Allen School News

A team of University of Washington and NVIDIA researchers developed a system that can help make large language models (LLMs) faster and more adaptable. The foundation of LLMs are built on transformers, a neural network architecture driven by attention mechanisms that help artificial intelligence focus on relevant and important information. As these LLMs evolve and find new applications in diverse fields, however, optimized lower-level implementation, or GPU kernels, become necessary to help prevent errors and ensure low-latency inference.

The researchers introduced FlashInfer, a versatile LLM inference kernel library that is open source as well as highly optimized and adaptable to new techniques including key-value, or KV, cache reuse algorithms. They presented their research titled “FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving” at the Eighth Annual Conference on Machine Learning and Systems (MLSys 2025) in May and received a Best Paper Award.

“FlashInfer proves what’s possible when academia, industry and the open-source community innovate together — ideas jump from whiteboard to GPU kernels at lightning speed,” said lead author and Allen School Ph.D. student Zihao Ye, who completed part of the research during his internship at NVIDIA. “That shared, rapid feedback loop lets us iterate, refine and ship breakthrough inference speedups that keep pushing the limits of large language models.”

FlashInfer is able to address major challenges that LLMs face in memory access and heterogenous hardware. The attention engine uses a unified block-sparse format, where data is stored and organized in dense blocks making it easier to navigate, to optimize KV cache storage and composable formats. FlashInfer can also adapt to various attention mechanisms through just-in-time compilation, while the dynamic load-balanced scheduling framework effectively and efficiently handles different workloads. Compared to other state-of-the-art LLM serving solutions, the researchers found that FlashInfer significantly boosted kernel performance across diverse inference scenarios. Already, FlashInfer has been integrated into several leading LLM serving frameworks, including SGLang, vLLM and MLC Engine. 

Additional authors include Allen School professors Stephanie Wang, Baris Kasikci, Arvind Krishnamurthy and Luis Ceze, who is also VP of AI Systems Software at NVIDIA; Vinod Grover of NVIDIA and Wuwei Lin, previously at NVIDIA and now at OpenAI; Carnegie Mellon University professor Tianqi Chen (Ph.D., ‘19) and Ph.D. student Ruihang Lai; Lequn Chen (Ph.D., ‘24) at Perplexity; and Yineng Zhang at SGLang.

Read the full paper on FlashInfer.

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On Friday, June 13, an estimated 5,000 friends, family, faculty and staff packed the Alaska Airlines Arena in the University of Washington’s Hec Edmundson Pavilion to celebrate the Allen School’s graduating class of 2025. While the date invited superstition, the evening was full of jubilation as roughly 800 graduates collected their commemorative diplomas, flipped their tassels and made the transition from Allen School students to Allen School alumni.

“It feels like yesterday that we were welcoming you to the Allen School. And tonight we celebrate all you have accomplished here,” said Magdalena Balazinska, professor and director of the Allen School. “We are extremely proud of you. We are proud of all you have accomplished and can’t wait to see what you accomplish next!”

‘True impact doesn’t come from what you accumulate, but what you contribute.’

That was the message graduation speaker Trish Millines Dziko — co-founder and executive director of the Technology Access Foundation (TAF), computer scientist and proud Husky mom — delivered to the graduates as they contemplate the next stage of their journey. She was welcomed to the stage by professor Ed Lazowska, who exercised one of his last official acts in his 48th and final year as an Allen School faculty member by introducing Millines Dziko, calling her “a friend of mine and a hero of mine.”

“TAF uses STEM as a tool for social change,” Lazowska said during his introductory remarks. “And in its nearly 30 years, TAF has changed the lives of tens of thousands of students in our area.”

Technology as a tool for social change was a recurring theme in Millines Dziko’s speech — but, she noted, not always for the better. With more than 60% of the nation’s wealth concentrated in the top 10% of households, while the bottom 50% hold just 5%, Millines Dziko suggested that the world needs “more people who care enough to fix what’s broken.”

“You can use your critical thinking, problem solving, ideation, creation and leadership skills to build solutions to some of the most pressing problems like homelessness, generational poverty, public education, the environment and health care,” she said.

Whatever path they decide to pursue, the graduates will not be able to rely on their technical skills alone. Saying hard work and good grades were “just the beginning,” Millines Dziko advised the graduates to prioritize building relationships by showing themselves to be capable, reliable, truthful, empathetic and accountable. Developing these qualities would enable them to build social capital that, she noted, they could use along with technology and engineering “as the vehicle to creating a better future for everyone.”

“I hope you pursue purpose over profit, and let your values lead your vision. Please create solutions that lift people up and improve communities,” Millines Dziko urged. “Because in the end, changing the world isn’t about being remembered — it’s about doing things worth remembering.”

Alumni Impact Award: Nicki Dell (Ph.D., ‘15)

Nicki Dell is a shining example of what Millines Dziko talked about. Each year, the Allen School recognizes one or more alumni who have used their Allen School education to change the world. Since her own graduation a decade ago, the 2025 Alumni Impact honoree has been “doing things worth remembering” in the form of technologies that serve the needs of overlooked communities such as home health care workers and people experiencing intimate partner violence. Dell worked with professors Linda Shapiro and the late Gaetano Borriello on her way to earning the 500th doctoral degree awarded by the Allen School before taking up a faculty position at Cornell Tech.

In his remarks, presenter Shwetak Patel, professor and associate director of development and entrepreneurship, highlighted Dell’s leadership of the Clinic to End Tech Abuse (CETA) among her many contributions — contributions that had already earned her a SIGCHI Societal Impact Award as well as a MacArthur Foundation “genius grant.”

“She deeply partners with affected communities, and then builds systems and interventions that make our computer-mediated world safer and more equitable for everyone,” Patel said.

Recognizing student leadership and service

So many members of the Allen School’s undergraduate student body — which now numbers more than 2,200 — contribute to activities and events that enrich the student experience, it is difficult for the Undergraduate Student Services Team (USST) to choose the recipients of this and the Outstanding Senior awards. But choose, they did; after USST Director Crystal Eney invited all graduating students who were involved in outreach, community building and mentorship to stand and be recognized, the following individuals were singled out for their contributions to the Allen School community and the field of computing.

Undergraduate Service Awards

Honoree Kianna Roces Bolante was described as the “epitome of service” in her role as chair of the student group Computing Community, or COM^2, overseeing school-wide events and activities that build community among the undergraduate majors in the Allen School. In her two years at the helm, she earned a reputation — and universal appreciation — for interacting with the community she serves with empathy, intention and a commitment to inclusion. “Her leadership is a labor of love, and she is an inspiration to so many students on campus,” said Chloe Dolese Mandeville, senior assistant director for student engagement and access at the Allen School.

