Allen School News

Modern Internet of Things (IoT) technologies such as smart home devices, sensors and security cameras have transformed how we interact with our physical environments. As University of Washington researchers discovered, they also have the potential to help residents living in tiny house villages, a type of emergency shelter for those experiencing homelessness. To learn more about the team’s findings, we spoke with Allen School professor Kurtis Heimerl and Allen School postdoc Esther Han Beol Jang (Ph.D., ‘24). Read more →

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To help make datasets easier to understand and examine, in 2015, a team of researchers led by Allen School professor Jeffrey Heer introduced Voyager, a system that automatically generates and recommends charts and visualizations based on statistical and perceptual measures — allowing users to efficiently explore different parts of the dataset they may not have discovered before. At IEEE VIS 2025 earlier this month in Vienna, Austria, Heer and his co-authors were recognized with the InfoVis 10-Year Test of Time Award for the Voyager paper’s lasting impact on the field. Read more →

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At the Allen School, 22% of Fall 2025 undergraduate students are first generation, or one of the first in their family to pursue a bachelor’s degree. For first-gen students, navigating the twists and turns of higher education without a roadmap can be a daunting challenge. Still, these students have persevered to figure it out on their own or leverage resources such as the Allen School’s first-gen student group, GEN1, to help them find their way. In honor of the National First-Generation College Celebration on November 8, we asked students and faculty to share their experience being first and what advice they have for others still embarking on their first-gen journey. Here are some of their stories. Read more →

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From a robotic arm that learns how to pick up new objects in real time, to a model that converts 2D videos into 3D virtual reality, to a curious chatbot that adapts to its users, to machine learning techniques for decoding the brain (and so much more), the 2025 edition of the annual Research Showcase and Open House highlighted the breadth and depth of computing innovation coming out of the Allen School. Read more →

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Each year, the MIT Technology Review recognizes science and technology trailblazers whose work is helping solve global problems. Three members of the Allen School community were named part of this year’s MIT Technology Review Innovators Under 35 Asia Pacific — professors Simon Shaolei Du and Ranjay Krishna, along with alum Sewon Min (Ph.D., ‘24), now a faculty member at University of California, Berkeley and research scientist at the Allen Institute for AI (Ai2). The three were recognized as pioneers for their innovative research that is advancing our understanding of artificial intelligence, large language models, computer vision and more. Read more →

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In his research, Allen School professor Baris Kasikci focuses on developing techniques for building systems that are both efficient and have a strong foundation of dependability, with an emphasis on real-world technical and societal impact. At the 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2025) in June, Kasikci was recognized with the Rising Star in Dependability Award for “his impressive track-record and contributions in the field of dependable systems, including multiple publications in highly regarded venues, and influence on current industry practice.” Read more →

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To help network engineers and operators ensure that their networks operate exactly as they intend, Allen School professor and alum Ratul Mahajan (Ph.D., ‘05) and his collaborators introduced Batfish, an open source network configuration analysis tool that can find errors and ensure the accuracy of planned network configurations, helping to prevent costly outages. At the ACM Special Interest Group on Data Communication (SIGCOMM) conference last month, Batfish was recognized with the SIGCOMM Networking Systems Award for its “significant impact on the world of computer networking.” Read more →

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Despite their increasing potential and popularity, LLMs can often get facts wrong or even combine tidbits of information into a nonsensical response, also known as hallucinations. For Akari Asai (Ph.D., ‘25), research scientist at the Allen Institute for AI (Ai2) and incoming faculty at Carnegie Mellon University, the solution is developing retrieval-augmented language models, a new class of LLMs that pull relevant information from an external datastore using a query that the LLM generates. Her research has helped establish the foundations for retrieval-augmented generation (RAG) and showcase its effectiveness at reducing hallucinations. She was recently named one of MIT Technology Review’s Innovators Under 35 2025 for her pioneering research improving artificial intelligence. Read more →

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At the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), Allen School researchers brought home multiple awards for work that is moving natural language processing research forward. Their projects ranged from laying the foundation for how artificial intelligence systems understand and follow human instructions to exploring how LLMs pull responses from their training data — and more. Read more →

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Each year, Qualcomm recognizes exceptional Ph.D. students with the Qualcomm Innovation Fellowship. Two of this year’s winning teams from North America featured Allen School Ph.D. students. Andrew Alex and Megan Frisella received support for their proposed project “Productive Programming of Multi-Threaded Hardware Accelerators,” while Zixian Ma and collaborator Yushi Hu of the University of Washington Department of Electrical & Computer Engineering earned a fellowship for their project “Learning Multi-modal Agents to Reason and Act for Complex Multi-modal Tasks.” Read more →

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