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Monitoring Freshwater Vulnerability to Climate Change and Human Activity
Project Lead: Catherine Kuhn, School of Environmental and Forest Sciences eScience Liaisons: Amanda Tan and Rob Fatland Rivers, lakes and streams are considered sentinels of environmental change. Deforestation, urbanization, and nutrient runoff are increasingly recognized as drivers of change for freshwaters, yet most research analyzing the impact of these forcings occurs at the watershed scale.…
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Detecting Small Particles in Low-Contrast Images to Aid in Particle Tracking
Project Lead: Alicia Clark, Mechanical Engineering eScience Liaisons: Bernease Herman and Valentina Staneva Ultrasound (US) is a safe and non-invasive imaging method commonly used in healthcare and clinical applications due to its high spatial and temporal resolution. However, there are areas of the body where low contrast makes it difficult to obtain high quality images needed…
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3D Visualization of Prostate Cancer Using Light-Sheet Microscopy
Project Lead: Dr. Nicholas Reder, Pathology eScience Liaison: Ariel Rokem Advances in microscopic imaging enable visualization of heretofore unseen 3D microanatomical features, which have the potential to transform cancer diagnostics. These novel imaging techniques have led to improved diagnostics in kidney biopsies, brain structure, and embryonic development. Light-sheet microscopy and tissue clarification techniques are a particularly…
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Cloud-Enabled Tools for the Analysis of Subsea HD Camera Data
Project Lead: Aaron Marburg, Applied Physics Laboratory eScience Liaisons: Bernease Herman and Valentina Staneva The publicly available data generated by CamHD have enormous scientific potential, with the capacity to support a wide range of geological, biological, hydrological, and oceanographic investigations using image analysis methods. However, the large size of the video archive and the lack of…
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Applying Machine Learning to the Analysis of the Large-Scale Structure of Turbulence
Project Lead: Owen Williams, Department of Aeronautics and Astronautics eScience Liaison: Jake VanderPlas Turbulent flows dominate many flows of engineering interest, regulating mixing, heat transfer and drag on vehicles. While hard to concisely define, turbulence is noisy, stochastic, and contains eddies of a wide range of scales that combine to create a chaotic set of movements that…
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Poster and networking session success
By Robin Brooks The UW Data Science Poster and Networking Session, hosted by the eScience Institute, was held on February 21, 2017, at the Mary Gates Commons. Over 50 students, postdoctoral candidates and researchers representing more than 30 departments on campus presented posters. Topics ranged from tracking microbubbles to open data literacy to design technologies…
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Microsoft $1M gift for new UW, UBC urban data partnership
By Robin Brooks The University of Washington and the University of British Columbia are partnering on a new collaboration called the Cascadia Urban Analytics Cooperative (CUAC), which will connect researchers, students and public stakeholders working on urban issues across the region. A $1 million donation from Microsoft will allow the two universities to work together using data…
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Data Science Environments partners publish reproducibility book
By Robin Brooks Researchers from the UW’s eScience Institute, New York University Center for Data Science and Berkeley Institute for Data Science (BIDS) have authored a new book titled The Practice of Reproducible Research. Representatives from the three universities, all Moore-Sloan Data Science Environments partners, joined on January 27, 2017, at a symposium hosted by BIDS. There, speakers discussed…
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Fellow proposes critical analysis course
By Robin Brooks Jevin West, data science fellow and assistant professor in the UW Information School, and Carl T. Bergstrom, professor of biology, have proposed a new course meant to develop critical analysis skills. Tentatively titled Calling Bull***t, the class aims to teach learners “how to think critically about the data and models that constitute evidence…
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Affiliate’s health startup receives $8.5 million in funding
By Robin Brooks KenSci, a health data startup co-founded by Ankur Teredesai and Samir Manjure, has raised $8.5 million in a Series A investment round. The startup uses machine learning technology that “helps doctors predict who might get sick and how sick they might get, and take actions to help them before it happens.” (1)…