Joo Gyeong Kim was recognized for her foundational leadership in shaping the Allen School’s Changemakers in Computing (CIC) program that engages rising juniors and seniors in high school in learning about technology, society and justice. “As one of the founding mentors, she brought a thoughtful, mission-driven approach that helped define the program’s values and direction,” Dolese Mandeville said. She leaned heavily on that approach when she took on temporary leadership of the entire program one summer while both directors were out sick. Known as a steady and compassionate leader, Kim’s impact extends to the entire CIC community.

Anjali Singh was honored for her dedicated service in multiple roles with the Student Engagement & Access team. Starting with the Allen School Ambassadors — a team of current majors who engage middle and high school students in learning about computer science via school visits and field trips — Singh used her warmth and knack for storytelling to inspire students. She quickly rose to the position of lead ambassador before going on to help launch a new team of Student Recruitment Representatives. Having served hundreds of prospective students along the way, “her dedication, advocacy for accessible pathways into computing and long-standing service have left a lasting legacy,” Dolese Mandeville said.

Zhengyu Zhang was recognized for his service to the robotics research community in the Allen School. His contributions include the mastery of complex simulation tools, one-on-one mentorship and the development of an open-source repository that is used by researchers in multiple labs. Known for being generous with his time and willing to support others regardless of their skill level, Zhang’s collaboration, service and mentorship has, noted Dolese Mandeville, “enabled the success of countless students and researchers, from undergraduates to postdocs.”

Outstanding CSE Senior Awards

Balazinska called Bolante back to the stage to collect one of four awards designed to recognize students who demonstrate superior scholarship and leadership potential — qualities that Bolante has epitomized during her time at the Allen School. In addition to her aforementioned service contributions, she has also contributed to research supporting people with Parkinson’s disease, language preferences in disability communities and computer science education. For the latter, she developed a suite of six social computing modules which she piloted with more than 1,400 local high school students. Last year, she received a CRA Outstanding Undergraduate Researcher Award from the Computing Research Association — one of four in the nation — for her work.

Eujean Lee was recognized for her outstanding academic achievements and research contributions, for which she was also nominated for a College of Engineering Dean’s Medal for Academic Excellence. As an undergraduate researcher in the Makeability Lab, Lee co-authored two papers on the use of augmented reality and computer vision to make sports more accessible to people with low vision — one of which earned a Best Paper Award at the Workshop on Inclusion, Diversity, Equity, Accessibility, Transparency and Ethics in Extended Reality (IDEATExR). Lee also served as vice president of the Korean Job Search Association, helping to connect students with career opportunities and resources.

Honoree Kenneth Yang’s research spans software engineering, neuroscience and computer graphics. He contributed to a paper presenting a suite of new, more reliable version control merge tools for shared repositories such as Git that was published at the IEEE/ACM International Conference Automated Software Engineering (ASE) — one of the top conferences in the field. He also developed new software tools for automating electrophysiology experiments to accelerate brain research and open up new avenues of experimentation. Yang previously received a CRA Outstanding Undergraduate Researcher Award honorable mention for his work.

Andre Ye was recognized for blending technical innovation with humanistic insight in research that spans computer vision, machine learning and human-AI interaction. In the Allen School’s Social Futures Lab, he developed a framework to account for human uncertainty in medical image segmentation models that earned an honorable mention at the Conference on Human Computation and Crowdsourcing (HCOMP). He has also investigated the influence of linguistic and cultural differences on image captioning models and the use of language models to support critical thinking. Ye has earned multiple accolades, including a Paul & Daisy Soros Fellowship and a College of Arts & Sciences Dean’s Medal. He will pursue his Ph.D. at MIT in the fall.

Celebrating scholarly achievement

The path to a doctorate involves years of intensive, original research — as the 52 newly-hooded Ph.D. graduates seated on the floor of the arena could attest. But they are not the only Allen School students who make original contributions to the field on their way to earning a degree; a significant number of bachelor’s and fifth-year master’s students know their way around a lab, as well. Professors Leilani Battle and Maya Cakmak, co-chairs of the Allen School’s Undergraduate Research Committee, had the pleasure of highlighting several of them with Best Senior Thesis or Outstanding Master’s Thesis awards.

Best Senior Thesis (Winner)

Winner Andrew Shaw was recognized for his thesis titled “Agonistic Image Generation: Unsettling the Hegemony of Intention,” which was the result of a collaboration with Outstanding Senior honoree Andre Ye. Under the guidance of Allen School professors Ranjay Krishna and Amy Zhang, Shaw combined computer science and philosophy to develop a novel image generation interface that actively engages users with competing visual interpretations of their prompts, in consideration of the sociopolitical context, to facilitate user reflection. The paper was accepted to the ACM Conference on Fairness, Accountability, and Transparency (FAccT).

Best Senior Thesis (Honorable Mention)

In his thesis titled “SAM2Act: Integrating A Visual Foundation Model with A Memory Architecture for Robotic Manipulation,” honorable mention recipient Haoquan Fang introduced new models that achieved state-of-the-art performance on existing benchmarks for robotic manipulation, plus a new benchmark for testing robots’ ability to act based on past information. Fung completed this work under the supervision of Allen School professor Dieter Fox and presented his results at the International Conference on Machine Learning (ICML) and the Conference on Computer Vision and Pattern Recognition (CVPR).

Outstanding Master’s Thesis (Winner)

Winner Hayoung Jung’s thesis, “Towards Inclusive Technologies: Examining Social Values and Harms in Large-Scale Sociotechnical Systems,” introduced technical approaches grounded in the social sciences to measure and mitigate human biases and social harms perpetuated by generative large language models and algorithmically driven platforms such as YouTube. Jung completed this work, which was published in multiple top-tier conferences, under the guidance of Tanu Mitra, a professor in the UW Information School and adjunct faculty member in the Allen School. Jung will begin his Ph.D. in computer science at Princeton University in the fall.

Outstanding Master’s Thesis (Honorable Mention)

In his thesis titled  “On the Existential and Strong Unforgeability of Multi-Signatures in the Discrete Log Setting,” honorable mention recipient Sela Navot advanced new theories and protocols for generating secure digital signatures in distributed, multi-party scenarios such as blockchain systems. Navot completed this work, which was published at the International Conference on the Theory and Application of Cryptology and Information Security (Asiacrypt), under the guidance of Allen School professor Stefano Tessaro.

Honoring excellence in teaching

Bob Bandes Memorial Awards

The Bob Bandes Memorial Award for Outstanding Teaching, which is named in honor of a graduate student who died in a skydiving accident in 1983, recognizes exceptional teaching assistants (TAs) who go above and beyond in service to the thousands of students who take Allen School courses each year. Over the past year, roughly 650 undergraduate or graduate students served as TAs; among those, nearly 250 individuals were nominated for Bandes Award recognition via over 600 nominations submitted by Allen School faculty and students.

Winner Naama Amiel served as a TA for CSE 351: The Hardware/Software Interface, no fewer than six times before her latest TA assignment with CSE 451: Introduction to Operating Systems. According to one nominator, “Anyone that talks to her can explain and help others struggling with the same things, so she creates a chain of learning that has impacts far beyond her conversations and office hours.”

