insights and helping recruit participants for the study, which is one of the few to involve a “community researcher,” a member of the target community who collaborates with the team throughout the entire research process, from early ideation all the way to research publication. 

“I believe the future of caregiving and at-home nursing care is the assistive robotic field,” Schrenk said. “Assistive robotics are a must for those living with disabilities.” 

Currently, many challenges affect at-home care. Schrenk pointed to a lack of available caregivers as well as challenges with receiving care that is tailored to one’s needs and preferences. Another hurdle is giving users an increased sense of autonomy. With assistive robots, users would be empowered to complete tasks when they want to and in their own way, augmenting the support that human caregivers can provide them. 

“Tyler helped define the direction of the project and provided context for much of the data analysis,” Nanavati said. “This collaboration helped us reach much deeper insights and challenged us to adapt research norms to make them more accessible.”

A meal should be memorable, Alves-Oliveira added, and not for a potential faux pas from the machine. No spilled food, no extraneous movements. First and foremost, the user should be in control. 

Together, the team has set the table for a brighter future, a place where everyone feels welcome. 

“No matter what culture we belong to, there are moments at the table that can be compared to a sacred ritual — we share important moments of our lives while sharing food,” Alves-Oliveira said. “We discovered that people with motor impairments are missing out on this social exchange because they are distracted by challenges during dining or they avoid social dining altogether. We wanted to bring back this meaningful experience to them with the help of a robot.”

Read the research paper here, watch a video presentation of the work here, and see some of the ways in which robot-assisted social feeding can go wrong here.  Read more →

Since 2020, communities around the globe have endured more than 1,100 natural disasters combined. From floods and drought to earthquakes and wildfires, these events contribute to human suffering and economic upheaval on a massive scale. So, too, do pandemics; since the emergence of SARS-CoV-2 at the end of 2019, nearly 7 million people have died from COVID-19. 

Then there is the human, economic and geopolitical toll caused by cyberattacks. While there is no way to know for certain, one oft-cited study estimated hackers launch “brute force” attacks against a computer once every 39 seconds, the equivalent of roughly 800,000 attacks per year. The fallout from malicious actors gaining unauthorized access to these and other systems — ranging from an individual’s laptop to a country’s electrical grid — is projected to cost as much as $10.5 trillion worldwide by 2025.

Whether natural or human-made, events requiring rapid, coordinated responses of varying complexity and scale could be could be addressed more efficiently and effectively with the help of artificial intelligence. That’s the thinking behind two new National Artificial Intelligence Research Institutes involving University of Washington researchers, including Allen School professors Simon Shaolei Du and Sewoong Oh, and funded by the National Science Foundation.

AI Institute for Societal Decision Making

Allen School professor Simon Shaolei Du will contribute to the new AI Institute for Societal Decision Making (AI-SDM) led by Carnegie Mellon University. The institute will receive a total of $20 million over five years to develop a framework for applying artificial intelligence to improve decision making in public health or disaster management situations, when the level of uncertainty is high and every second counts, drawing on the expertise of researchers in computer science, social sciences and humanities along with industry leaders and educators.

“AI can be a powerful tool for alleviating the human burden of complex decision making while optimizing the use of available resources,” said Du. “But we currently lack a holistic approach for applying AI to modeling and managing such rapidly evolving situations.”

To tackle the problem, AI-SDM researchers will make progress on three key priorities to augment — not replace — human decision making, underpinned by fundamental advances in causal inference and counterfactual reasoning. These include developing computational representations of human decision-making processes, devising robust strategies for aggregating collective decision making, and building multi-objective and multi-agent tools for autonomous decision-making support. Du will focus on that third thrust, building on prior, foundational work in reinforcement learning (RL) with long-time collaborators Aarti Singh, professor at CMU who will serve as director of the new institute, and Allen School affiliate professor Sham Kakade, a faculty member at Harvard University, along with CMU professors Jeff Schneider and Hoda Heidari.

Adapting RL to dynamic environments like that of public health or disaster management poses a significant challenge. At present, RL tends to be most successful when applied in data-rich settings involving single-agent decision making and using a standard reward-maximization approach. But when it comes to earthquakes, wildfires or novel pathogens, the response is anything but straightforward; the response may span multiple agencies and jurisdictions, the sources of data will not have been standardized, and each incident response will unfold in an unpredictable, situation-dependent manner. Compounding the problem, multi-agent decision making algorithms have typically performed best in scenarios where both planning and execution are centralized — an impossibility in the evolving and fragmented response to a public health threat or natural or human-made disaster, where the number of actors may be unknown and communications may be unreliable. 

Du and his colleagues will develop data-efficient multi-agent RL algorithms capable of integrating techniques from various sources while satisfying multiple objectives informed by collective social values. They will also explore methods for leveraging common information while reducing sample complexity to support effective multi-agent coordination under uncertainty.

But the algorithms will only work if humans are willing to use them. To that end, Du and his collaborators will design graduate-level curriculum in human-AI cooperation and work through programs such as the Allen School’s Changemakers in Computing program to engage students from diverse backgrounds — just a couple of examples of how AI-SDM partners plan to cultivate both an educated workforce and an informed public.

“There is the technical challenge, of course, but there is also an educational and social science component. We can’t develop these tools in a vacuum,” Du noted. “Our framework has to incorporate the needs and perspectives of diverse stakeholders — from elected officials and agency heads, to first responders, to the general public. And ultimately, our success will depend on expanding people’s understanding and acceptance of these tools.”

In addition to CMU and the UW, partners on the AI-SDM include Harvard University, Boston Children’s Hospital, Howard University, Penn State University, Texas A&M University, the University of Washington, the MITRE Corporation, Navajo Technical University and Winchester Thurston School. Read the CMU announcement here.

AI Institute for Agent-based Cyber Threat Intelligence and Operation

Allen School professor Sewoong Oh and UW lead Radha Poovendran, a professor in the Department of Electrical & Computer Engineering, will contribute to the new AI Institute for Agent-based Cyber Threat Intelligence and OperatioN (ACTION). Spearheaded by the University of California, Santa Barbara, the ACTION Institute will receive $20 million over five years to develop a comprehensive AI stack to reason about and respond to ransomware, zero-day exploits and other categories of cyberattacks. 

