Cassia Blossoms

Holograph (photocopy).Words by Li Ch'ing-Chao, translated from Chinese, also printed as text preceding score.At end: March 1988, Seattle, Washington.Premiered at the Bennington Chamber Music Conference and Composer Forum of the East, Aug. 10, 1988.Duration: 9:00.Contact [email protected] for more informatio

An Assessment of Noise Pollution Propagated by WSDOT Ferries in the Puget Sound

Increasing ferry traffic in the Puget Sound and Salish Sea raises concern for marine mammals due to noise pollution. This is not a topic of major environmental concern in the design process for future ferry generations. The factors of vessel type that influence noise levels are not known, and thus not used as a means of minimizing noise pollution. For the sake of sustaining future marine mammal populations in an environment of growing vessel traffic, this project tested the levels of noise pollution from two class of ferries in the Puget Sound. Multiple linear regressions with interactions and ANOVAs determined the relationships between continuous and categorical variables. Results determined one or more categorical variables influence SPL and kinetic variables that influence SPL are acceleration and range. These data are useful in quantifying the current acoustic overlap for different marine mammal groups and in minimizing the noise levels of new ferries

Knowledge as Infrastructure: The Economy of Private Ownership in Digital Academia

Bachelor of Arts (BA)This thesis examines the governance failures produced by the increasing privatization of digital knowledge infrastructure in higher education. As academic publishing, learning management systems, and research tools consolidate under a small number of private firms, the shared resources that sustain scholarly communication and learning face conditions that resemble Common-Pool Resource dilemmas as described by Elinor Ostrom. The central argument is that academic knowledge production functions as a knowledge commons, and that private control over the platforms supporting it introduces structural governance failures that threaten the sustainability of open scholarship. The analysis applies Ostrom’s Institutional Analysis and Development framework to map the actors, rules, and incentive structures that shape how academic platforms operate. It draws on Ostrom’s design principles for sustainable commons institutions to evaluate governance failures in the learning management system market, with particular attention to data collection practices, vendor accountability, and the erosion of institutional rule-making authority. Robert Axelrod’s cooperation theory is used to explain why the current arrangement persists and what conditions would be necessary to change it. Primary interview data collected from a Director of Digital Learning at the University of Washington Tacoma supplements published sources and provides an institutional perspective on vendor dependency, AI integration, and the challenges of building self-hosted alternatives. The thesis finds that privatized digital knowledge infrastructure consistently violates the governance conditions that Ostrom identifies as essential to commons sustainability. Consolidated vendors concentrate monitoring authority and rule-making power while academic institutions, operating under uneven funding recovery from the 2008 recession, have limited capacity to build or negotiate alternatives. Recent events including the Anthology Inc. bankruptcy and the Amazon Web Services outage of October 2025 illustrate the concrete risks of this dependency. The paper recommends several interventions. It argues for platform-neutral and adaptable institutional governance frameworks, enforceable vendor accountability mechanisms, and investment in open-source and cooperative infrastructure alternatives. It also proposes a structured work-study or apprenticeship model in which students maintain the digital infrastructure they depend on, connecting community governance principles to practical institutional labor needs. These recommendations are grounded in existing cooperative models including the Public Library of Science, arXiv, and Moodle, and are framed as actionable directions for both institutional practice and future research

China Recharted: The Zou Family’s Cartographic Enterprise and the Making of Chinese Territoriality in the Late Qing, 1850-1911

Thesis (Ph.D.)--University of Washington, 2026In the age of Google Maps, we sometimes mistakenly assume map literacy, but the ability to read meaning within maps requires long-term exposure and instruction. While scholarship has demonstrated how Qing China (1644-1911) utilized cartographic projects in its territorial expansions of the seventeenth and eighteenth centuries, far less attention has been paid to how new maps in the late 1800s impacted the national consciousness of Qing elites. Analyzing these new maps reveals that the Chinese nation as a spatial concept had appeared in the 1880s, earlier than China’s defeat by Japan in 1895, the year commonly seen as marking the beginning of Chinese nationalism by many scholars. In addition, these maps indicate two important realities about the construction of the Chinese nation during this period: 1) that conservatives utilized these maps to conceptualize the Chinese nation, and 2) the influence of capitalist markets upon map production. First, people involved in the creation of these maps were not revolutionaries or reformists but conservative businessmen. Although Chinese conservatives were blamed for the Qing’s failure to modernize, they used cartographic products to transmit their views of the Chinese nation to the reading Chinese public. Second, in order to maximize profits, these conservative businessmen produced their products based upon considerations of each map’s cost and marketability. Relevant factors included each map’s type of paper, size, and quantity, as well as the salaries of draughtsmen and the tastes of the public. Unlike the eighteenth-century atlases made in the Qing court, commercial map production in the late 1800s was influenced by the interactions between map businessmen and consumers of the Han Chinese reading public. Based on these two realities, this dissertation shows how the commercial and the social factored into map production and, in turn, the conceptualization of the Chinese nation in late Qing China