Fellow winner Antonio Ballesteros was honored for his kindness and patience in meeting students where they are in his role as TA for two courses — once for CSE 391: System and Software Tools, and three times for CSE 331: Software Design and Implementation. “In every interaction with Antonio as a student, it is clear that he deeply cares about every student’s learning and experience in the course,” one nominator said.

The third and final winner, Amal Jacob, served as a TA for CSE 344: Introduction to Data Management a total of six times, for five different instructors. Known as patient, friendly, professional and dedicated, Jacob earned the appreciation of instructors for routinely picking up extra responsibilities — often before they even realized there were gaps that needed filling — and was heralded by at least one student nominator as “one of the best TA’s I have had in the Allen School.”

The Allen School also recognized three TAs with honorable mentions. Elizabeth Shirakian was a TA nine times for the Allen School’s revamped introductory programming course series, specifically CSE 121 and CSE 122, and will be the instructor for the summer offering of CSE 122. Megan Wangsawijaya was a TA multiple times for CSE 390T: Transfer Admit Seminar that helps newly arrived transfer students acclimate to the Allen School, as well as CSE 390Z: Mathematics for Computation Workshop, a companion to the Allen School’s Foundations of Computing course. Last but not least, Ph.D. student Zhihan Zhang earned “rave reviews” for his support of student teams enrolled in the CSE 475: Embedded Systems Capstone course.

Undergraduate Teaching Awards

Bolante presented the 2025 Undergraduate Teaching Awards in her capacity as chair of COM^2, the largest Allen School student organization that represents all undergraduate majors. 

“As we celebrate the class of 2025, it’s worth remembering that none of us reached this stage alone,” Bolante said. “Educators do more than teach; they support us, inspire us and help shape the paths we take.”

Bolante described the first honoree, Ruth Anderson, as a “powerhouse” within the Allen School who has made a lasting impact on students as well as TAs. “In every class she teaches, Ruth creates a clear and supportive environment where students feel empowered to engage with complex material and build lasting understanding,” observed Bolante, noting that her work with TA’s elevates the quality of teaching across the school. 

Anderson’s fellow honoree, Lauren Bricker, was Bolante’s first professor by way of the Allen School Scholars Program — making the presentation of this award especially meaningful. “Lauren brings warmth, enthusiasm and genuine care to absolutely everything she does…She creates inclusive spaces where students feel supported and encouraged to grow,” Bolante said. “Through her tireless support and advocacy, Lauren continues to inspire and uplift our community.”

Watch the Allen School graduation video on YouTube, and read GeekWire’s coverage of Millines Dziko’s graduation speech.

Congratulations to the Allen School Class of 2025! In the words of Trish Millines Dziko, “Go out and build a life that matters!”

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Since graduating from the Allen School, Nicki Dell (Ph.D., ‘15) has focused on using technology to “make our computing-mediated world safer and more equitable for everyone.” Her work combines the fields of human-computer interaction (HCI) and computer security and privacy to improve the lives of overlooked communities, specifically those experiencing intimate partner violence (IPV) and home health care workers.

For her contributions, the Allen School recognized Dell with the 2025 Alumni Impact Award, honoring former students with exceptional records of achievement. 

“This award is incredibly meaningful,” Dell said. “Whether developing mobile health tools in low-resource settings or building interventions to protect survivors of intimate partner violence from technology-facilitated harm, I learned at UW that impact isn’t just measured in lines of code or papers published — but in trust earned, dignity upheld and lives made a little better.”

During her time at the Allen School, Dell worked with the late professor Gaetano Borriello and professors Richard Anderson and Linda Shapiro on research that addresses the needs of those in low-resource settings. Growing up in Zimbabwe, she saw how limited resources and poor infrastructure created daily challenges. Dell designed a system that integrates Open Data Kit Scan, a mobile app that digitizes data from paper forms, into the community health worker supply chain in Mozambique. In her dissertation, Dell developed a mobile camera-based system to help improve data collection and disease diagnosis in low-resource environments. After graduating as the Allen School’s 500th Ph.D. student, Dell became a faculty member at the Jacobs Technion-Cornell Institute at Cornell Tech and Cornell University’s Department of Information Science.

“My time at the University of Washington was transformative,” Dell said. “When I began my Ph.D. journey, I never imagined the path it would lead me on — not just through the world of academic research, but into the lives and stories of people who are too often overlooked by the tech industry.”

At Cornell Tech, one line of Dell’s research has focused on mitigating technology-facilitated abuse experienced by survivors of IPV. She found that abusers threaten, harass, intimidate and monitor victims using adversarial authentication techniques to compromise victims’ accounts or devices. Dell and her collaborators also analyzed more than 500 posts in public online forums where potential perpetrators discussed strategies and justification for surveilling their partners. Building off of her research, Dell co-founded the Clinic to End Tech Abuse (CETA). Trained CETA volunteers work directly with survivors of IPV to mitigate any technology-related abuse they are experiencing, such as checking devices for spyware and providing other privacy and safety information and guidance. Her work has informed legislation, including the Safe Connections Act of 2022, upholding survivors’ requests to have themselves or those in their care removed from abusers’ shared phone plans while retaining their phone numbers. Over the years, her work has received eight paper awards and the 2019 Advocate of New York City Award.

Another line of Dell’s research investigates how technology can support home health care workers, who are some of the most under-resourced among the medical workforce. As the director of technological innovation at the Initiative on Home Care Work in the Center for Applied Research on Work (CAROW), she co-leads a multidisciplinary team of scientists, scholars and physicians aiming to improve patient outcomes and working conditions for home health care workers. For example, Dell and her collaborators designed interactive voice assistants, similar to Amazon’s Alexa, that can help home health aides manage day-to-day tasks or give guidance during medical assessments such as monitoring for leg swelling associated with heart failure. She also explored how computer-mediated peer support groups can benefit home health care workers, as well as how technology can help account for all the invisible, or unnoticed, work that these aides do for patients.

In addition to receiving this year’s Alumni Impact Award, Dell was awarded a 2024 MacArthur Foundation Fellowship, also known as the “genius grant.” Her work has also earned her the 2023 SIGCHI Societal Impact Award and a 2018 National Science Foundation CAREER Award.

“I’m immensely grateful for the mentors who challenged and guided me, chiefly among them Gaetano Borriello, whose guidance I carry with me and who is still profoundly missed,” Dell said. “I’m also grateful for the peers who inspired and encouraged me, for the broader Allen School community that cultivated in me both a rigorous technical foundation and a deep sense of purpose and for the communities I’ve had the privilege to work alongside.”

Dell will be formally honored at the 2025 Allen School graduation celebration on June 13. Read more about the Alumni Impact Award.

