Please join us for a UW Data Science Seminar featuring Amelia Keyser-Gibson and Will von Geldernon Tuesday, October 21st from 4:30 to 5:20 p.m. PT. The seminar will be held in IEB G109.
“Thermal Analysis of Climate Ready Vines”
Abstract: 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 with differing growing habits, performance, rate of growth and leaf morphology have been selected and assigned one of four irrigation deficit treatments based on reference evapotranspiration, soil and weather conditions. Plants in urban landscapes fulfill important ecosystem services such as shading and cooling buildings, and other infrastructure. Experimental plants are grown on standardized trellises and receive one year of establishment irrigation followed by two years of deficit irrigation. Thermal imagery is collected monthly following the initiation of irrigation treatments to quantify leaf temperature across taxa, irrigation treatment and site. We are currently developing a convolutional neural network model for the extraction of temperature data corresponding to plant material to allow for evaluation of if the amount of irrigation has significant implications for vine cooling potential and use to make taxa and irrigation recommendations.
Biography: Amelia is a PhD student in the School of Environmental and Forest Sciences interested in how plants and ecosystems are and will be impacted by climate change. Her current research project investigates plant acclimation to decreased water availability, shifts in performance across a growing season and between plant types by measuring physiological traits across a climatic gradient. Broadly, she hopes to understand more about how the variation and diversity across the plant kingdom influences ability to acclimate (and long term, adapt) to stressors from changing environmental conditions.
“Using Retrieval-Augmented Generation to Analyze Evictions”
Abstract: I will present preliminary results from a project that uses computer vision and natural language processing to document tenant responses to eviction summonses and connect tenants’ response patterns to subsequent case outcomes. As a part of the eScience Institute’s Data Science and AI Accelerator, I worked with eScience Data Scientist Curtis Atkisson to measure tenant behavior and case outcomes using text extracted from ~195,000 pdf documents from ~8,500 eviction cases in Pierce County, WA filed between 2022 and 2024. Using retrieval-augmented generation (RAG) including LLM analysis, we documented the links between tenants’ submission of written responses, attendance at show cause hearings, and access to legal assistance from Washington’s right to counsel (RTC) program. This novel data also allows us to examine the relationship between legal representation and case outcomes. Results show that legal representation is provided to less than 50% of tenant households facing an eviction despite the broad eligibility criteria in Washington’s RTC program. Our findings also highlight the importance of several critical “administrative checkpoints” during eviction cases and suggest possible reforms that could increase tenants’ access to legal representation.
Biography: Will von Geldern (he/him) is a PhD candidate at the UW Evans School of Public Policy & Governance. He uses mixed methods to examine the effects of public policies and legal systems on the health and wellbeing of marginalized communities. His dissertation uses qualitative analysis, data science, and experimental methods to study the barriers that prevent tenants from accessing legal assistance during evictions.