”Attackers and their tactics are constantly evolving, so our defenses have to evolve along with them,” Oh said. “By taking a more holistic approach that integrates AI into the entire cyberdefense life cycle, we can give human security experts an edge by rapidly responding to emerging threats and make systems more resilient over time.”

The complexity of those threats, which can compromise systems while simultaneously evading measures designed to detect intrusion, calls for a new paradigm built around the concept of stacked security. To get ahead of malicious mischief-makers, the ACTION Institute will advance foundational research in learning and reasoning with domain knowledge, human-agent interaction, multi-agent collaboration, and strategic gaming and tactical planning. This comprehensive AI stack will be the foundation for developing new intelligent security agents that would work in tandem with human experts on threat assessment, detection, attribution, and response and recovery.

Oh will work alongside Poovendran on the development of intelligent agents for threat detection that are capable of identifying complex, multi-step attacks and contextualizing and triaging alerts to human experts for follow-up. Such attacks are particularly challenging to identify because they require agents to sense and reason about correlating events that span multiple domains, time scales and abstraction levels — scenarios for which high-quality training data may be scarce. Errors or omissions in the data can lead agents to generate a lot of false positives, or conversely, miss legitimate attacks altogether. 

Recent research using deep neural networks to detect simple backdoor attacks offers clues for how to mitigate these shortcomings. When a model is trained on data that includes maliciously corrupted examples, small changes in the input can lead to erroneous predictions. Training representations of the model on corrupted data is an effective technique for identifying such examples, as the latter leave traces of their presence in the form of spectral signatures. Those traces are often small enough to escape detection, but state-of-the-art statistical tools from robust estimation can be used to boost their signal. Oh will apply this same method to time series over a network of agents to enable the detection of outliers that point to potential attacks in more complex security scenarios.

Oh and Poovendran’s collaborators include professors João Hespanha, Christopher Kruegel and Giovanni Vigna at UCSB, Elisa Bertino, Berkay Celik and Ninghui Li at Purdue University, Nick Feamster at the University of Chicago, Dawn Song at the University of California, Berkeley and Gang Wang at the University of Illinois at Urbana-Champaign. The group’s work will complement Poovendran’s research into novel game theoretic approaches for modeling adversarial behavior and training intelligent agents in decision making and dynamic planning in uncertain environments — environments where the rules of engagement, and the intentions and capabilities of the players, are constantly in flux. It’s an example of one of the core ideas behind the ACTION Institute’s approach: equipping AI agents to be “lifelong learners” capable of continuously improving their domain knowledge, and with it, their ability to adapt in the face of novel attacks. The team is keen to also develop a framework that will ensure humans continue to learn right along with them.

“One of the ways this and other AI Institutes have a lasting impact is through the education and mentorship that go hand in hand with our research,” said Oh, who is also a member of the previously announced National AI Institute for Foundations in Machine Learning (IMFL). “We’re committed not just to advancing new AI security tools, but also to training a new generation of talent who will take those tools to the next level.”

In addition to UCSB and the UW, partners on the ACTION Institute include Georgia Tech, University of California, Berkeley, Norfolk State University, Purdue University, Rutgers University, University of Chicago, University of Illinois Chicago, University of Illinois Urbana-Champaign and University of Virginia. Read the UCSB announcement here and a related UW ECE story here.

The ACTION Institute and AI-SDM are among seven new AI Institutes announced earlier this month with a combined $140 million from the NSF, its federal agency partners and industry partner IBM. Read the NSF announcement here.

Read more →

The National Science Foundation (NSF) recognized seven Allen School students as part of its 2023 Graduate Research Fellowship Program (GRFP) competition. The NSF GRFP supports students for their potential to demonstrate excellence and innovation in teaching and research early in their careers. The students — six graduate students and one undergraduate student — were recognized in the Comp/IS/Eng or Engineering categories. 

“Allen School students strive for excellence in research and innovation,” said professor Anna Karlin, associate director for graduate studies at the Allen School. “This year’s NSF GRFP honorees exemplify determination and creativity to push the boundaries in fields as diverse as molecular computing, robotics, security and more.”

Tyler Han

First-year Ph.D. student Tyler Han earned a fellowship for his work in the Robot Learning Lab under the direction of Allen School professor Byron Boots, co-founder and CEO of UW spinout Overland AI​​.

Han’s research focuses on advancing localization, planning, perception and control for high-speed off-road autonomous vehicles operating in unstructured and unpredictable environments. Through his work with the University of Washington’s RACER (Robotic Autonomy in Complex Environments with Resiliency) team and with the support from the NSF GRFP, Han aims to improve the speed and maneuverability of autonomous vehicles using methods like inverse reinforcement learning (IRL), which allows robots to learn from data generated through human driving. With IRL, these robots will better handle situations in which environmental features present complicated situations, like speeding through banked turns or crashing through vegetation.

Rachel Hong

Fellowship recipient Rachel Hong is a first-year Ph.D. student. She works with Allen School professors Jamie Morgenstern, who focuses on the social impacts of ML, and Tadayoshi (Yoshi) Kohno, co-director of the Security and Privacy Research Lab.

Combining ML, security and technology policy, Hong explores the behavior of existing ML algorithms in relation to privacy and fairness, as well as how to prevent those algorithms from being misapplied in society. As an undergraduate student, Hong was introduced to the field of algorithmic fairness through building a novel representation learning algorithm on biomedical data to help patients receiving care at a variety of hospitals in both rural and urban settings. Hong seeks to build on that foundation to improve algorithmic fairness through examining demographic biases in facial recognition technology to better understand how various modifications of training data can mitigate disparate outcomes.

Carina Imburgia

Fellowship winner Carina Imburgia is a first-year Ph.D. student who works with Jeff Nivala in the Molecular Information Systems Lab (MISL).

Imburgia joined the Allen School as a graduate student after having pursued a degree in biology and working in the field of molecular biology. Harnessing her multidisciplinary background, she intends to develop and optimize new systems for processing information stored in molecular form. Imburgia proposes to improve a Cas9-based similarity search architecture, which is a programmable gene editing tool and to develop computing abstractions for processing information molecularly. Decreasing the environmental impact of data storage technologies also motivates her to explore molecular storage options that can hold significantly larger amounts of data in a compact and stable form as well as rely less heavily on energy consumption than current storage methods.

Toma Itagaki

Graduating senior Toma Itagaki received a fellowship based on his research in the Ubiquitous Computing (UbiComp) Lab directed by Allen School and UW Department of Electrical & Computer Engineering professor Shwetak Patel.