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As part of a multiyear initiative, the Allen School reimagined the introduction to programming course series with the goal of better serving the widest range of students across the University of Washington. Since its launch in 2022, CSE 121, 122 and 123, collectively known as the CSE 12X series, have enrolled thousands of students each year, serving as a gateway into computer science and as an essential part of UW’s general education for the entire campus. 

Building a new course series from the ground up was no small feat, but a herculean team effort from many people in the Allen School. The nominated team – lecturer Kasey Champion and professors Elba Garza, Miya Natsuhara, Hunter Schafer and Brett Wortzman – had central roles, including co-teaching the pilot offerings of the courses.

The UW recognized the team behind this transformation with this year’s Distinguished Team Teaching Award as part of the 2025 Awards of Excellence — one of the University’s highest honors, recognizing outstanding alumni, faculty, staff, students and retirees whose achievements support the UW mission. 

“We are thrilled to see our hard work recognized, and I hope we can keep doing what we’re doing: creating a welcoming environment where students of all computing backgrounds and experiences can thrive,” Wortzman said. 

Changing directions

Prior to the CSE 12X series, UW students interested in computer programming would take CSE 142 and CSE 143. These popular courses sparked many students’ interest in computer science, including Natsuhara, who went on to become a teaching assistant (TA) for them. 

But after many years since its introduction in 2004, it was time for a change. 

The previous courses were designed during a time when few students came to the UW with any programming experience. Over the years, however, more students had access to computing classes in high school such as Advanced Placement classes, and the experience level of the students coming into the introductory courses started to vary. At the same time, the field itself had changed. Computer science is a fast growing field, and over two decades, new methods for teaching programming had emerged. 

“It’s important for our curriculum in general to be reviewed every so often to make sure that we’re keeping up with things in terms of content and what kind of teaching is effective,” Wortzman said. “The student population was also changing, and it was time to respond to that.”

The new CSE 12X series design included a number of fundamental changes — starting from the top. Instead of two introductory classes, the material is spread across a sequence of three courses, and students can start at whichever one they feel comfortable in. To help students choose, the team created a guided self-placement tool. The tool is not an exam; it asks students to describe their confidence with various programming topics, test out some sample problems (and see the answers) and then recommends which course would be right for them. 

So far, the course recommendations have been helpful. Across the Winter, Spring and Autumn 2024 quarters, only 3% of students switched from one course in the sequence to another. 

“One of the goals was to offer more points of entry,” said Natsuhara, who received her bachelor’s degree in 2018 and her master’s degree in 2020 both from the Allen School. “It’s created a healthier learning environment, especially for the CSE 121 course. I don’t want students who have never programmed before to feel intimidated that their classmates are talking about the Python apps they’ve coded. Now, those more advanced students can skip ahead in the sequence and everyone is more likely to be around others at the same experience level.”

In the classroom

The team also updated the structure of the courses themselves. Each four-unit course now features two lectures and two sections guided by TAs per week, compared to three lectures in the previous sequence. With this format, each section only covers the previous lecture’s material, so TAs do not have to rush through topics from multiple lectures. Professors introduce new concepts in lectures, and these smaller sections give students the supportive space for practicing problems, which is “where the real learning happens,” Wortzman noted.

In addition, lectures are paired with short pre-class materials that introduce key concepts and provide practice with the new topics. This pre-work, which should take students about 30 minutes to complete, allows professors to use class time for answering questions, running activities and discussing more advanced applications.

By spreading out the content over three quarters, it gave lecturers the time and space to explicitly teach students important skills such as how to debug and fix problems with their code. Previously, students were expected to either know those skills implicitly or learn it on their own time, Natsuhara explained. 

The team revamped the curriculum to reflect not just the variety of student skill levels, but also intended majors. In Autumn 2024, for example, students from more than 70 majors enrolled in one of the CSE 12X courses. Instead of having students learn by solving traditional programming puzzles, the team wanted to appeal to this broad range of student interests by highlighting how programming can be used to solve real-world problems across different disciplines.

One of Natsuhara’s favorite assignments asks students to implement an algorithm that prioritizes patients in an emergency room based on factors such as age, pain level or insurance status. Despite being well-intentioned, the algorithm is intentionally flawed and does not treat patients equitably. Each assignment has a reflection component asking students to grapple with how that algorithm made them feel, how it could be improved and what are some of the unintended consequences. 

Other assignments follow similar veins including implementing algorithms for allocating disaster relief, generating computer-based election forecasts or identifying trends in social media posts.

“We’re helping our students wrestle with the idea that programming and computer science is not an amoral field — there are moral and ethical implications for these things and we should care about them,” Wortzman said.

The team also updated their grading policies to help students master the material. First, instead of starting at 100% and deducting points for inaccuracies like in traditional grading, the courses use mastery grading concepts such as coarse-grained evaluations that assess students on how well they demonstrate their understanding of the key ideas. Second, students are able to learn from their mistakes and resubmit assignments for an updated grade. This system incentivizes students to keep learning and working because “learning does not stop once an assignment is turned in,” Wortzman explained. 

These policies have already helped students find success in their courses. During the 2023 calendar year, only about 1% of students in a CSE 12X course were retaking the class compared to almost 8% in 2018 under the previous CSE 14X series.

After the team built the new introductory series — course structure, curriculum and even grading policies — from the ground up, they expected some pushback or major bumps in the road. The rollout, however, “appeared amazingly smooth,” said Dan Grossman, Allen School professor and vice director. 

“The nominated team members acted as shock absorbers, and the fact that the new course rollout was such a success and felt so smooth is a great testament to what they pulled off and how hard it was,” Grossman said. 

However, none of these efforts would be possible without the help of the TA community and countless others supporting the course instructors and participating in the design. This project was also supported by funding from the Center for Inclusive Computing (CIC) at Northeastern University.

“The task of launching the new courses was enormous, and we could not have done it without the massive army of undergraduate TAs that helped us put it together and keep it running to this day,” Natsuhara said. “We leaned on TAs and gave them more autonomy and responsibilities than we have previously done, and they stepped up in a really big way. We are still making iterations and improvements to the courses, and their continuous work deserves recognition as well.”

Natsuhara is not the only alum on the team; her colleague Schafer earned both his bachelor’s and master’s in computer science from the Allen School in 2016 and 2018, respectively.

Other members of the Allen School community were also nominated for this year’s UW Awards of Excellence. For the Distinguished Staff Award, fiscal specialists Emily Miller and Bree Siegel were nominated for their work in payroll, senior grants manager Stephanie McConnel was nominated as a member of the Collaborative for Research Education (CORE) training team and Vani Mandava, head of engineering for the UW’s Scientific Software Engineering Center in the eScience Institute, was nominated as part of the Post-award Dashboard Team. Director of Information Technology Aaron Timss was also nominated in the Career Achievement category, recognizing individuals for their demonstrated excellence throughout their years of service to the UW.

Read more about the 2025 UW Distinguished Team Teaching Award.

