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Open-Source Dynamical Systems Research, with a Side of (Francis) Bacon
No full textThesis (Ph.D.)--University of Washington, 2025Sparse Identification of Nonlinear dynamics (SINDy) is a family of methods for explicitly identifying differential equations from data. The open-source Python package pysindyprovides the engineering to support ongoing SINDy research.
I discuss original and community innovations in smoothing and sparse optimization, as
well as a colocation approach to simultaneous estimation of states and sparse coefficients.
The compatibility of these methods through the pysindy API has lessons for mathematics
as an experimental field.
My contribution to the state of the art includes both original innovations and ongoing
support for research contributions from the community. These innovations include smoothing
methods such as kernel and Kalman, and sparse regression approaches involving Monte Carlo
estimation, physics constraints, or mixed-integer optimization. The pysindy changes have
also allowed a principled approach to simultaneous optimization of states and coefficients.
Across these projects and more, the requirement for a consistent API has given rise to a
common experimental language. This defense codifies that language in additional pacakges
and suggests useful lessons for the open-source, numerical lab
Insight into Enceladus’s ocean chemistry, habitability, and past from fractionation studies of the erupting plume
No full textThesis (Ph.D.)--University of Washington, 2025The erupting plume of Enceladus provides an ideal opportunity to investigate the chemistry and astrobiological potential of the subsurface ocean. However, the complexities of the eruption process likely result in a plume that is chemically fractionated and distinct from its ocean source. Chemical fractionation in the plume is not well understood, but it has ramifications for both extrapolation from plume measurements to ocean composition, and for long-term changes to the ocean chemistry due to preferential eruptive loss. In this work we (1) numerically model gas fractionation over the course of an Enceladus plume eruption, including gas exsolution from the ocean, (2) use laboratory experiments to constrain and validate our numerical models of gas exsolution, and (3) use models to investigate the long-term effects of plume eruption on Enceladus’s bulk chemistry and constrain the longevity of plume eruption. We find that Enceladus’s ocean is likely gas- and ammonium-rich and moderately alkaline, with free energy for methanogenesis. We also find that terrestrial models and measurements of mass transfer can generally be applied to carbon dioxide exsolution under Enceladus conditions, but may underestimate mass transfer coefficients of insoluble gases. Finally, we constrain overall timescales of plume eruption to 30–300 Myr and find that Enceladus’s early ocean may have been carbon dioxide-rich and acidic, but was more likely ammonium-rich and basic. Our work advances our understanding of this small, dynamic moon and the nature of its ocean-plume connection, and provides tools for the interpretation of future spacecraft measurements at Enceladus
Embedded Giants: The Political Economy of Production Networks and Local Business Environments in China
No full textThesis (Ph.D.)--University of Washington, 2025Why do governments differ in the quality of business environments they provide, even under similar political institutions and levels of economic development? This dissertation addresses this puzzle by developing and empirically testing a theory of how firm-level production network complexity shapes both business demand and government supply of public goods. I argue that large firms embedded in complex production networks—those with dense, multi-stage, and interdependent supplier and client relationships—have stronger incentives to seek improvements in legal, regulatory, and infrastructural conditions, and also have greater leverage to induce government responsiveness. These firms face higher coordination risks and are more sensitive to transaction costs in the external business environment, making public goods more critical to their operations.The empirical chapters draw on firm-level survey data, annual reports of publicly listed firms, and firm registry records in China. Chapter 3 shows that firms with high levels of backward and forward linkages place greater importance on business-related public goods. Chapter 4 demonstrates that firms benefit not only from their own political connections but also from those of their supply chain partners in accessing government subsidies. Chapter 5 shifts to the local level, showing that counties where large firms are embedded in complex production networks are more likely to invest in business-friendly infrastructure and regulatory practices. A case study of Kunshan illustrates the underlying mechanisms and addresses endogeneity concerns.
