Category: Incubator Project

• A novel regression framework for Southern Ocean surface carbon reconstruction using merged observations from ships and autonomous floats

  

  Project Lead: Sangmin Song, Oceanography Data Science Lead: Scott Henderson The ocean holds a massive 93% of the world’s carbon that cycles among the atmosphere, land, and sea. Because of its capacity to absorb vast amounts of human-emitted carbon from the atmosphere each year, the ocean has effectively buffered society’s impact on climate over the…

• Investigating Seasonal Glacier Fluctuations in Northeast Greenland Using Machine Learning and Explainable Artificial Intelligence

  

  Project Lead: Claire Jensen, UW Earth and Space Sciences Data Science Lead: Scott Henderson The Greenland Ice Sheet (GrIS) is losing mass due, in part, to the recent speedup of many of the outlet glaciers that line the ice sheet. Mass loss from outlet glaciers can be characterized by (1) retreat of the glacier’s frontal…

• Using Computer Vision to Understand Collective Navigation in Salmon

  

  Project Lead: Andrew Berdahl, UW School of Aquatic and Fishery Sciences and Ben Koger, University of Wyoming School of Computing and Department of Zoology and Physiology Data Science Lead: Valentina Staneva From daily foraging movements to long-distance migrations, animals often travel in groups, and their navigational decisions are influenced by those around them. Theory suggests that…

• Enhancing LSTM streamflow modeling in data-scarce rain-dominated basins: the impact of using multiple precipitation products as model inputs

  

  Project Lead: Hernán Querbes Duhart Data Science Leads: Nicoleta Cristea and Scott Henderson GitHub Repo Uruguay relies heavily on hydropower, with three dams along the Río Negro providing nearly half of the country’s electricity. Accurate streamflow modeling is therefore critical for dam operations and energy reliability. Machine learning, particularly Long Short-Term Memory (LSTM) networks, has…

• On testing hearing sensitivity across the animal kingdom more quickly and accurately

  

  Project Lead: Aoi Hunsaker, Andrew Brown and Joseph Sisneros, UW Psychology Data Science Lead: Ariel Rokem I study what sounds animals can hear by recording brain responses while I play sounds over a speaker. This kind of test is called the Auditory Evoked Potential (AEP) test. There is a need in my field to do these recordings…

• HuskyFetch API

  

  Project Leads: Jason Civjan, Zahra Taher, Adelin Ma, and Maeve Seyer, UW IT Data Science Lead: Curtis Atkisson UW-IT’s Student Innovation Lab (SIL) is dedicated to helping UW students from all disciplines explore solutions to problems facing the UW community. We provide access to UW data, resources, and consultations to support fast, effective, and responsible…

• Longitudinal Uptake Patterns in Patients with Grade 1-2 Well-Differentiated Gastroenteropancreatic Neuroendocrine Tumor on Long-Acting Somatostatin Analogs

  

  Project Lead: Ai Phuong S. Tong, UW Medicine Data Science Lead: Curtis Atkisson Our project explored how a specialized imaging technique called somatostatin receptor (SSTR) positron emission tomography (PET) changes over time in patients with neuroendocrine tumors, a type of slow-growing cancer that often affects the gastrointestinal system. These scans help doctors visualize tumors by…

• Retinal Circuit Model for Color Vision

  

  Project Leads: Kathryn Tabor and Jay Neitz, UW Medicine Data Science Lead: Noah Benson You pick a ripe, red strawberry outside in the bright sunshine, and shortly thereafter the same fruit still appears the same shade of red in the dimly-lit kitchen, even though the spectrum of light reaching the eye has changed dramatically. Color…

• Large Language Models for Predicting Survival in Non-Small Cell Lung Cancer from Pathology Reports

  

  Project Lead: Jie Fu, UW Medicine Data Science Lead: Joseph Hellerstein Pathology reports contain detailed descriptions of tumor characteristics, but much of this information is unstructured text that is difficult to analyze with traditional methods. In this project, we explore how large language models (LLMs), advanced AI systems designed to understand and interpret human language,…

• Predictors of rehabilitation therapy intensity during skilled nursing facility stays

  

  Project Lead: Rachel Prusynski, UW Medicine Data Science Lead: Curtis Atkisson Over a million Medicare beneficiaries receive nursing and rehabilitation therapy – physical therapy (PT), occupational therapy (OT), and speech language pathology (SLP) services annually in skilled nursing facilities (SNFs) after hospitalization. The goal of post-acute SNF care is to facilitate medical and functional recovery…