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Each year, the Association for Computing Machinery (ACM) recognizes the best Ph.D. dissertations in computer science with its ACM Doctoral Dissertation Award. In the 2024 competition, two of the recognized dissertations were the work of Allen School students: award winner Ashish Sharma (Ph.D., ‘24), now a senior applied scientist at Microsoft, and honorable mention recipient Sewon Min (Ph.D., ‘24), a research scientist at the Allen Institute for AI (Ai2) and incoming faculty member at the University of California, Berkeley.

Both Sharma and Min contributed to advances in artificial intelligence, albeit in different domains — highlighting both the variety and quality of AI research in the Allen School.

For his dissertation titled “Human-AI Collaboration to Support Mental Health and Well-Being,” Sharma devised ways to address a fundamental challenge in health care by leveraging AI to make high-quality mental health support available to more people. Meanwhile, in her dissertation titled “Rethinking Data Use in Large Language Models,” Min addressed fundamental challenges in natural language processing (NLP) by developing a new class of language models (LMs) and alternative approaches for how such models are trained. Min also earned the inaugural ACL Doctoral Dissertation Award from the Association for Computational Linguistics for this work.

Ashish Sharma: “Human-AI Collaboration to Support Mental Health and Well-Being”

Therapy can be an effective tool for supporting those with mental health challenges, but barriers such as an ongoing shortage of clinicians, high costs as well as stigma with seeking care can limit access. Instead of fully replacing therapists and clinicians with AI, given the significant risks inherent in this domain, Sharma proposes an alternative: he developed two novel human-AI collaboration systems designed to augment, rather than replace, human providers.

“Augmenting mental health interventions with AI and NLP-based methods has the potential to provide scaffolding that could make quality mental health care accessible to all,” said Sharma,  who completed his dissertation as part of the Allen School’s Behavioral Data Science Group. “By carefully designing human-AI collaboration that is grounded in psychology expertise to truly understand the complexities of mental health, human behavior and user needs, and is rigorously tested for safety and effectiveness, we can empower both those seeking help and those providing it.”

Sharma introduced reinforcement learning-based methods that can understand, measure and give feedback on how empathy is expressed in online peer-to-peer mental health support platforms. While many peer supporters are well-intentioned in helping those who reach out, they may be untrained and unaware of key psychotherapy skills such as empathy that can foster more effective conversations. He then leveraged and evaluated these methods in a randomized trial of 300 real-world peer supporters from TalkLife, one of the largest, global peer support platforms, and found that the AI-based feedback helped peer supporters express empathy more effectively in their conversations. The research received the Best Paper Award at The Web Conference 2021.

Human-AI collaboration can also enhance the accessibility and engagement of self-guided mental health interventions. These “do-it-yourself” methods to learn and practice coping skills are often cognitively demanding and emotionally triggering, making it difficult to implement them on a wider scale, Sharma explained. Building on psychological and cognitive science theories, he developed human-centered NLP methods to help “debug” human thought and support people through the process of cognitive reframing – that is, identifying and overcoming negative thoughts. In a randomized study of more than 15,000 participants, Sharma showed that the system helped participants reframe negative thoughts and informed psychology theory about the processes that lead to positive outcomes. He deployed this system at Mental Health America, which provides mental health tools and resources, and it has been used by over 160,000 users.

“Ashish’s dissertation is highly interdisciplinary and unparalleled in combining fundamental advances in natural language processing with large-scale, positive, immediate impacts on the mental health of large populations,” said Allen School professor Tim Althoff, who advised Sharma. “To date, his research has directly improved mental health services that support more than 10 million people yearly — an exceptional feat for any researcher.”

Prior to the ACM’s recognition of his work, Sharma received one of two William Chan Memorial Dissertation Awards, which are named for the late Allen School graduate student William Chan and recognize dissertations of exceptional merit, as well as a JP Morgan AI Ph.D. Fellowship.

Sewon Min: “Rethinking Data Use in Large Language Models”

Although current LMs including ChatGPT have transformed NLP progress, they still have fundamental issues, such as factuality and privacy, that arise from how they learn to perform new tasks after training. The widespread belief was that LMs obtain new skills on the fly without additional training through in-context learning; however, Min showed that LMs’ in-context learning capabilities are actually based on patterns they learn in their training data, which can be activated in certain ways. Based on this understanding, she introduced a new class of models called nonparametric LMs. 

“This new class of LMs includes learned parameters and a datastore, from which they retrieve information for improved accuracy and updatability,” Min explained. 

During inference, a nonparametric model can identify and reason with relevant text from its datastore, unlike a conventional model that must remember every relevant detail from its training set. Having a datastore present at inference time can help lead to more efficient and flexible LMs. 

“My Ph.D. thesis is about understanding and advancing large language models centered around how they use the very large text corpora they are trained on,” said Min, who was part of the UW NLP group. “My research established the foundations of nonparametric models, and also opened up new avenues for responsible data use, such as enabling data opt-out and credit assignment to data creators.”

These nonparametric LMs include retrieval-augmented generation (RAG), and her research has helped establish the technique. However, “the recent use of RAG has been mainly using an off-the-shelf retrieval model and an off-the-shelf LM and plugging them together without training the model, whereas my research advocates for developing new architectures and training methods that allow for more effective and efficient use of the datastore,” Min explained.

Nonparametric LMs can lead to new approaches to avoid the legal constraints that traditional LMs often run into. It is common practice to train LMs using all available online data, but this approach can lead to concerns with copyrights and crediting data creators. Instead, Min developed a new method based on nonparametric LMs — training LMs using public domain data, while keeping copyrighted or other high-risk data in a datastore that is only accessed during inference and can be modified at any time. 

“Sewon’s thesis identifies bold, impactful and challenging problems that many researchers shy away from, and then designs creative technical solutions to address these problems,” said Allen School professor Hannaneh Hajishirzi, who is also a senior director for NLP research at Ai2 and co-advised Min alongside faculty colleague Luke Zettlemoyer. “Her ambitious, creative and forward-thinking vision is complemented by a foundation of technical, structured, mathematical and analytical strengths, leading to groundbreaking and pioneering research.”

The ACM and ACL honors are not the only accolades Min has earned for her dissertation work; she, too, earned a William Chan Memorial Dissertation Award from the Allen School, as well as the 2024 Western Association of Graduate Schools (WAGS) ProQuest Innovation in Technology Award, which recognizes research that introduces innovative technology as a creative solution to a major problem. During her time at the Allen School, Min received a JP Morgan Ph.D. Fellowship in AI and was also named a 2022 EECS Rising Star.

Read more about the ACM Doctoral Dissertation Awards as well as a related GeekWire story.

Editor’s note: This story was updated on July 30, 2025 to reflect Min’s ACL recognition, which was announced after the original publication date. Read more →

Artificial intelligence existed as both a subfield of computing and a cultural phenomenon long before ChatGPT entered the lexicon in November of 2022. While AI may be decades old, its impact on the way we work, the way we learn and, indeed, the way we live clearly has been accelerating in recent years. What isn’t clear is what comes next; regardless, a growing number of professionals across a range of industries will need the ability to understand, leverage and integrate AI and machine learning as part of their work.