By integrating insights from political economy, development studies, and organizational theory, this dissertation advances our understanding of how the structural characteristics of industrial organizations and market economies shape state behavior and governance. It contributes to the literature on state-business relations and industrial policy, offering new perspectives on China’s subnational governance and the political consequences of industrial development
Examination of Risk and Protective Factors Associated with Suicidal Ideation Among Sexual and Gender Minority Midlife and Older Adults
No full textThesis (Master's)--University of Washington, 2025Purpose: Sexual and gender minority (SGM) individuals have an elevated risk for suicidal ideation (SI) compared to their heterosexual and cisgender peers. However, existing research has primarily focused on SGM youth and young adults, with limited attention given to the aging SGM population. This thesis aims to examine the multifaceted risk and protective factors associated with lifetime SI among SGM midlife and older adults. By integrating the Health Equity Promotion Model and Fluid Vulnerability Theory, this study explores: (1) how social positions, such age, gender, race/ethnicity, sexual orientation, and socioeconomic status, contribute to baseline risk of SI; (2) whether historical/environmental factors, including experiencing discrimination and victimization, influence SI; (3) the role of psychological and behavioral factors that function as risk or protective mechanisms affecting acute risk of SI. Methods: A secondary analysis was conducted utilizing data from the 2014 National Health, Aging, and Sexual/Gender Study, conducted by the Goldsen Institute. A total of 2,425 SGM individuals born before the year of 1965 were included in the analysis. Descriptive statistics were computed to summarize the sociodemographic characteristics, and a multivariable logistic regression model was applied to examine the strength and direction of the associations between SI and the hypothesized predictors from historical/environmental, psychological, and behavioral domains, after controlling for demographic variables. Results: The results indicated that transgender identity, lifetime discrimination, and lifetime victimization emerged as significant baseline risk factors for SI. In the acute risk domain, SI was mainly impacted by depression, drug addiction, and lack of nutrition, while resilience and physical activity served as protective factors. It is worth noting that several factors that are commonly considered to be SI predictors, such as age, sexual orientation, educational attainment, income level, anxiety, and alcoholism, were not significantly associated with SI in the current study. Discussion and Implications: These findings revealed the importance of understanding SI among SGM midlife and older adults through an intersectional and life course lens. Specifically, SI among this marginalized population should be viewed as a response to the broader, accumulated adversities from both personal experiences and structural-level inequities across the lifespan. Clinically, these results underscore the need for developing trauma-informed, culturally responsive SI intervention strategies that focus on behavioral health and personal resilience for this marginalized community. From a policy standpoint, this study demonstrates the importance of strengthening antidiscrimination protections and promoting equitable access to healthcare services across senior service settings for SGM older adults
Diffusion Models for Protein Structure Design: From Backbone Generation to Atomic-Resolution Enzyme Design
No full textThesis (Ph.D.)--University of Washington, 2025The field of protein structure modeling has been revolutionized by the introduction of deep learning methods, particularly AlphaFold2, which has achieved near-experimental accuracy in predicting protein structures from amino acid sequences. This dissertation explores the application of diffusion models to create general solutions to protein design tasks. We introduce RFdiffusion, a model that generates protein structures as a series of backbone frames, which achieves state of the art performance on unconditional generation, motif scaffolding, and protein-protein binder design. We then leverage a broadened molecular vocabulary to predict general biomolecular structures including nucleic acids, small molecules, post-translational modifications, metals, and ions with RoseTTAFoldAA. Using the RoseTTAFoldAA architecture we finetune a diffusion model capable of generating proteins which bind small molecules. Finally, we present RFdiffusion2, a flow-matching model trained from random weight initializations capable of unindexed atomic motif scaffolding, enabling the design of enzymes with complex active sites. In all cases we validate the design capabilities of the models \textit{in vitro}. Our work demonstrates the potential of diffusion models to advance the field of protein design and opens new avenues for enzyme engineering
Mapping the Literary Landscape in the Late Tang: Interpreting the Intellectual World through the Prose of Luo Yin, Lu Guimeng, and Pi Rixiu
No full textThesis (Ph.D.)--University of Washington, 2025The dissertation delves into the often overlooked, underestimated, and misunderstood writers of ninth and tenth-century China. Within the declining years of the Tang dynasty, these scholars have been overshadowed by their predecessors and successors. From imperial China to modern scholarship, their literary contributions have only been recognized as a continuation of the literary legacy from the earlier Tang periods, a transition before a literary renaissance in the Northern Song dynasty, and a representation of the political and social issues of the chaotic time. The dissertation challenges this longstanding conventional view by highlighting the unique qualities of the prose written by Lu Guimeng (d. 881), Pi Rixiu (838-883), and Luo Yin (833-910). By analyzing the collective and individual themes and styles present in their prose, as well as their mastery of literary tradition and innovative approaches, this dissertation illustrates the indispensable value of late Tang prose. The dissertation is structured into two primary sections: textual and contextual analyses, followed by annotated translations. The first section is dedicated to providing an in-depth discussion of the topic, comprising six main chapters. Each chapter explores a distinct topic within the literary world, including remonstrance, reclusion, identity construction, historical writing, political views, philosophical ideology, hobbies, and religious beliefs. The second section serves not only as a reference and appendix to the discussion but also aims to lay valuable groundwork by paying attention to literary allusions, rhetorical devices, grammatical nuances, textual variations, and reception history
3D Hydrogel Formation via a Radical-free and Multiphoton-mediated Oxime Ligation
No full textThesis (Master's)--University of Washington, 2025Light is a unique stimulus with high bioorthogonality, enabling spatiotemporal control in the creation and modification of biomaterials. Photopolymerization permits solid materials to be formed from liquid precursors upon directed light exposure. This technique is valuable in the field of tissue engineering due to its ability to create complex structures with high levels of control. Additionally, light’s compatibility with living systems enables cells to be encapsulated within photopolymerized 3D materials, creating a more replicative environment than traditional 2D cultures, and provides a route towards 4D customization with structures that can vary in both time and 3D space. While this technique improves the programmability of hydrogel formation, many photopolymerizations produce free radicals that can be cytotoxic and cause undesired reactions due to their highly reactive nature. Herein, we introduce and utilize a method to create 3D hydrogels via a radical-free and multiphoton-mediated oxime ligation
Has the use of a digital hand hygiene monitoring tool been associated with decreased prevalence of hospital acquired infections in Siem Reap Provincial Referral Hospital?
