Yejin Choi, a University of Washington computer science professor and senior research manager at Seattle's Allen Institute for Artificial Intelligence (AI2), won a $800,000 "genius grant" given annually by the John D. and Catherine T. MacArthur Foundation. Choi, one of 25 MacArthur Fellows for 2022 revealed Wednesday, is an expert in natural language processing. Her work aims to improve the ability of computers and artificial intelligence systems to perform commonsense reasoning and understand implied meaning in human language. "This is such a great honor because there have been only two other researchers in the natural language processing field who have received this award," Choi told UW News. Choi spoke to GeekWire earlier this year about the debate over a robot's ability to have human-like feelings.

We are a research group at the Paul G. Allen School of Computer Science of Engineering. Our aim is to explore and understand behavior through the lens of data science. The Behavioral Data Science Group develops computational methods that leverage large-scale behavioral data to extract actionable insights about our lives, health and happiness through combining techniques from data science, social network analysis, and natural language processing. We currently work on research related to mental health, misinformation online, scientific reproducibility, and informing the COVID-19 response. We have a postdoc position available.

Earlier this year, Dartmouth College's medical school charged 17 students with cheating on remote online exams. Three of the students were expelled. The accused protested their innocence, claiming the medical school's remote test administration, or RTA, system had falsely flagged their conduct. With their reputations and careers hanging in the balance, their fate came down to a dispute about the software. Eventually, a technical explanation emerged, showing how students' logged-in cellphones and tablets might have been accessing course notes while the exam was being administered.

The College of Engineering Awards acknowledge the extraordinary efforts of the college's teaching and research assistants, staff and faculty members. Sam Burden is an expert in sensorimotor control and hybrid systems and their application to robotics, neuroengineering and cyber-physical systems. He is a founding co-director of the Laboratory for Amplifying Movement and Performance (AMP Lab), where his research focuses on developing mathematical and computational modeling tools to enable collaborative learning and control between humans and machines. As a first-generation college graduate and UW engineering alum, Burden is committed to broadening participation in engineering, a goal he pursues in his role as the first DEI coordinator for the ECE department, where he works to define and implement the department's diversity, equity and inclusion goals through the formation of an advisory committee and partnering with other department leaders on strategic planning, funding, hiring and recruiting. He is the recipient of an ARO Young Investigator Award, WRF Early Faculty Award and an NSF CAREER Award.

UW-IT continues to enhance Hyak, the University's supercomputer, to ensure it best serves ever-growing faculty and student research needs. Upgrades include a new hardware infrastructure now underway, and recent expansions in GPU (Graphics Processing Unit) capacity. Hyak supports a broad range of workloads -- from traditional high-performance computing to data science approaches such as machine learning and other computation-heavy Big Data problems. An infrastructure update underlies Hyak's third-generation build, named "Klone." The update will improve performance even while leveraging existing standard hardware, and includes a new CPU cluster with more data storage overall, faster read/write capability and a more performant (twice as fast), cost-effective and scalable inter-networking architecture among Hyak's processors.

Researchers at the University of Washington have figured out a way to use machine-learning algorithms to turn smart speakers into sensitive medical devices that can detect irregular heartbeats. The scientists use smart speakers like Amazon Echo or Google Home to send out an inaudible sound that bounces off a person's chest and returns to the device, reshaped in a way that reveals the heartbeat. An uneven cardiac rhythm can be associated with ailments including strokes or sleep apnea. The researchers employed a machine-learning algorithm to tease out the heartbeats from other sounds and signals such as breathing, which is easier to detect because it involves a much larger motion. The algorithm was also needed to zero in on erratic heart rhythms -- which from a health perspective are generally more important to identify than a steady "lub-dub."

Tim Althoff is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. His research advances computational methods that leverage large-scale behavioral data to extract actionable insights about our lives, health and happiness through combining techniques from data science, social network analysis, and natural language processing. Tim holds Ph.D. and M.S. degrees from the Computer Science Department at Stanford University, where he worked with Jure Leskovec. Prior to his PhD, Tim obtained M.S. and B.S. degrees from the University of Kaiserslautern, Germany. He has received several fellowships and awards including the SAP Stanford Graduate Fellowship, Fulbright scholarship, German Academic Exchange Service scholarship, the German National Merit Foundation scholarship, a Best Paper Award by the International Medical Informatics Association, and the SIGKDD Dissertation Award 2019.

Allen School professor Adriana Schulz and adjunct professor Nadya Peek are among the 35 "Innovators Under 35" recognized by MIT Technology Review as part of its 2020 TR35 Awards. Each year, the TR35 Awards highlight early-career innovators who are already transforming the future of science and technology through their work. Schulz, a member of the Allen School's Graphics & Imaging Laboratory (GRAIL) and Fabrication research group, was honored for her visionary work on computer-based design tools that enable engineers and average users alike to create functional, complex objects. Peek, a professor in the Department of Human-Centered Design & Engineering, was honored in the "Inventors" category for her work on modular machines for supporting individual creativity. Schulz and Peek are also among the leaders of the new cross-campus Center for Digital Fabrication (DFab), a collaboration among researchers, educators, industry partners, and the maker community focused on advancing the field of digital fabrication.

The IEEE Robotics & Automation Society has announced Allen School professor Dieter Fox as the recipient of a 2020 RAS Pioneer Award in recognition of his "pioneering contributions to probabilistic state estimation, RGB-D perception, machine learning in robotics, and bridging academic and industrial robotics research." The society will formally honor Fox, director of the University of Washington's Robotics and State Estimation Laboratory and senior director of robotics research at NVIDIA, during the International Conference on Robotics and Automation (ICRA 2020) next week. The RAS Pioneer Award honors individuals who have had a significant impact on the fields of robotics and automation by initiating new areas of research, development, or engineering. Fox's contributions have focused on enabling robots to interact with people and their environment in an intelligent way, with an emphasis on state estimation and perception problems such as 3D mapping, object detection and tracking, manipulation, and human activity recognition. "We are extremely proud that Dieter has been recognized with this prestigious award. It is truly deserved," said professor Magdalena Balazinska, director of the Allen School.

Benjamin Lee, a second-year Ph.D. student in the Allen School's Artificial Intelligence group working with professor Daniel Weld, has been named a 2020 Innovator in Residence by the Library of Congress. Now in its second year, the Innovator in Residence program aims to enlist artists, researchers, journalists, and others in developing new and creative ways of using the library's digital collections. During his residency, Lee will apply deep learning to enable the automatic extraction and tagging of photographs and illustrations contained in the more than 15 million newspaper scans comprising the library's Chronicling America collection. His goal is to produce interactive visualizations, searchable by topic, that will make the content more accessible to users and support cultural heritage research. "A primary motivation behind my project is to excite the American public by demonstrating the possibilities of applying machine learning to library collections," Lee explained in an interview posted on the library's blog.