Itagaki’s research interests bridge neuroscience, ubiquitous computing and human-computer interaction (HCI). After his first undergraduate research experience at UW in the Orsborn Lab, Itagaki knew he wanted to pursue studying neuroscience. He was drawn to the UbiComp Lab, where he studied wearable sensors such as electroencephalography (EEG) headsets and smartwatches to assess the quality and consistency of data collection. These projects motivated Itagaki to explore the quantification of subjective experiences by looking at sensory brain-machine interfaces. As a Ph.D. student starting this fall at Columbia University, Itagaki intends to explore ways to leverage mobile health and brain-machine interfaces to better address post-surgical pain management.

Alexandra Michael

First-year Ph.D. student Alexandra Michael received a fellowship for her work that is co-advised by Allen School professors David Kohlbrenner in the Security and Privacy Research Lab and Dan Grossman in the Programming Languages and Software Engineering (PLSE) group.

Michael’s research combines her interests in security, programming languages and compilers. Prior to graduate school, Michael was fascinated by how computers could connect people yet put them at risk. Her work focuses on mitigating those risks by leveraging programming languages and security tools to improve the security and privacy of systems and the people who use them. She proposes to build a highly performant, secure and portable low-level language that will act as target for programs written in unsafe languages.

Lancelot Wathieu

Second-year Ph.D. student Lancelot Wathieu earned a fellowship for his work in the MISL with Allen School professors Luis Ceze and Chris Thachuk.

While Wathieu’s background is in computer engineering and mathematics, his research interests are inspired by the natural world, which led him to focus on designing molecular algorithms and systems. Molecular computing has shown promise based on what it could theoretically compute, and Wathieu proposes to put this theory into practice by building an end-to-end automated DNA computing workflow that incorporates novel circuit designs. Wathieu’s work will make molecular computing more efficient and accessible while advancing its transformative potential in domains spanning therapeutics, manufacturing and computer science.

Zachary Englhardt

Zachary Englhardt is a first-year Ph.D. student working with Patel and Allen School professor Vikram Iyer. Englhardt earned an honorable mention from NSF for his design work on embedded systems for sensing, networking and actuation.

Englhardt intends to develop internet of things (IoT) devices with masses under one gram which are capable of autonomously navigating an environment to collect data. Current sensor technologies tend to be stationary and collect data in a passive manner. Previous attempts at building sub-gram autonomous IoT devices have faced scaling challenges due to their weight and power needs. Englhardt proposes to develop a computing and robotics platform to address these challenges. By taking an interdisciplinary approach that integrates intermittent computing, embedded ML and microrobotics fabrication, Englhardt proposes to build a new hardware platform, algorithms for enabling autonomous control, and a novel approach to swarm networking for smart agriculture and other potential applications.

NSF recognized two UW graduate students outside of the Allen School with fellowships in the Comp/IS/Eng category. Claire Mitchell, a first-year Ph.D. student in the Information School, studies and designs wearable sensors to understand motor control and improve communication interfaces. Human Centered Design and Engineering (HCDE) second-year Ph.D. student Brett Halperin employs computational cinema and media design to promote housing justice through community-based participatory research.

Learn more about the NSF GRFP program here. Read more →

Six Allen School students were recently named to the 2023 class of the Husky 100, an honor recognizing undergraduate and graduate students who are making the most of their time at the University of Washington. Husky 100 students make connections in and out of the classroom, making a positive impact on campus and in their communities. This year’s Allen School inductees are living those values, proving Huskies are stronger when in a pack. 

Grace Brigham

At the time, the free Welch’s grape juice was probably a bad idea. Yet it turned out to be what greased the wheels for Grace Brigham, whose visits to her father’s office as a youngster featured the dangerous combination of plentiful sugar and groundbreaking technology. 

“It felt like a wonderland to me,” she said, recalling the ample, well-stocked food courts. 

One day her father showed her what his team had been working on: a touch-screen table. Before the age of iPads, it was like peering through the looking glass for the younger Brigham. The memory, among other things, stuck.

“My dad definitely cringed as I put my probably grape juice-covered hands all over it but I couldn’t help myself,” Brigham said. 

The newly minted member of the Husky 100 has made the most of her time at UW through a number of projects and ventures, each putting community and social impact at the forefront. 

During her first two years, she worked as a mentor and then a program lead with Changemakers in Computing, a summer program offered by the Allen School for Washington state high school students from marginalized backgrounds. As a sophomore, she co-founded Mezzo, an app that helps plan social meetups, and competed in a number of entrepreneurship competitions with her team.

Now a third-year student, Brigham has continued to make her mark at UW. During the most recent quarter, the Redmond native began working in the Allen School’s Security and Privacy Research Lab, investigating conceptions of consent and acceptability in deepfake technology. 

Brigham is set to graduate this fall with her bachelor’s in computer science. When she turns the tassel, a toast might be in order — perhaps one involving that sweet purple potion that helped pique her interest more than a decade ago. 

“No matter what, I tried to make the most of my time and I am truly honored to be receiving recognition for that,” Brigham said. “I’m humbled to join a group of such driven, unique and inspiring individuals.”

Eric Fan

Near the beginning of his UW experience, Eric Fan took an introductory programming course that would alter his perspective. He was mesmerized by the ways in which technology could change the world, their capabilities for problem-solving and the theories behind them. 

But at the center of it all was the teaching assistant who made the concepts come alive. It was an encounter that Fan would never forget. 

“He played a significant role in my success in understanding the course content,” Fan said. “The inspiring way he taught the concepts made a significant contribution to my excitement for computer science.” 

Shortly after taking the course, Fan dove into extracurricular activities. He became a teaching assistant himself, developing a passion for education and for making the field more accessible to students from diverse backgrounds. He served on the Allen School Student Advisory Council and became a research assistant for the Ubiquitous Computing Lab. In 2022, he published a book highlighting efforts from individuals and communities who are making CS education more equitable. 

“The highlights of my Husky Experience have centered around communities and the opportunities to serve,” said Fan, who grew up in the Seattle area. “Having been invested in by several individuals and communities around me, I’ve been inspired to give back.”

Fan completed his master’s degree in computer science this year and is currently teaching CSE 390B. 