Starting this fall, one option for gaining the necessary knowledge and skills will be the Allen School’s stackable Graduate Certificate in Modern AI Methods, a new part-time evening program designed with the needs of working professionals in mind.

“This new curriculum provides students with the opportunity to gain hands-on experience and build their knowledge of best practices when it comes to widely-used AI and machine learning methods,” said instructor Taylor Kessler Faulkner. “Professionals in a wide range of fields who are interested in applying AI and ML techniques in their work will benefit from this certificate.”

That curriculum comprises four courses taught by Allen School instructors with deep expertise in the field, addressing topics such as deep learning, computer vision and natural language processing and their applications. The series culminates in a final, project-based course that invites students to put what they’ve learned into practice. 

Although the certificate is geared toward working professionals, the Allen School also welcomes applications from recent graduates who want to develop their knowledge and skills in AI. Unlike many other programs of this type, the Graduate Certificate in Modern AI Methods will be delivered in person on the University of Washington’s main campus — which will provide students with multiple benefits beyond the course content.

“Students in the certificate program will have access to UW facilities and face time with faculty and the other students in their cohort,” noted Allen School professor Luke Zettlemoyer, who is also senior research director at Meta FAIR. “It’s a great opportunity for local professionals and recent graduates without a formal education background in computer science to take graduate-level courses in the Allen School.”

Course content will be available only to students enrolled in the program. The courses are designed to be taken sequentially over twelve months, starting in September. 

For those with ambitions of earning a master’s degree, the stackable certificate in Modern AI Methods can be applied towards either of two stacked master’s degree programs currently offered at the UW: the Master of Science in Artificial Intelligence and Machine Learning for Engineering, and the Master’s of Engineering in Multidisciplinary Engineering. More stackable degree options may be added in future.

“AI is having an impact on many professions, both inside and outside of the technology industry, and that impact will continue to grow as new techniques and tools come online,” said Magdalena Balazinska, professor and director of the Allen School and holder of the Bill & Melinda Gates Chair in Computer Science & Engineering. “With the Allen School’s long history of leadership in AI, we embrace our responsibility to help students to acquire the fundamental knowledge and skills that will enable them to leverage the latest advances in their current profession or any new career path they might want to explore.”

While the program is likely to be a good match for individuals with a background in science, technology, engineering or mathematics (STEM) or mathematically-focused business degrees, holders of a bachelor’s in any field with the requisite math and programming skills are welcome to apply. However, for those with a degree in computer science or computer engineering, Kessler Faulkner says, the Allen School’s Professional Master’s Program is likely to be a better fit. Applicants can complete an online self-assessment prior to submitting their application to gauge how well their skills are a match for the certificate program.

The inaugural cohort will start in autumn 2025. The deadline to apply to be part of that cohort is August 1st. Learn more about the stackable Graduate Certificate in Modern AI Methods by visiting the Allen School website and also check out a related story in GeekWire. Read more →

Even the most well-designed and accessible websites may inadvertently have inaccessible elements — advertisements. Pesky pop-ups or bothersome banner ads may be easy for many people to navigate away from, but for those who use screen readers, ads that are not developed with accessibility in mind can make browsing online a frustrating experience. 

Allen School Ph.D. student Christina Yeung alongside professors Franziska Roesner and Tadayoshi Kohno wanted to understand just how problematic inaccessible ads can be to users who rely on screen readers. By auditing how ads use, or do not use, accessible elements and pairing that with interviews with blind participants about their browsing experience, the researchers found that the overall online ad ecosystem is fairly inaccessible for users with screen readers. However, encouraging ad platforms to adhere to existing web accessibility guidelines can help make surfing the web a better experience for everyone. 

The researchers presented their paper “Analyzing the (In)Accessibility of Online Advertisements” at the 2024 ACM Internet Measurement Conference (IMC) in Madrid, Spain, last November where it received the Best Paper Award. 

“Online ads are everywhere and so pervasive. If you’re browsing on your phone, or even have an ad blocker on your laptop — you will still see ads,” lead author Yeung said. “But because ads are designed with the intent to visually tell you what’s going on, for those who are blind and use screen readers, they can be even more problematic in ways that other people might not think about on a day-to-day basis.”

Yeung and her collaborators analyzed the behavior of over 8,000 ads across 90 different websites based on how well they adhere to Web Content Accessibility Guidelines (WCAG) best practices. Over the course of a month, the team looked at whether the ads disclosed their third-party content status to screen readers as well as their use of HTML assistive attributes such as alt-text and aria-labels. These elements ensure that screen readers can perceive images and other non-text elements on the ad. They also tracked the number of interactive elements each ad had and if there was any missing text associated with links or buttons. For an ad with 15 interactive elements, someone who uses the tab key to maneuver through ads would need to press it 15 times to reach other content on the site. If an ad has a button without associated text, instead of telling the user what it does, the screen reader will just say “button.”

The researchers found that the majority of the ads contained inaccessible elements. More than half of the ads had no alt-text at all, or had empty or non-descriptive strings. Many assistive attributes included non-descriptive language such as “ad” or “image.” They also noticed that ad developers were using title attributes to provide information, contrary to WCAG guidelines. Title attributes can provide more context to specific HTML elements, appearing as a tooltip when a user hovers their mouse over the element. However, not all screen readers can consistently interact with them. 

“Inaccessible ads have two primary problems,” Yeung said. “First, people can’t differentiate what the content is, so they can’t even make the decision as to whether or not they want to interact with it. Secondly, ads that are designed poorly really do negatively impact browsing in a way that can be quite cumbersome.”

Yeung then interviewed blind participants who use screen readers to understand just how burdensome these poorly-designed ads can be. All of the participants reported that these ads both distracted and detracted from their web browsing experience as they were difficult to navigate away from. Because many ads did not disclose their third-party status, participants often had to use context clues to identify them. For example, if someone was on a news site and they suddenly hear content about furniture, they would know that the furniture content is the ad. While the researchers did not evaluate pop-up ads in the study, participants brought up how frustrating these ads are because they are difficult to close and participants struggled to get back to where they were on the page before the ad.

Only a few large companies dominate the ad landscape, so refining how they adhere to accessibility guidelines can make a noticeable difference. Major ad platforms such as Google, Yahoo and Criteo could create and enforce policies requiring ads to provide meaningful information to screen readers in the HTML attributes. They could also go a step further and develop templates that encourage using assistive attributes and reject ads with generic or missing information, Yeung explained.

“By making some fairly minor changes, we can improve the ecosystem in a way that makes browsing more equitable for everyone,” Yeung said.

Next, Yeung is looking into people’s perceptions of the data collection practices of different generative artificial intelligence companies. 

Read the full paper on ad inaccessibility.

