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Photo: Mark Stone/University of Washington
Artificial intelligence tools have the potential to become as essential to medical research and patient care as centrifuges and x-ray machines. Advances in high-accuracy predictive modeling can enable providers to analyze a range of patient risk factors to facilitate better health care outcomes — from preventing the onset of complications during surgery, to assessing the risk of developing various diseases.
When it comes to emergency services or critical care settings, however, the potential benefits of… Read more →
April 11, 2022
Less than a year after her arrival at the University of Washington, professor Yulia Tsvetkov is making her mark as the newest member of the Allen School’s Natural Language Processing group. As head of the Tsvetshop — a clever play on words that would likely stymie your typical natural language model — Tsvetkov draws upon elements of linguistics, economics, and the social and political sciences to develop technologies that not only represent the leading edge of artificial intelligence and natural… Read more →
April 4, 2022
Recent advances in open-ended text generation could enable machines to produce text that approaches or even mimics that generated by humans. However, evaluating the quality and accuracy of these large-scale models has remained a significant computational challenge. Recently, researchers at the Allen School and Allen Institute for AI (AI2) offered a solution in the form of MAUVE, a practical tool for assessing modern text generation models’ output compared to human-generated text that is both efficient and scalable. The team’s… Read more →
February 28, 2022
Luke Zettlemoyer, a professor in the Allen School’s Natural Language Processing group and a research director at Meta AI, was recently elected a Fellow of the Association for Computational Linguistics (ACL) for “significant contributions to grounded semantics, semantic parsing, and representation learning for natural language processing.” Since he arrived at the University of Washington in 2010, Zettlemoyer has focused on advancing the state of the art in NLP while expanding its reach into other areas of artificial intelligence such… Read more →
February 23, 2022
The Allen School has a proud tradition of nurturing undergraduate student researchers whose work has the potential for real-world impact. This year, three of those students — Jerry Cao, Mike He and Yu Xin — earned honorable mentions from the Computing Research Association (CRA) as part of its 2022 Outstanding Undergraduate Researcher Awards competition for their contributions in health sensing and fabrication, programming languages and machine learning, and building robust computer systems.
Jerry Cao
The CRA recognized senior Jerry… Read more →
February 22, 2022
During their time at the Allen School, recent alumni Maarten Sap (Ph.D., ‘21) and Ivan Evtimov (Ph.D., ‘21) tackled some of the thorniest issues raised by emerging natural language processing and machine learning technologies — from endowing NLP systems with social intelligence while combating inequity and bias, to addressing security vulnerabilities in the convolutional neural networks that fuel state-of-the-art computer vision systems. Recently, the faculty honored both for their contributions with the William Chan Memorial Dissertation Award, which was… Read more →
February 3, 2022
Allen School professor emeritus Richard Ladner has been elected a Fellow of the American Association for the Advancement of Science (AAAS) for his “distinguished contributions to the inclusion of persons with disabilities in the computing fields.” One of 26 leading scientists in the organization’s Information, Computing & Communications section to attain the rank of Fellow this year, Ladner has devoted the past two decades to research and advocacy aimed at making computing education and careers more accessible while designing technologies… Read more →
January 26, 2022
Mohit Shridhar, a Ph.D. student working with Allen School professor Dieter Fox, has been named a 2022-2023 NVIDIA Graduate Fellow for his research in building generalizable systems for human-robot collaboration. Shridhar’s work is focused on connecting language to perception and action for vision-based robotics.
Shridhar aims to use deep learning to connect abstract concepts to concrete physical actions with long-term reasoning to develop robot butlers. The Fellowship will help him continue his work in building robots that learn… Read more →
January 19, 2022
Credit: gemma on Unsplash
“You are what you eat,” as the saying goes. But not everyone has the same degree of choice in the matter. An estimated 19 million people in the United States live in so-called food deserts, where they have lower access to healthy and nutritious food. More than 32 million people live below the poverty line — limiting their options to the cheapest food regardless of proximity to potentially healthier options. Meanwhile, numerous studies have pointed to… Read more →
January 18, 2022
As the world watched COVID-19 grow from a mysterious virus in far-off places to a planetary pandemic, news outlets worked hard to keep the world informed on how, where and why it was spreading. At the start of the outbreak, Matthew Conlen, a Ph.D. student in the Allen School’s Interactive Data Lab, was working as a graphic/multimedia editor for the New York Times helping with their elections forecasting application, also known as “The Needle.” He switched gears… Read more →
December 21, 2021
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