“The communities I’ve been a part of, including course staff teams, Allen School student groups and fellowships, have all helped me find my place at a large public university,” Fan said. “I cherish the relationships I’ve developed over the years at UW and am thankful for all the ways they have encouraged me.”

Richard Li

In his high school AP Computer Science class, Richard Li received a smartphone from his teacher with the challenge to “do something cool with it.” The phone ran the first version of Android. There was no documentation or support online. 

“Although the coding process was painful, it was also tremendously exciting to see code running on a physical device external to the computer,” said Li, a South Carolina native. “Running code on a physical device opened up new opportunities to interact with the physical world using features such as motion sensors and cameras. This particular facet and interest guided many future decisions, leading to being in a Ph.D. program and my current research areas.”

It was one of Li’s first forays into analyzing how technology could influence its environment and the end user. At UW, he has conducted research in the wearable and ubiquitous computing space, developing human-centered systems in healthcare, physiology and more. On various projects, he’s worked with advisors James Fogarty, Shwetak Patel, Sean Munson, Cindy Lin, George Ionnaou and Philip Vutien. The fourth-year Ph.D. student chose computer science, he said, because he found the major to be inherently interdisciplinary — solutions, even if they are outside of one’s remit, are encouraged.

The prolific academic environment, along with the university’s proximity to many of tech’s biggest players, has helped Li grow as a scientist, he added. 

“UW’s incredibly supportive community is renowned, well-known internationally,” Li said. “Being in Seattle opens up opportunities to collaborate with partners in the community as well as in industry. Four years later, I’m happy to report that UW has delivered both of these things.”

Li, who plans to graduate in June 2025, continues to do cool things with technology. Working with a team that included computer scientists, engineers and clinicians, he helped develop Beacon, a handheld device that allows for at-home screening of liver disease. He’s also currently working on the design of a smartwatch band with embedded electronics. The design will allow scientists to monitor how well it fits the user’s wrist, he said, while improving the device’s other capabilities using this measurement. The project is advised by Patel.

For Li, his Husky Experience illustrates his former teacher’s request. After graduation, he plans on pursuing a professorship and teaching students to go out and seek solutions — to “do something cool” with their newfound knowledge. 

“I’m honored to be named to the Husky 100,” he said. “It’s rewarding to be acknowledged for the honor of contributing to the UW community, from conducting incredible research to mentoring the next generation of young scientists and engineers.”

Amanda Ong

Amanda Ong entered UW intending to major in biology. But the summer before her freshman year, Ong had an opportunity to work with a team of UW researchers investigating the spectroscopic signatures of nitrogen aggregates in nanodiamonds, proving that diamonds may be forever but plans are rarely written in stone. 

As part of the ALVA program, Ong made the most of an opportunity to work in the Li Lab, a computational chemistry laboratory at UW headed by professor Xiaosong Li. There, she marveled at the supercomputer utilized in the experiment and how it powered the project from start to finish. She eventually switched her major to computer science. 

“Wow!” she said of her eureka moment. “Programming, which had previously seemed so abstract, suddenly had a concrete application.”

Since then, Ong has become an integral member of the UW community. The Redmond native has fostered her interest in CS education through roles with the Society of Women Engineers and the Association for Computing Education, besides working as a teaching assistant for CSE 160, a course she will teach this summer. Currently, she is working with professor Jeffrey Herron in the Herron Lab to develop a testing framework for the OMNI-BIC microservice, which is a microservice designed to facilitate neuromodulation research.

She’s also empowered members of the greater UW community and beyond. As president of the Seattle nonprofit Young Leaders Program, she introduced several prosocial initiatives, including a virtual career events series and a project with the City of Seattle Office of Labor Standards. For the latter, students worked with minority-owned businesses to educate them on the city’s labor laws. 

The fifth-year student completed her undergraduate degree in computer science at UW with a minor in neural computation. She plans to graduate with her master’s in computer science this spring. 

“As a student at UW, I am continually inspired by the fearlessness of my peers, faculty and staff in pursuing their beliefs and passions to create a better environment for those around them,” Ong said. “It’s an honor to be selected for the Husky 100 as it recognizes the same qualities I strive to emulate. I’m particularly proud to be representing the Allen School as a part of such a diverse and inspiring cohort of students.”

May Wang

May Wang wears her school spirit proudly. As co-founder of Dawg Outfitters, a UW merchandise startup, she’s engaged in the endeavors of entrepreneurship in addition to helping put other Huskies in cozy hoodies. 

The Calgary native’s Husky Experience is defined by warmth — whether that’s in the community or in the type of cloth featured in her company’s merchandise. (It’s a high-stitch fleece.)

“Having my work and involvement recognized by UW not only makes me feel valued as a student and as a leader, but has also given me the opportunity to learn about and appreciate the inspiring contributions of fellow Husky 100 students,” Wang said. “Furthermore, it has allowed me to reflect on my own impact on the community. I hope that my work can be an inspiration to others, encouraging them to pursue their passions and make the most of their Husky Experience.”

Wang, a fourth-year computer science student, has performed a number of roles while at UW. When she’s not programming or investigating better ways to safely store passwords, she takes up mentorship opportunities through her work as a teaching assistant and in the Residential Life department, helping younger students along in their own journeys. 

Wang plans to graduate this spring. She said she hopes to continue pursuing entrepreneurship after her time at UW comes to close. 

“I am excited to apply my experiences with technology, leadership and entrepreneurship towards my goal of inspiring others beyond the UW community,” she said.

Duaa Zaheer

When Duaa Zaheer first arrived on the UW campus, she felt like a small fish in a pond much larger than Drumheller Fountain. Her high school graduating class had 38 students — a far cry from the more than 40,000 she would soon encounter.

“I started out my experience as an anxious and overwhelmed freshman who didn’t know where she fit in at a school as big as the UW,” Zaheer said. “Over time, I slowly found myself building community and a support network through groups around campus with students sharing the same interests, passions and skills.” 

By taking active roles in organizations such as Women in Informatics and Impact++, she’s grown as a leader, helping foster a more inclusive environment and build technology for social good. As president of the Pakistani Students Association, she’s shared her love for her culture through community outreach efforts and programs. 

Connecting communities informs Zaheer’s Husky Experience, which will culminate in June when she graduates with her bachelor’s degree in computer science and a minor in informatics. While reflecting on her time at UW, the Redmond native expressed gratitude at staying close to home, while experiencing opportunities that she couldn’t have imagined at the beginning of her freshman year. 