Read more →

Ever since he was a student at the University of Washington, Armon Dadgar (B.S., ‘11) has had his head in the cloud. And despite co-founding the high-flying company HashiCorp after graduation, he has kept his feet firmly on the ground by finding ways to parlay his success into support for future innovators and entrepreneurs.

That success grew out of an experience Dadgar and his friend and co-founder, Mitchell Hashimoto (B.S., ‘11), had as undergraduate researchers in the Allen School’s systems research group. It was there that the two gained their first hands-on exposure to cloud computing and the challenges it posed for practitioners. At the time, cloud computing was on the rise, and of today’s three big players — Amazon, Google and Microsoft — only Amazon had officially launched its platform. But Dadgar and Hashimoto had access to all three for the aptly named Seattle Project, which aimed to leverage these emerging platforms for large-scale, peer-to-peer scientific applications. As part of the project, the duo attempted to build a software solution that would span the “multi-cloud” environment they had to work with.

They were unsuccessful on that first attempt, but according to Dadgar, the experience sparked their entrepreneurial spirit. After graduation, they moved to San Francisco and eventually decided to revisit the old research problems that had since emerged on an enterprise scale. They started HashiCorp, which became a leading provider of software for companies and organizations seeking to automate their infrastructure and security management in multi-cloud and hybrid environments. As co-founder and Chief Technology Officer, Dadgar helped grow HashiCorp to over 2,500 employees. The company counted such household names as Expedia and Starbucks among its roughly 5,000 commercial customers prior to its acquisition by IBM for $6.4 billion earlier this year, after going public in 2021.

“Major revolutions in computing, such as the public cloud, have depended on crucial research innovation in computer systems. As an undergrad in the Allen School, I was fortunate to have been exposed to research in operating systems, virtualization, networking, and more which underpins the public cloud,” said Dadgar. “Those experiences ultimately led to me founding HashiCorp. By supporting systems research, I hope for the Allen School to continue to be at the forefront of innovation in AI and beyond to inspire the next generation of students, researchers and entrepreneurs.”

Dadgar may have traded the city by the sound for the city by the bay years ago, but his affection for the UW is evergreen. Now, he and his partner, Joshua Kalla, are living in Seattle and hoping to sow the seeds of the next HashiCorp through a $3 million gift to the Allen School to support research and student success — and drive the next wave of systems innovation for the artificial intelligence era. The couple’s commitment includes $1 million to establish the Armon Dadgar & Joshua Kalla Endowed Professorship in Computer Science & Engineering, with the intent to help propel Seattle and Dadgar’s alma mater from the epicenter of cloud computing to the leading edge at the intersection of systems and AI.

“We are incredibly grateful to Armon and Josh for their generosity,” said Magdalena Balazinska, director of the Allen School and Bill & Melinda Gates Chair in Computer Science & Engineering. “The Allen School is one of the top computer science programs in the country, and an academic leader in cloud computing, systems, and AI research. But to maintain that leadership and continue to make transformational advances while educating the next generation of innovators, we need support to attract and retain the most talented faculty and students. Armon’s and Josh’s gift will greatly help us with that.”

While Dadgar is eager to give next-generation systems research a lift, he is even more enthusiastic about elevating the next generation of students entering the field. To that end, he and Kalla have committed $2 million to the Allen School Student Success Fund to support a variety of initiatives aimed at prospective and current Allen School students, with a focus on first-generation college students and K-12 students in Washington with limited access to computing education resources.

“Education has always been an incredible driver of economic mobility,” said Dadgar. “Our goal is to broaden the pathways into computer science and technology, and particularly to focus on first-generation college students where we can have a multi-generational impact on both the individual and their families.”

Dadgar has repeatedly walked the talk, whether on campus or at company headquarters. At HashiCorp, he championed the creation of the Early Career Program in 2021 to enable college students of all majors and backgrounds to spend a summer at HashiCorp applying what they’ve learned in the classroom in a real-world corporate setting. More than 170 interns from across the country have benefited from the program’s mentorship and networking opportunities — over a third of whom accepted full-time positions with the company after graduation. In 2019, Dadgar and Kalla committed $3.6 million to the UW to provide scholarships to undergraduate students who participate in the university’s Educational Opportunity Program, which has supported 35 scholars to date.

As a professor at Yale University, Kalla is well aware of the impact such programs can have on students — and the institutions that provide them with that pathway to economic mobility.

“The University environment is a unique setting where students are exposed to new ideas, learn valuable skills, and through research advance the frontiers of knowledge,” said Kalla. “Creating opportunities for the next generation to participate and ultimately to lead us forward is incredibly important to us personally.”

Among the programs supported by the Student Success Fund are the Allen School Scholars Program, a one-year cohort-based program for incoming computer science and computer engineering majors focused on emerging leaders from first generation, low-income and underserved communities, and Changemakers in Computing, a summer program for rising juniors and seniors in high school to learn about computing and its societal impacts.

“We’re hugely appreciative of Armon and Josh’s extraordinary generosity, which will have a lasting impact on our program and our students,” said Ed Lazowska, professor and the Bill & Melinda Gates Chair Emeritus at the Allen School. “This gift is an opportunity to reflect on the inspirational story of HashiCorp: best friends pursuing a vision that began with some software that they built as part of an undergraduate project in the Allen School — and it will enable future generations of Allen School students to pursue their dreams.”

Read a related GeekWire story.
Read more →

Throughout his career, professor James Fogarty, who joined the Allen School faculty in 2006, has grown to become a central figure in Seattle’s human-computer interaction (HCI) community and beyond. His research has made key contributions in sensor-based interactions, interactive machine learning, personal health informatics and accessibility, publishing over 100 peer-reviewed papers. At the same time, he has played a pivotal role in founding and growing Design, Use, Build (DUB) — University of Washington’s cross-campus HCI alliance bringing together faculty, students, researchers and industry partners.

The ACM Special Interest Group on Computer-Human Interaction (SIGCHI) recognized Fogarty’s contributions and inducted him into the SIGCHI Academy Class of 2025. Each class represents the principal leaders of the field, whose research has helped shape how we think of HCI.

“I am honored to be among the SIGCHI Academy Class of 2025,” Fogarty said. “I’m grateful for the amazing students and collaborators that I’ve had the pleasure to work with over the years, advancing HCI, interactive machine learning, personal health informatics and accessibility research.”

Since the beginning of his career, Fogarty has made breakthroughs in HCI research. As a first-generation student, he was introduced to HCI research at Virginia Tech and was part of the first cohort of Ph.D. students in the Human-Computer Interaction Institute at Carnegie Mellon University. Key research from his dissertation, which focused on using sensor-based interactions to predict the best time to interrupt someone, received a 2005 CHI Best Paper Award. 

Upon joining the UW, Fogarty launched a new research emphasis in interaction with artificial intelligence (AI) and machine learning. Fogarty’s research into new methods for engaging end-users in machine learning training and assessment and understanding difficulties that machine learning developers encounter was considered ahead of its time. The researchers contributed to what is now known as human-AI interaction before it became a trending topic, and this line of research went on to directly impact industry guidelines for the field. 

