Allen School News

The cardinality estimation problem, or the challenge of accurately predicting the size of the output to a query without actually evaluating the query, is one of the oldest and most important problems in databases and data management. Cardinality estimation helps guide decisions on every aspect of query execution, however, current methods can often have large errors, leading to poor decisions downstream. To address this, a team of researchers led by Allen School professor Dan Suciu of the UW Database Group introduced a new pessimistic cardinality estimator called LpBound which provides a guaranteed upper bound on the query output size, and received a SIGMOD Best Paper Award for their work. Read more →

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Magdalena Balazinska, professor and director of the Allen School, has been elected a member of the Washington State Academy of Sciences (WSAS) in recognition of her “contributions in data management for data science, big data systems, cloud computing, and image/video analytics and leadership in data science education.” The WSAS was established in 2015 as a source of independent, evidence-based scientific and technical advice for state policy makers, modeled after the National Academies of Science, Engineering and Medicine. Balazinska, who was directly elected by her WSAS peers, is one of 36 members in the 2025 class. Read more →

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Allen School professor Abhishek Gupta is interested in developing ways to help robots learn new skills with minimal human help and engineering. Gupta joined the Allen School faculty in 2022, and already he has introduced research that has shaped the future of robotics. His contributions to the field earned him the IEEE Robotics & Automation Society (RAS) Early Academic Career Award in Robotics and Automation where the organization recognized him “for pioneering contributions to real world robotic reinforcement learning.” Read more →

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Allen School Ph.D. student Cheng-Yu Hsieh is interested in tackling one of the biggest challenges in today’s large-scale machine learning environment — how to make artificial intelligence development more accessible. Large foundation models trained on massive datasets have revolutionized AI, however, but these scaling efforts are often out of reach for many except for well-resourced companies. With support from a Google Ph.D. Fellowship, Hsieh is working to make data and model scaling more efficient and affordable to help democratize AI development. Read more →

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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 researchers introduced FlashInfer, a versatile LLM inference kernel library that is open source as well as highly optimized for new techniques including key-value 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) and received a Best Paper Award. Read more →

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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 — accompanied by words of wisdom and inspiration from Trish Millines Dziko, co-founder and executive director of the Technology Access Foundation (TAF). Read more →

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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 and computer security and privacy to improve the lives of overlooked communities, specifically those experiencing intimate partner violence 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. Read more →

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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. The UW recognized the team – lecturer Kasey Champion and professors Elba Garza, Miya Natsuhara, Hunter Schafer and Brett Wortzman — behind this transformation with this year’s Distinguished Team Teaching Award in the 2025 Awards of Excellence, one of the University’s highest honors. Read more →

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Each year, the Association for Computing Machinery recognizes the best Ph.D. dissertations in computer science with its Doctoral Dissertation Award. Ashish Sharma (Ph.D., ‘24), now a senior applied scientist at Microsoft, received the 2024 award for leveraging AI to make high-quality mental health support available to more people. Sewon Min (Ph.D., ‘24), a research scientist at Ai2 and incoming faculty member at the University of California, Berkeley, received an honorable mention for developing a new class of language models that are more efficient and flexible. Read more →

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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. Read more →

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