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Echopype: Interoperability and Scalable Ocean Sonar Data Analysis
Partners: Wu-Jung Lee and Emilio Mayorga SSEC Engineers: Don Setiawan and Valentina Staneva Research Goals and Domain Scientists commonly use active sonar systems to collect data about mid-trophic level animals, such as zooplankton and small fish that play an important role in marine ecosystems. Echosounders, or fish-finders, are high-frequency sonar systems that emit pulses of…
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NoisePy: Ambient Field Seismology
Partners: Marine Denolle, Yiyu Ni, and Kuan-Fu Feng SSEC Engineers: Carlos Garcia Jurado Suarez Research Goals and Domain The Earth’s ambient field contains a great deal of information about its structure. Changes in this structure occur at a vast range of temporal and spatial scales. We can record these changes thanks to the long-term deployment…
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Wet AI: Collaborative Neurobiology
Partners: David Haussler, Matt Elliot, David Parks, and Lon Blauvelt SSEC Engineers: Cordero Core and Don Setiawan Research Goals and Domain Cerebral organoids are synthetic tissues derived from induced or natural stem cells within a laboratory setting. Once they are differentiated, these structures offer an avenue for researchers and students to probe and stimulate neural…
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Offshore Geodesy: Advancing Research and Collaboration in Seafloor Deformation
Partners: David Schmidt and John DeSanto SSEC Engineer: Don Setiawan Research Goals and Domain The Near-Trench Community Geodetic Experiment, is a five-year NSF-funded project aimed at establishing open and accessible seafloor deformation data in the Alaska and Cascadia regions, both notorious for witnessing some of the largest earthquakes and tsunamis in recorded history. By utilizing…
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Neglected Diagnostics: Democratizing Genetic Testing
Partners: Hal Holmes, Misa Winters, and Cifeng Fang SSEC Engineers: Aniket Fadia and Carlos Garcia Jurado Suarez Research Goals and Domain Genetic testing is routinely relied upon to detect the illegal trafficking of wildlife, the introduction of invasive species and pathogens, as well as monitor disease spread or outbreaks that can devastate the health of…
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Deep Learning to Uncover Watershed Specific Characteristics in Salmon Otolith Patterns to Aid in Management of Pacific Salmon
Project Lead: Ben Makhlouf, UW Aquatic and Fisheries Sciences Data Science Lead: Valentina Staneva Pacific salmon in western Alaska support a multi-million-dollar commercial fishing industry and are a vital source of subsistence for upstream communities. In recent years, catastrophic declines in Chinook and Chum salmon populations have severely impacted subsistence opportunities, causing significant hardship across the region.…
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Detection of Early Warning Signals regarding Safety Concerns of Implantable Medical Devices
Project Lead: Aparna Ramanathan, UW Medicine Data Science Lead: June Yang, Spencer Wood Currently in the United States, postmarket surveillance of medical device safety is conducted via the Manufacturer and User Facility and Device Experience (MAUDE) database. MAUDE is targeted at device manufacturers and does not engage patient or provider users of new medical devices; this lack…
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Global High-Resolution Modeling: A New Lens on the Southern Ocean
Project Lead: Mira Berdahl, UW Earth and Space Sciences Data Science Lead: Scott Henderson Modern Antarctic ice loss is largely driven by warm, dense circumpolar deep water (CDW), which reaches the ice sheet margin and causes ice to melt. Antarctic mass loss has significant implications for global sea level rise, but the mechanisms that transport CDW to…
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Automated assessment of butterfly thermoregulatory traits from specimen images
Project Lead: Laura Buckley, UW Biology Data Science Lead: Vaughn Iverson Heterogenous responses to climate change highlight the need to identify the underlying organismal mechanisms. Insects offer an excellent system for investigating mechanisms of climate change responses due to their high sensitivity to environmental conditions and extensive historical records. Dramatic recent declines in insect populations, including of…
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Quantitative HIV Viral Load Monitoring Via Fluorescent Image Analysis
Project Lead: Coleman Martin, UW Chemical Engineering Data Science Lead: Noah Benson In 2014 the United Nations set out to end the HIV/AIDs endemic by 2030 with the goal of having 90% of people living with HIV know their HIV status, be on retroviral treatment, and be virally suppressed. As of 2019, the most recent data, the…