One of those included meeting UW’s cuddliest member, Dubs II. At the Husky 100 celebration this year, Zaheer shook paws with the university’s 14th live mascot as an honored guest, hobnobbing with its biggest cheerleader. 

For Zaheer, it’s just one of several cherished memories that have been a product of the last four years. 

“The Husky 100 is symbolic of the journey I took to reach the well-supported and enlightened point of my college experience I’m at today,” she said. “It is a sign that I’ve left an impact on my school despite how small I felt at the beginning of the journey.” Read more →

There was a time when cookies were considered something to be savored — back when chips referred to chocolate rather than silicon. Once “cookies” became synonymous with online tracking, privacy researchers weren’t so sweet on the concept. 

That includes Allen School professors Franziska Roesner and Tadayoshi Kohno, who investigated the online tracking ecosystem for their 2012 paper “Detecting and Defending Against Third-Party Tracking on the Web.” Last month, Roesner, Kohno and co-author David Wetherall, a former Allen School professor who is now a Distinguished Engineer at Google, received the Test of Time Award at the 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2023) for their influential work, which offered the first comprehensive evaluation of third-party trackers and their intrusion into people’s activities online. 

The team’s findings informed the nascent policy debate around web privacy that has become all the more relevant with the proliferation of social media and reliance on targeted advertising as a revenue model. They also led to the creation of new tools like Privacy Badger, a browser extension that learns and automatically blocks hidden third-party trackers used by millions of people to protect themselves and their browsing histories online. The work also inspired a significant body of follow-on research, including team members’ subsequent paper that appeared at NSDI 2016 chronicling the increase in both the prevalence of online tracking and the complexity of tracker behavior over time.

“Considering how much time we spend online and the variety of activities we engage in, this type of tracking can yield a lot of information about a person,” said Roesner, a co-director of the Security and Privacy Research Lab at the University of Washington along with Kohno. “That’s even truer today than it was a decade ago, and I’m gratified that our work helped initiate such an important conversation and informed efforts to educate and empower users.”

At the time of the original paper’s release, third-party tracking had started to gain attention in security and privacy circles. But researchers were just nibbling around the edges, for the most part; they had a fragmented understanding of how such trackers worked and their impact on people’s online experience. Roesner — an Allen School Ph.D. student at the time — worked with Kohno and Wetherall to develop a client-side method for detecting and classifying trackers according to how they interact with the browser. They analyzed tracker prevalence and behavior on the top 500 website domains, as identified by the now-defunct web traffic analysis firm Alexa Internet, examining more than 2,000 unique pages.

“We identified 524 unique trackers, some of which had sufficient penetration across popular websites to enable them to capture a significant fraction of a user’s browsing activity — typically around 20%, and in one case, as much as 66%,” Roesner recalled.

Roesner and her colleagues cataloged five types of tracker behavior, varying from the relatively benign, to the opportunistic, to the infuriating. The behaviors spanned analytics that are generally confined to a specific site, Google Analytics being an example; “vanilla” trackers, which rely on third-party storage to track users across sites for the purposes of additional analytics or targeted advertising, such as Doubleclick; forced, which include the dreaded popup or redirect that compels the user to visit its domain; referred, which rely on unique identifiers leaked by other trackers; and personal trackers, which engage in cross-site tracking based on a user’s voluntary visit to its domain in other contexts. Some trackers exhibit a combination of the above.

Despite the existence of multiple tools intended to give users more control, from third-party cookie blockers to “private” browsing mode, the team found those options insufficient for preventing certain trackers from following people across the web while maintaining any semblance of functionality. This was particularly true for popular social widgets by the likes of Facebook, Twitter, LinkedIn, Digg, and others that were embedded on a growing number of sites ranging from news outlets to online storefronts.

“While users could prevent some tracking, that was not the case for social widgets,” noted Roesner. “If a user was logged into a social media site like Facebook, for instance, their activity elsewhere on the web would be tracked — non-anonymously, I would add — even if they didn’t interact with the ‘like’ button embedded on those sites.”

For those who would prefer to cover their tracks while continuing to enjoy the convenience of interacting with social widgets on their terms, Roesner and her collaborators developed ShareMeNot. The browser extension took a bite out of social widgets’ ability to construct browsing profiles of users by only allowing activation of third-party tracking cookies when a user explicitly interacted with the “like,” “share,” or other relevant buttons; if a user visited a site but did not click on the social widgets, ShareMeNot stripped the cookies from any third-party requests to those trackers.

The team worked with an undergraduate research assistant in the lab, Chris Rovillos (B.S., ‘14) to refine ShareMeNot following the paper’s initial publication and address instances of the trackers attempting to circumvent the restrictions on cookies via other means. Instead of just blocking cookies, the new and improved version of the tool blocked tracker buttons altogether. In their place, ShareMeNot inserted local, stand-in versions of the buttons that users could click to either “like” a page directly or load the real button — putting users, not the trackers, in control. Roesner partnered with the nonprofit Electronic Frontier Foundation to incorporate ShareMeNot into the previously mentioned Privacy Badger, which remains an important tool for protecting users from intrusion by third-party trackers to this day.

The team’s work is notable for inspiring not only new technologies but also a new wave of researchers to focus on web tracking. One of those researchers, Umar Iqbal, followed that inspiration all the way to the Allen School.

“This is one of the seminal works in the space of web privacy and security. It had an immense influence on the community, including my own research,” observed Iqbar, a postdoc in the Security and Privacy Research Lab. “I extended several of the techniques proposed in the paper as part of my own doctoral thesis, from the measurement of online trackers, to their characterization, to building defenses. It was, in fact, one of the reasons I decided to pursue a postdoc with Franzi at UW!”

Roesner, Kohno and Wetherall were formally recognized at NSDI 2023 last month in Boston, Massachusetts. Read the research paper here.

Read more →

Single-cell genomics is revolutionizing biomedical research by enabling high-volume analysis of gene expression at the cellular level to understand the origins of disease and identify targets for potential treatment. To accelerate this progress, researchers are increasingly turning their attention to artificial intelligence (AI) tools to analyze these connections at scale. But the size and complexity of the resulting datasets, combined with noise and systematic biases in experimentation, make it difficult to build meaningful AI models from which to derive new biological insights.