Multi-modal profiling reveals epithelial hierarchy disorganization underlying field cancerization in head and neck cancer

Thesis (Ph.D.)--University of Washington, 2026Local recurrence rates in head and neck squamous cell carcinoma (HNSCC) exceed 50%, potentially due to field cancerization, a phenomenon where tissue that appears normal microscopically actually harbors molecular changes that can give rise to new tumors. The prevailing model assumes these "at-risk" tissues share driver mutations with adjacent tumors, but whether field cancerization depends solely on mutations remains unknown. To comprehensively characterize this phenomenon, we profiled matched tumor, normal-adjacent field (NAF), contralateral normal, and blood samples from HPV-negative HNSCC patients using whole genome sequencing, targeted driver gene sequencing, single-nucleus multiome profiling, and functional cell-fate tracing assays. While histologically normal NAF tissues did harbor expanded mutant clones, these mutations rarely overlapped with paired tumors and were not shared across patients, suggesting features beyond mutations are altered in NAF. Single-cell multiomics revealed that NAF epithelium loses its normal organizational hierarchy: basal stem cell markers persist in cells that should be differentiating, while terminal differentiation programs fail to activate. Proliferating cells appeared in tissue layers normally restricted to post-mitotic cells, a pattern typically seen only in overt dysplasia. Additionally, we identified a distinct "emerging state" cell population enriched in NAF that expresses tumor-associated markers and transcriptionally bridges normal epithelium and tumor, which we spatially identify using immunofluorescence staining of key markers. Together, our findings demonstrate that field cancerization operates through epithelial hierarchy disorganization, disrupting differentiation and generating cells with tumor-like features, all within tissue that appears histologically normal

Leadership Strategies, Employee Engagement, and Organizational Resilience: A Multi-Dimensional Analysis of Global Crises

Bachelor of Arts (BA)The COVID-19 pandemic constituted a prolonged and multifaceted global crisis that significantly disrupted organizational operations, employee well-being, and leadership practices across sectors and geographic regions. This literature review examines how leadership strategies influence employee engagement and organizational resilience during global crises, with particular emphasis on empirical findings from the COVID-19 pandemic. Looking at interdisciplinary research from organizational psychology, management, healthcare leadership, and cross-cultural studies, the review synthesizes evidence demonstrating that leadership behaviors grounded in transparent communication, empathy, and employee empowerment are central to sustaining employee engagement under crisis conditions. Across diverse organizational and cultural contexts, psychological safety and trust consistently emerge as key mediating mechanisms linking leadership behavior to employee engagement and resilience outcomes. When leaders communicate clearly, demonstrate empathy, and empower employees to participate in decision-making, employees are more likely to remain engaged during periods of disruption. The review further highlights cross-cultural similarities and differences in crisis leadership practices, emphasizing the importance of culturally responsive, human-centered leadership approaches. By integrating crisis leadership theory with employee engagement and resilience research, this paper proposes a conceptual model positioning leadership as the primary driver of engagement-mediated organizational resilience. The findings offer practical implications for organizations seeking to strengthen crisis preparedness and inform future research on leadership development, engagement strategies, and long-term organizational resilience

Scalable Data Paradigms for Steering General-Purpose Language Models

Thesis (Ph.D.)--University of Washington, 2026Pretrained Language Models (LMs) have demonstrated remarkable general-purpose capabilities by encoding vast amounts of knowledge from the internet. However, effectively steering these models to serve diverse downstream applications, such as following instructions, chatting with users, using tools, or performing complex reasoning, poses another set of challenges that require diverse, high-quality, and increasingly costly training data. This dissertation explores scalable paradigms for structuring, creating, and optimizing data to facilitate the broader generalization of language models and enhance their critical capabilities.First, through the creation of the SuperNaturalInstructions benchmark—a large-scale dataset with over 1,600 NLP tasks—I demonstrate that unifying NLP tasks via natural language instructions enables model generalization at the task level. Second, I propose Self-Instruct, a novel framework where LMs generate their own instructional data to train themselves, thereby demonstrating model self-improvement. Third, I develop HyPER, a framework that routes preference annotation tasks between humans and AI to optimize data quality and collection efficiency for preference-based learning. Finally, I systematically study the impact of diverse open instruction-tuning datasets on LM capabilities, leading to the development of the Tülu series of openly available and highly capable models. Together, these efforts—unifying task structures, leveraging model-generated synthetic data, optimizing human-AI data partnerships, and fostering open data ecosystems—have demonstrated an effective path to building a strong, scalable, and community-driven data foundation for post-training language models. Finally, I envision future directions that can further enhance this data foundation for building more advanced and sustainable AI systems

