Category: Incubator Project

• Challenges to Climate Adaptation Among Organic Farmers in the U.S.

  

  Project Lead: Masha Vernik, UW Environmental and Forest Sciences Data Science Lead: Curtis Atkisson Description: As seasons become less predictable and extreme weather events become more intense and frequent, farmers learn to adapt.  Adaptation can mean anything from building new infrastructure that’s out of a flood zone to installing improved irrigation lines; it can mean shifting crop…

• Updating Open-Source Verbal Autopsy Software to Modern Python Standards

  

  Project Lead: Abraham D. Flaxman, UW Global Health Data Science Lead: Bryna Hazelton, Naomi Alterman The purpose of this project was to modernize SmartVA-Analyze, an existing open-source verbal autopsy (VA) software, by transitioning its codebase from Python 2 to Python 3. Verbal autopsy is a crucial tool for estimating the causes of death in settings where…

• Assessing Influences of Wildfires on Park Visitation Patterns Using Gravity

  

  Project Lead: Nino Migineishvili, UW Computer Science and Engineering Data Science Lead: Spencer Wood Wildfires have been growing in size, duration, and destructivity, resulting in more decisive calls to improve forest health and protect communities. Wildfire fuel treatments – which  involve reducing or removing vegetation from fire-prone areas – are one strategy for reducing wildfire risk. Where…

• Polygenic and Contextual Determinants of Alzheimer’s Disease and Related Dementias

  

  Project Lead: Diane Xue, Institute for Public Health Genetics Data Science Lead: Bryna Hazelton One in three people over the age of 65 dies with dementia. The most common cause of dementia is Alzheimer’s disease (AD), a progressive neurodegenerative disorder influenced by genetic and environmental factors. Dozens of genetic loci have been linked to AD and related…

• Illuminating the role of cold-pools in structuring shallow convection

  

  Project Lead: Hauke Schulz, Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES) Data Science Lead: Bernease Herman Shallow convection, like the stratocumulus decks off the Washington coast, is responsible for a large portion of the uncertainty in climate projections, thus a better understanding of their processes is crucial. Advances in computational resources allow for ever increasing…

• What do the leaders say? Analysis of the United Nations General Debate Corpus

  

  Project Lead: Jihyeon Bae, Ph.D. Candidate, Political Science Data Science Lead: Valentina Staneva Every year, more than 200 state representatives open the United Nations General Assembly meeting with statements during the General Debate (UNGD). The UNGD speech floor provides a rare opportunity for all states to equally have their voices heard by a wide range of audiences.…

• Investigating germline genetic influence on somatic immune traits in non-cancerous tissues

  

  Project Lead: Tabitha Harrison, UW Epidemiology Faculty Advisor: Sara Lindström, Epidemiology Data Science Lead: Vaughn Iverson Cancer is a significant health burden in the US, causing substantial morbidity and mortality. This research project builds on past studies demonstrating that inherited genetic variants can influence how our immune system affects cancer risk and survival. While prior work has linked…

• Characterizing glacial lake outburst flood hazard at a regional scale using fused InSAR-speckle tracking surface displacement time series

  

  Project Lead: George Brencher, UW Civil & Environmental Engineering Data Science Lead: Scott Henderson Glacial lakes are distributed in alpine terrain worldwide and are frequently dammed by unstable glacial moraines. These moraine dams can fail, causing lakes to rapidly drain and flood downstream valleys. Glacial lake outburst floods (GLOFs) are a significant hazard for high-elevation infrastructure and…

• Investigating Structure of Social Science Research Datasets for Better ML Evaluation

  

  Project Lead: Bernease Herman, eScience Data Scientist Specialized machine learning architectures, such as deep learning, typically rely on inductive biases and other data-specific correlational structure information to produce more effective models. Similarly, the design and evaluation of differentially private synthesizers depends heavily on the correlational structure of the datasets most commonly used in the field. We…

• Wetland Communities in the US

  

  Project Lead: Celina Balderas Guzman, UW Assistant Professor of Landscape Architecture Data Science Lead: Spencer Wood Sea level rise threatens human communities on the coast with a variety of hazards including erosion and flooding. However, these risks are reduced in locations where coastal wetlands provide a natural buffer that absorbs the force of waves created by storms.…