Professors Su-In Lee and Sara Mostafavi of the Allen School’s Computational Biology group are working on new solutions to the problem, supported by two competitive grants from the Chan Zuckerberg Initiative’s (CZI) Data Insights program. The program supports the advancement of tools and resources that make it possible to gain greater insights into health and disease from single-cell biology datasets.

Lee directs the University of Washington’s AIMS Lab, shorthand for AI for bioMedical Sciences, where she and her collaborators develop explainable AI techniques for lifting the so-called black box on models to make them more transparent and interpretable in biomedical sciences and clinical settings. Newer deep neural network architectures used in single-cell genomics, such as transformers and graph neural networks (GNNs), are ripe for such tools. While they have been used to good effect by researchers investigating the mechanisms of gene regulation and cell identity in complex tissues across multiple single-cell datasets, how they arrive at their results remains shrouded in mystery. 

The CZI Data Insights grant will support a project led by Lee, working in collaboration with professor Jian Ma at Carnegie Mellon University, to fill that void by extending principled XAI methods, such as a new framework for computing Shapley values using a learned explainer model, to transformers and GNNs. The results will enable researchers to understand which features contributed to the models’ predictions — and to what extent.

“There is an urgent need for new, explainable AI techniques that can be applied to complex neural network architectures,” said Lee. “This approach will enable researchers to rigorously interpret these models to enable data-driven biological discoveries in single-cell regulatory genomics for which a “wave” of new datasets is expected and enhance our fundamental understanding of how a cell works.” 

A second CZI-funded project led by Mostafavi, working in collaboration with Lee, will support her efforts to develop methods for predicting how cells respond differently to various environmental factors. This direction extends Mostafavi’s previous research into the use of deep neural networks to predict when and how genetic variation between people leads to differences in disease susceptibility.

“Combining recent advances in AI with emerging single-cell datasets is a promising approach for understanding the role of genetic determinants of heritable diseases such as Alzheimer’s and cancer in rare or previously unknown cell populations,” explained Mostafavi, who is principal investigator on the project. “But we need to address issues of accuracy, scalability, and interpretability in the models in order to gain meaningful biological insights.”

Mostafavi and Lee’s awards are among three earned by University of Washington researchers in this latest cycle of CZI Data Insights grants. Allen School adjunct professor William Noble, professor of genome sciences at the UW, is part of a project to develop new computational methods that will significantly improve the quantitative accuracy of single-cell proteomics data.

Learn more about the CZI Data Insights grantees here. Read more →

The 1939 movie “The Wizard of Oz” opens in black and white. After a tornado sweeps up her Kansas home and drops it with a thud, Dorothy, the story’s protagonist, opens the front door, her dog Toto in tow. When she does, she’s greeted by a world of color. 

“Toto, I have a feeling we’re not in Kansas anymore,” she says, eyes wide. 

Allen School senior Matt Deitke is not from Kansas, nor has he been to the Land of Oz. Yet he experienced a similar revelation, minus the intervention from Hollywood or Mother Nature. When Deitke was in high school, he spent long hours using Adobe Photoshop to manually colorize images for personal projects. But the task was tedious and unavoidable, he said, a process to be endured rather than enjoyed. 

That changed when he encountered a different kind of technical wizardry, one that opened up a new world of color. Via artificial intelligence, the process could be automated. A black-and-white image of a Monarch butterfly, for instance, underwent metamorphosis before his eyes, the orange of its wings bursting into arresting, vibrant life.

“I was completely amazed,” Deitke said. “Witnessing the impressive results, it felt like I was experiencing pure magic.” 

Yet the laws behind this trick were governed by logic, not legerdemain. For the budding scientist, neither tornado nor Toto was needed. He wasn’t in “Kansas” anymore. 

“This eye-opening experience led me to realize the impact computer vision would have on the field of computer graphics,” he said. “It soon became clear that these AI techniques would transform industries far beyond design.”

While Deitke doesn’t hail from the Sunflower State, he spent his youth in the Midwest, growing up in a suburb of Chicago. There he tinkered with computer graphics, interface design and visualization, completing projects for Ohio State University and the University of Cincinnati while still in high school. The possibilities of AI led him to the University of Washington, where he quickly channeled his curiosity into practice. 

His first year brought several new experiences. As a freshman, he enrolled in a graduate computer vision course taught by Richard Szeliski, Steve Seitz and Harpreet Sawhney. At the time, Szeliski was revising his 2010 book “Computer Vision: Algorithms and Applications,” updating it to account for advances in deep learning. Deitke, not one shy to show his inquisitive side, wrote pages of comments to Szeliski on topics such as transformers and text-to-image generation. He asked probing questions, gave insightful suggestions and turned heads. 

“At some point I said, ‘Would you be willing to write a section of the book?’” Szeliski said. “He agreed, and there’s a whole chapter on the more advanced topics of deep learning that he wrote.” 

Deitke soon went on to author more impressive feats. Early in his time at the Allen School, he began working for The Allen Institute for AI (AI2), a global leader in advancing AI research, and became a full-time employee toward the end of his sophomore year. 

“UW is an exceptional place to do AI research,” Deitke said. “Particularly now that AI progress requires a lot of engineering and computational power.”

At AI2, he joined the Perceptual Reasoning and Interaction Research (PRIOR) team, the computer vision research group then led by Allen School professor Ali Farhadi. Now headed by Allen School affiliate associate professor Ani Kembhavi, PRIOR continues to innovate in the AI research space, focusing on vision-and-language research, embodied AI and common good research. 

One project Deitke recently completed, ProcTHOR, investigated scaling up the diversity of datasets used to train household robotic agents. He was lead author on the paper, which won an Outstanding Paper Award at the 2022 Neural Information Processing Systems (NeurIPS) Conference. 

“Training robots in the real-world is difficult and time consuming,” Deitke said. “An emerging alternative is to train robots in photorealistic video-game simulators to make training much faster.”

Prior to ProcTHOR, artists had to manually design spaces such as simulated 3D houses. Deitke proposed a generative function to sample diverse and realistic house environments. It worked brilliantly. 

“Training on the generated houses led to remarkably robust agents across several distributional shifts,” Deitke said. “We’ve still yet to hit a ceiling on how much further such a simple recipe can go.”

As it turns out, there’s no place like home. For Deitke, UW has been home for the past four years. With graduation nearing, he’s been weighing offers from several top doctoral programs, looking to continue his research and keep searching for that spark of “pure magic,” wherever it might be. 