Programming tension in 3D-printed networks inspired by spiderwebs

Each element in tensioned structural networks—e.g., tensegrity or architectural fabrics—requires a specific tension to achieve the desired shape and stability. These structures are challenging to manufacture, 3D print, or assemble because flattening them during fabrication introduces multiplicative inaccuracies in the final tension gradients. We overcome this challenge by offering an algorithm for direct 3D printing of such networks with programmed tension gradients, analogous to the spinning of spiderwebs. The algorithm: (i) defines the desired network and prescribes its tension gradients; (ii) converts it into an unstretched counterpart by optimizing element lengths and converting straight elements into arcs; and (iii) decomposes the network into printable toolpaths; with the option to: (iv) flatten curved 2/3D networks to ensure printing compatibility; and (v) automatically resolve unwanted crossings introduced by flattening. Experimental validation is achieved using 2D unit cells with <1.0 % strain error in the tension gradients. The method remains effective for networks with a minimum element length of 5.8 mm and a maximum stress of 7.3 MPa. Fabricating complex cases is demonstrated for flat spiderweb, curved mesh, and tensegrity networks. The method represents a stepping-stone toward developing compact, integrated cable networks and orthotic devices with programmable moment-exerting structures.Support provided by the National Science Foundation Award No. 2341950

The Convex Algebraic Geometry of Higher-Rank numerical Ranges

Thesis (Ph.D.)--University of Washington, 2026The higher-rank numerical range is a convex compact set generalizing the classical numerical range of a square complex matrix, first appearing in the study of quantum error correction. In this thesis, we will discuss some of the real algebraic and convex geometry of these sets, including a generalization of Kippenhahn’s theorem, and describe an algorithm to explicitly calculate the higher-rank numerical range of a given matrix. We will also discuss the inverse field of values problem, an inverse problem on the numerical range. We focus on the geometric properties of the set of solutions. Finally, we consider an analogous problem for higher-rank numerical ranges and show how to solve it using the ideas behind the proof of convexity for these sets

The Value of Resilience: Flood Risk, Information Disclosure, and Housing Markets in New York City

Thesis (Ph.D.)--University of Washington, 2026Flood risk increasingly shapes where households live, how much they pay for housing, and how safety is traded off against affordability in U.S. urban housing markets. As climate change intensifies flooding hazards and expands exposure beyond traditionally recognized high-risk areas, many households face constrained choices between safer locations and affordable housing. Historically, housing markets have often failed to fully price flood risk, reflecting limited disclosure, uneven risk communication, and uncertainty about whether public mitigation investments meaningfully reduce risk. As flood risk information becomes more visible and as governments invest in resilience, understanding how households and markets navigate the trade-off between safety and housing costs is critical for equitable urban policy. This dissertation examines how flood risk, information disclosure, and mitigation investments interact to shape housing market outcomes, with a particular focus on New York City. The first study systematically reviews the empirical literature on climate-related hazards and housing prices, highlighting how research has evolved from disaster-focused analyses toward frameworks that examine ongoing risk exposure and household decision-making. The review emphasizes how flood risk introduces a persistent safety-affordability trade-off in housing markets and identifies gaps in how studies account for information disclosure and mitigation as mechanisms that may alter this balance. The second study examines how the evolving flood-risk information environment, including the release of risk data on real estate platforms and new disclosure requirements, affects housing prices over time using an interrupted time series approach. The findings show modest and uneven market responses, with disclosure events shifting housing price trends rather than causing abrupt repricing, suggesting gradual diffusion of flood-risk information in housing markets. The third study evaluates whether community-level flood mitigation activities influence the relationship between flood risk and housing prices using transaction-level hedonic models. The findings show that some mitigation investments can partially offset the negative capitalization of flood risk by signaling improved safety and resilience, although the magnitude of these effects varies across neighborhoods and types of intervention. Taken together, these studies demonstrate that flood risk is not simply capitalized into housing prices but negotiated through trade-offs among safety, affordability, and trust in public action. Risk disclosure can gradually reshape market behavior by increasing the visibility and salience of climate risk, while mitigation investments influence whether households view flood-prone locations as viable long-term housing options. By linking flood risk analytics, market behavior, and public investment, this dissertation provides policy-relevant insights into how cities can manage climate risk while addressing housing affordability and social equity