Category: Incubator Project

• Universe of IGOs: Measuring Heterogeneity and Distributions of Member States

  

  Project Lead: Jihyeon Bae, UW Political Science Data Science Lead: Curtis Atkisson Does having a diverse mix of member states make an inter-governmental organization (IGO) more or less cooperative? Scholars have long debated whether regime heterogeneity, especially variation in democracy levels, helps or hinders intergovernmental organizations (IGOs). Yet despite rich theoretical discussions, empirical findings remain…

• Creating a code base for on- and offline analysis of ultrafast X-rayspectroscopy data recorded at the chemRIXS instrument

  

  Project Lead: Amke Nimmrich, UW Chemistry Data Science Lead: Bryna Hazelton X-ray Free Electron Lasers help us more deeply understand the details of a chemical reaction. They are large scale facilities providing ultrashort pulses of X-ray light at high repetition rates. These light pulses can be used to observe reaction dynamics in real time (femto-…

• Climate Ready Vines Thermal Image Analysis for Cooling Potential

  

  Project Lead: Amelia Keyser-Gibson, UW Environmental and Forest Sciences Data Science Leads: Noah Benson and Bernease Herman  The Climate Ready Vines project is a multi-state collaborative research effort to evaluate and monitor potential energy saving, water use, ecological, physiological and horticultural characteristics of vine plants across different climates and latitudes in the Western U.S. Vine taxa…

• Building a Sustainable, Open Source Workflow for the Self-Sufficiency Standard

  

  Project Leads: Lisa Manzer, Annie Kucklick, and Sarah Brolliar, UW Social Work Data Science Lead: Anshul Tambay The Self-Sufficiency Standard measures how much income families need to meet their basic needs without public or private support. Used by researchers, policymakers, and advocates nationwide, the Standard draws on detailed local data such as housing, child care,…

• Improving Data Quality in Eviction Research

  

  Project Lead: Will von Geldern, UW Public Policy & Governance Data Science Lead: Curtis Atkisson Evictions cause many harmful impacts on housing-insecure households and low-income communities. Most sociological and policy research has used two measures of evictions (filings and judgments) to identify and measure the consequences of the modern eviction crisis. This study will help advance what…

• The Use of Machine Learning to Predict Hospital Readmissions After Lower Limb Amputation in the Medicare Population

  

  Project Lead: Rachael Rosen, UW Medicine Data Science Lead: Valentina Staneva Lower limb amputation (LLA) is a significant health event that is often an indicator for worsening chronic disease and increased risk of further health decline—especially among older adults.  After amputation, recovery depends not only on medical care but also on access to supportive post-acute care services,…

• A web-based interface for rare disease lumping and splitting predictions with LumpIt

  

  Project Lead: Shirin Khanam, Jessica Chong, and Allison Marcello, UW Pediatrics Data Science Lead: Bernease Herman Rare genetic disorders affect 263-446 million persons or ~3.5–5.9% of the worldwide population, and the vast majority of these persons have a Mendelian condition (MC). Over 4,500 genes underlie one or more of the 6,000 MCs described to date, and…

• Deep Learning to Uncover Watershed Specific Characteristics in Salmon Otolith Patterns to Aid in Management of Pacific Salmon

  

  Project Lead: Ben Makhlouf and Daniel Schindler, UW Aquatic and Fisheries Sciences Data Science Lead: Valentina Staneva Pacific salmon are vital to Alaskan communities, serving as a key cultural, subsistence, and economic resource. However, Chinook salmon populations in Western Alaska have declined sharply in recent years, particularly in the Yukon, Kuskokwim, and Nushagak River basins. While many…

• Detection of Early Warning Signals regarding Safety Concerns of Implantable Medical Devices

  

  Project Lead: Aparna Ramanathan, UW Medicine Data Science Lead: June Yang and 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…

• 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…