“The field of AI is beginning to change the world,” he said. “It is incredibly rewarding being able to work on the cutting-edge of research and pushing the frontier of what’s possible in science and technology.” Read more →

SIGCHI, the Association for Computing Machinery’s Special Interest Group on Computer-Human Interaction, has honored four researchers with ties to the University of Washington with 2023 SIGCHI Awards. Allen School alum Nicola (Nicki) Dell (Ph.D., ‘15), a leader in applying technologies to safeguard victims of technology-enabled intimate partner violence (IPV), received a Societal Impact Award, while Dhruv (DJ) Jain (Ph.D., ‘22), received an Outstanding Dissertation Award for his work on technologies to enhance sound awareness for people who are deaf or hard of hearing. In addition, Megan Hofmann, a visiting Ph.D. student at the UW who taught at the Allen School, and Kai Lukoff, a recent alum of the UW Department of Human-Centered Design & Engineering, also received Outstanding Dissertation Awards — a testament to the UW’s far-reaching impact on human-computer interaction (HCI) education and research through its Design Use Build (DUB) group.

Dell’s work seeks to understand, build and deploy sociotechnical systems that benefit those who are underserved both in the United States and in resource-constrained regions of the world. She draws from qualitative and quantitative methodologies and engages with people in real-world settings as well as in academia, industry, government and non-governmental organizations. At the Allen School, Dell collaborated with the late professor Gaetano Borriello and professors Richard Anderson and Linda Shapiro on research that combines HCI, Information and Communication Technologies for Development (ICTD) and computer vision and machine learning, such as mobile camera-based systems to advance data collection and disease diagnosis in low-resource settings.

“Nicki’s work has always looked at the impact of digital technology on marginalized populations,” noted Anderson. “As a graduate student, she pioneered mobile applications in global health in domains such as rapid diagnostics and digitized data collection. She has now established herself as a leading researcher understanding the way that digital technologies tie into very sensitive situations, such as intimate partner violence. I am thrilled that her work is recognized by SIGCHI as she is highly deserving of the award.”

Upon graduation from the UW, Dell joined the faculty of the Jacobs Technion-Cornell Institute at Cornell Tech and the Department of Information Science at Cornell University. There, her efforts to improve digital safety and security for those who have experienced IPV have resulted in greater support for individuals affected by IPV and impacted both policy and legal discourse. In 2018, Dell and her Cornell colleague Thomas Ristenpart co-founded the Clinic to End Tech Abuse (CETA), whose mission is to address targeted attacks emanating from technology abuse.  

“Everyone should be free to use technology without fear of harm from abusive partners or others,” said Dell. “Survivors of abuse, stalking, or other mistreatment should have the support they need to keep themselves safe online and on their devices.”

Dell endeavors to understand both how survivors can stay safe and how abusers misuse technology. In 2017, she and Ristenpart undertook the initial research that would form the foundation on which they built CETA. Their paper, “A Stalker’s Paradise”: How Intimate Partner Abusers Exploit Technology, which won a Best Paper Award at SIGCHI 2018, described their findings from qualitative interviews conducted in New York City with those who had experienced technology enabled IPV. Their findings underscored how abusers threaten, harass, intimidate, monitor and harm victims by interacting with and compromising the victims accounts or devices through adversarial authentication. The authentication is often obtained as a result of the closeness between victim and abuser, but also through coercion, threats and violence. Dell’s subsequent work has explored care infrastructure for digital security in IPV to understand security support for those who have experienced technology enabled IPV as well as narrative justifications of intimate partner surveillance and tools and tactics of IPV through analyses of online forums.

Operating in New York City since 2018, CETA works directly with survivors of IPV to determine if someone is using technology to harm them and what they can do to stay safe. In parallel, CETA facilitates new research to understand how abusers can misuse technology, advocates for laws and policies that include better protections from technology abuse, and publishes resources for others who work to help survivors. At this time, their work has influenced legislation both in New York State and at the federal level. In December 2022, President Biden signed the Safe Connections Act into law. This legislation supports survivors’ requests to have themselves or those in their care removed from shared phone plans while retaining their phone numbers for uninterrupted connectivity. Other proposed legislation would require cellular providers to create strong privacy protection with regard to information about abuse, to eliminate difficult or trauma producing requirements for survivors, and to train employees about survivors’ rights.

“[Dell’s] work is exemplary in many regards, representing an unusually ‘full stack’ model of intervention and social impact,” wrote Neha Kumar, president of SIGCHI and a professor at the Georgia Institute of Technology, in the award announcement. “She has been the driving force in putting tech-related IPV abuses on the radar of companies, government, and HCI as a field; has offered direct and meaningful support to survivors; and has produced real-world changes that have begun to combat this pervasive and insidious problem.”

Dell is one of three recipients of this year’s SIGCHI Societal Impact Awards, including Shaowen Bardzell, a professor at Pennsylvania State University, and Munmun De Choudhury, a professor at the Georgia Institute of Technology. 

SIGCHI honored Jain, who completed his Ph.D. working with Allen School professor Jon Froehlich and HCDE professor and Allen School adjunct faculty member Leah Findlater, for his dissertation, “Sound Sensing and Feedback Techniques for Deaf and Hard and Hearing People.” That work, which was supported by a Microsoft Dissertation Research Grant and a Google CMD-IT LEAP Alliance Fellowship, focused on the design and evaluation of interactive systems to improve sound awareness for those who are deaf and hard of hearing (DHH). 

Jain takes a user centered approach to better understand sound awareness, sensing and technology preferences and needs of those who are DHH. After first evaluating the needs and preferences of those who are DHH, Jain employed an iterative approach in both the lab and the field to design, build and evaluate new systems that could support real-time sound recognition — informed in part by his own experiences as a DHH individual. 

“Dhruv’s dissertation exemplifies the use of end-to-end human-centered research to define and advance methods and tools for real-time sound recognition,” Froehlich expressed. “Fundamentally, his work advances our understanding of DHH people’s needs around sound recognition and provides technical solutions to support those needs.” 

Jain’s research led him to develop several such systems, including HoloSound, an augmented reality (AR) system that allows DHH individuals to receive a classification and visualization of sound along with speech transcription. Another project, HomeSound, explored how DHH people relate to sounds in the home, how they solicit and relate to feedback from home awareness systems, and what concerns arise with the use of these systems. Jain also developed a smartwatch app called SoundWatch that alerts people who are DHH to sounds in their environment.