In the same period, Fogarty and his collaborators developed Prefab, a system for real-time interpretation and enhancement of graphical interfaces through reverse engineering their pixel-level appearance. Prefab, which earned a 2010 CHI Best Paper Award, was a breakthrough in interface systems research, foreshadowing current work using AI to understand, interact with and enhance graphical interfaces. 

Fogarty then turned his research interests toward digital health, including tools to support people in self-tracking and making sense of health data. He and his collaborators provided new insights into the design of tools to support menstrual tracking, informing the design of Apple’s menstrual cycle tracking support. The research received a 2017 CHI Best Paper Award and helped expand the field’s conception of personal informatics to account for the role of design in experiences people have with their tools. Fogarty also researched the design of mobile food journals and activity-tracking visualizations as well as tools to help patients collaborate with their health providers to interpret and act on self-tracked data. More recently, Fogarty and his collaborators developed a new goal-directed approach to long-term migraine tracking, which earned them a 2024 CHI Best Paper Award, and a new tool for home-based self-monitoring of cognitive impairment in patients with liver disease, recognized with a 2025 CHI Best Paper Award. 

Outside of health tracking, Fogarty has also made important strides in accessibility research. He and his team drew inspiration from epidemiology to conduct the first large-scale assessment of accessibility in 10,000 Android apps. The Department of Justice cited the work as part of its updates to the Americans with Disabilities Act. He also extended his work on interface understanding and enhancement to demonstrate real-time repair of mobile app accessibility failures. This research helped directly motivate and inform Apple’s launch of accessibility repair in its pixel-based Screen Recognition.

“James has made an exemplary impact across research disciplines and industry,” Allen School professor Jeffrey Heer said. “His research prowess, volunteer spirit, deep care, thoughtfulness and community-mindedness have helped guide DUB and advance the HCI community in Seattle and across the globe.”

Fogarty is one of five UW faculty being recognized with ACM SIGCHI Awards this year. Department of Human Centered Design & Engineering (HCDE) professor and Allen School adjunct faculty member Kate Starbird joins Fogarty as part of the CHI Academy Class of 2025, and her work sits at the intersection of HCI and computer-supported cooperative work. 

Information School professor and Allen School adjunct faculty member Alexis Hiniker also won an ACM SIGCHI Societal Impact Award for her research into ways that consumer-facing technologies can hurt young people instead of helping them thrive. Nadya Peek and Cecilia Aragon, both HCDE professors and Allen School adjunct faculty members, were honored with ACM SIGCHI Special Recognitions. Peek was recognized for “democratizing automation through open-source hardware, building global maker communities and bridging academic research with grassroots fabrication practices,” and Aragon “for establishing human-centered data science as a new field bridging HCI and data science, demonstrating its impact through applications from astrophysics to energy systems.”

Read more about the 2025 ACM SIGCHI Awards, and see more about DUB and the UW presence at CHI 2025. 

Read more →

One of the foundations of database theory is efficient query execution. On the theory side, researchers have been tackling this issue by finding the upper bounds on the query size results to determine the fundamental hardness of query execution. Other researchers have been taking a practical approach by honing query optimizers that can automatically create query evaluation algorithms based on various data properties. These two approaches have converged in the form of worst-case optimal join algorithms, which ensure the optimal execution time for query evaluations by taking into account certain statistics about the queried dataset. 

In a paper titled “Partition Constraints for Conjunctive Queries: Bounds and Worst-Case Optimal Joins,” Allen School Ph.D. student Kyle Deeds introduced an innovative statistic called partition constraints that can improve existing worst-case optimal join algorithms by capturing the latent structure in relations within the data. The rigid nature of traditional constraints used in worst-case optimal join algorithms, such as degree constraints or cardinality constraints, can end up hindering query execution speed. Instead, partition constraints extend the notion of degree constraints, enabling the relationships between database attributes to be divided into smaller and more manageable sub-relations that each have their own degree constraints.

Deeds and his collaborator Timo Camillo Merkl of TU Wien presented their research at the 28th International Conference on Database Theory (ICDT) in Barcelona, Spain, last month where their work received the Best Student Paper and Best Paper Awards.

“A core problem of database theory is query execution,” said Deeds, who is advised by professors Dan Suciu and Magdalena Balazinska in the University of Washington’s Database Group. “What this work did was present a new kind of statistic, called partition constraints, on that data that we can take into account when we are executing a query, essentially speeding up the whole process for data that has this nice structure.”

An example of a use of partition constraints is in an algorithm that records who has key card access to which rooms within a university. Faculty and students may only need to enter a few rooms such as lecture halls and offices, while security and cleaning staff may need to be able to reach many more, or maybe all, rooms. It makes sense to then partition keycard clearance by tracking the access restrictions of faculty and students, and of the various room caretakers, to efficiently determine who needs access to which rooms.

Deeds took inspiration for partition constraints from another field of computer science called graph theory, or the study of networks. Degeneracy in graph theory measures how sparse a graph is. In a network with low degeneracy, researchers can design algorithms that minimize the performance impact of highly connected vertices, which can make some graph algorithms more efficient. When it comes to partitioning and databases, this property can also help maintain database performance, even in cases where the tables have very high degrees. The researchers developed partition constraints as a declarative version of graph degeneracy for higher-arity data, or data with more attributes or fields.

“This paper is like a translation style work,” Deeds said. “The goal of this work was to translate ideas from graph theory over in a way that made sense to the database community. Once we found the right way to do the translation, things just clicked into place.”

These ideas started clicking into place when Deeds and Merkl met and began collaborating on their research.

“Kyle and Camillo first met at a previous instance of the same conference, at ICDT in 2023 in Greece. Since then they worked remotely, without any help or guidance from their respective advisors,” said Suciu, who holds the Microsoft Endowed Professorship in the Allen School. “They started from an existing, elegant concept in graph theory, called ‘degeneracy,’ and extended it to a practical method for processing relational databases. Their main idea is that, by carefully partitioning each relation into a small number of fragments, then computing a query separately on each fragment, one can significantly reduce the query’s execution time.”

For Deeds, partition constraints point to a new direction for database theory research to pursue. Partition constraints help uncover underlying and useful structures within data, and understanding the different correlations and properties that a database has can help find ways to further optimize query executions.

“The same partitioning method that Kyle and Camillo developed has many other applications beyond query evaluation. For example, in one of my research projects we are developing improved techniques for cardinality estimation, and asked Kyle to join us to adapt his method for this problem,” Suciu said. 

Outside of partition constraints, Deeds has been researching ways to optimize other programs. He introduced Galley, a system for declarative sparse tensor computing that enables users to draft efficient tensor programs without needing to make complex algorithm decisions. 

Read the full paper on partition constraints. 

Read more →