Currently a professor at the University of Michigan, Jain builds on the research agenda that he developed during his Ph.D. work. He directs the Accessibility Lab, where he and his collaborators take a user-centered approach with the goal to make sound accessible to all people in all settings. Before the SIGCHI award, Jain received the Allen School’s William Chan Memorial Dissertation Award, which honors graduate dissertations of exceptional merit and is named in memory of the late graduate student William Chan. 

For her award-winning dissertation, “Optimizing Medical Making,” Hofmann worked with professor Jennifer Mankoff, who joined the Allen School faculty from CMU, on an interdisciplinary approach to the application of digital fabrication in health care. Combining programming languages, systems and ethnographic methodology, Hofmann introduces new ways that digital fabrication can be a tool to design assistive and medical devices informed by the domain expertise of people with disabilities and the medical knowledge of clinicians. This groundbreaking work has already had real-world influence in the application of clinical review processes to the production of personal protective equipment (PPE) during the COVID-19 pandemic.

Hofmann is now a professor at Khoury College of Computer Sciences at Northeastern University, where she directs the Accessible Creative Technologies (ACT) Lab. While at the UW, Hofmann taught the Allen School’s e-textiles course and was a member of the Make4all Group and Center for Research and Education on Accessible Technology and Experiences (CREATE).

The third UW-affiliated researcher to earn an Outstanding Dissertation Award, Lukoff explores the concept of user agency in a world where application design patterns strive to capture user attention, often without regard for the user’s well-being. His dissertation, “Designing to Support Sense of Agency for Time Spent on Digital Interfaces,” co-advised by HCDE professor and Allen School adjunct faculty member Sean Munson and Information School professor and Allen School adjunct faculty member Alexis Hiniker, goes beyond the concept of “screen time” to offer insights into how users’ experiences with digital interfaces can be meaningful or meaningless depending on the context and goals. Lukoff built a mobile app, SwitchTube, to investigate design features that allowed users a greater sense of agency when consuming online video content. He continues to build upon this line of inquiry at Santa Clara University, where he is a professor and director of the Human-Computer Interaction Lab.

Congratulations to this year’s SIGCHI award recipients! Read more →

Allen School undergraduates Jan Buzek and Nuria Alina Chandra are among five University of Washington students to be named 2023 Goldwater Scholars by the Barry M. Goldwater Scholarship and Excellence in Education Foundation. The Goldwater Scholars program recognizes and supports outstanding students who intend to pursue careers in mathematics, engineering and the natural sciences. 

Buzek is a junior studying computer science and mathematics who counts Allen School professor Paul Beame among his mentors. His research focuses on number theory and cryptography, and he and his collaborators have investigated finding twin smooth integers — very large consecutive integers with prime factors that are as small as possible. His team recently completed a project that uncovered new, more efficient algorithms to find these integer pairs. 

An avid hiker, Buzek remembers trying to factor large numbers in his head while trekking through nature as a child. He would make a game of guessing factors without having to try a lot of primes. 

For Buzek, work and play have coalesced, and the game never ended. 

“I was fascinated by the mysterious structure present in such a seemingly simple object — integers and multiplication,” he said. “This problem of factoring has stayed with me throughout my studies.”

This year, Buzek is studying abroad at the University of Heidelberg and ETH Zürich. He plans to pursue a doctorate in cryptography. 

“This recognition is great motivation for me to further pursue my research, and increases my enthusiasm for the role of cryptography in today’s world,” Buzek said. “I would like to thank all of my mentors, especially my recommenders Michael Naehrig, Stefan Steinerberger and Paul Beame for their support and the motivation they have given me to pursue my interests.”

Chandra is a senior majoring in computer science and minoring in global health. As part of her work with professor Sara Mostafavi in the Allen School’s Computational Biology Group, she uses deep learning to study regulatory genetics in immune cells. She has also conducted chronic pain research at Seattle Children’s Hospital with Dr. Jennifer Rabbitts and geometric combinatorics research with professor Rekha Thomas in the UW Department of Mathematics. 

As a teenager, Chandra started to have immune-related health problems. Her own experiences led her to pursue biomedical research at UW and then at Seattle Children’s Hospital. 

“When trying to understand my own health, I found that the immune system’s functions and dysfunctions are poorly understood,” she said. “I saw research as a way to help prevent and cure diseases that I had a personal connection with.”

But while at UW, her academic interests broadened. She was exposed to computer science for the first time, she said, and the experience kindled her passion for algorithmic approaches to problem solving. She switched her major to computer science, seeing a path where her fields of study could overlap. 

“I became interested in machine learning and deep learning because I saw what a powerful potential impact it has for improving our understanding of human health,” she said. “My computational biology research in the Mostafavi Lab has allowed me to use my interest in computer science to work toward understanding the diseases that I care deeply about.”

Her research is ongoing. The goal, she said, is to find a deep learning model that provides a clearer understanding of immune diseases and the genetic mechanisms behind them. 

“Gaining this type of understanding of how immunological diseases work will also help researchers develop preventative treatments,” she said, “so the disease never develops in the first place.”

Last year, Chandra was named to the 2022 class of the Husky 100. She plans to pursue a doctorate in computer science, focusing on the intersection of machine learning, computational biology and algorithms research.

“It makes me feel very proud to have my work as an undergraduate researcher acknowledged by this award,” Chandra said. “I have been fortunate to find many exceptional mentors at UW who have supported my research journey. I want to thank Jennifer Rabbitts, Rekha Thomas, Alexander Sasse and Sara Mostafavi for dedicating their time and energy to helping me grow as a researcher.”

Including Chandra and Buzek, a total of five UW students were named Goldwater Scholars for 2023. The other honorees were Abigail Burtner, a junior majoring in biochemistry and minoring in data science and chemistry; Meg Takezawa, a junior majoring in biochemistry; and Peter Yu, a junior majoring in civil and environmental engineering. They were selected from a pool of more than 5,000 students from across the U.S. 

Previous Allen School recipients of the Goldwater Scholarship include Alex Mallen in 2022, Parker Ruth in 2020, and Nelson Liu and Kimberly Ruth in 2018.  

Learn more about the Goldwater Scholars program here. Read more →