No full textThesis (Master's)--University of Washington, 2025The practice of hand hygiene (HH) is a key intervention to decrease the rate of healthcare associated infections (HCAI). We performed a pre-post analysis to assess the association
between the use of a digital monitoring tool for hand hygiene compliance and the prevalence of
HCAI in the Siem Reap Provincial Referral hospital in Cambodia. The study analyzed 10 wards
during the period of 2022-2024 and utilized a generalized linear model for our statistical
analysis. Our study showed a non-statistically significant decrease in HCAI prevalence in the first year of our intervention (OR: 0.83, 95%CI: 0.58-1.20) with a p-value of 0.50. This trend was reversed in
2024 (OR: 1.40 95%CI: 1.06-1.86) with a p-value of 0.02, which we believe to be caused by
unmeasured confounding. HH compliance increased from 29% to 64% at the end of the study
period. Each 10% increase in correct HH compliance was associated with a non-statistically
significant increase of 0.06% in HCAI prevalence (95%CI: -0.10 to 0.22) and a p-value of 0.50.
These results suggest that we need to consider methods to further improve the validity of both
our HH and HCAI data to mitigate bias and misclassification in our current collection methods
Understanding Human–Generative AI Interaction
No full textThesis (Ph.D.)--University of Washington, 2025This thesis offers a thorough analysis of multiple scenarios of human-generative AI interaction, including large-language-model-based search engine optimizations, heterogeneous adoption of generative AI, and the impact of generative AI tools on work. First, I investigate how LLM-powered chat search, exemplified by Bing Chat, selects its information sources. By comparing thousands of Bing Chat citations with traditional search results, I show that it systematically prefers text that is highly readable, well-structured, and of low perplexity. I replicate these findings using a GPT-4 RAG API, demonstrating that these preferences arise from the language models themselves rather than from bespoke engineering. I also find that RAG-cited sites are more homogeneous than those surfaced by classic search algorithms. These insights highlight the distinctive sourcing behavior and economic implications of chat-based search engines. Second, I examine how recent generative AI advances such as ChatGPT create a digital divide. Specifically, I distinguish between a learning divide, referring to differences in how quickly users update beliefs about ChatGPT’s value, and a utility divide, referring to variation in actual per-use benefit. By estimating a Bayesian learning model on six months of clickstream data, I find that lower-educated and non-white users gain greater utility per use but update their beliefs more slowly, whereas younger, male, and IT-background users excel on both fronts. I also identify a belief trap in which persistent underuse results from underestimated utility, and I show that targeted training can reduce this outcome divide. Third, I investigate how daily engagement with large-language-model-based generative AI tools reshapes the structure and focus of work. Drawing on clickstream records, I conduct an empirical analysis of the effect of using generative AI tools on working duration and distraction levels. I find that engagement with these tools significantly increases working hours while simultaneously reducing distraction rates. These findings offer practical guidance for employers and individual employees considering the adoption of generative AI tools for work. Taken together, this thesis lays a solid foundation for future research on human-generative AI interactions and on the broader challenges of AI alignment
Early Childhood Education and Violence Prevention Across the Life Course and Generations
No full textThesis (Ph.D.)--University of Washington, 2025High-quality early childhood education may buffer against social and structural drivers of interpersonal and self-directed violence. This dissertation examined associations of Head Start—a large-scale early childhood education program for low-income children, launched in 1965 as part of the War on Poverty—and violence-related outcomes within and across generations. Intragenerational analyses found that attending Head Start vs. other childcare was associated with lower handgun carrying and serious fighting risk among Black males. Intergenerationally, there was suggestive evidence that maternal Head Start exposure was associated with lower risk of fighting among Black and Hispanic/Latino male offspring. Collectively, findings suggest that early life investments in the social, economic, and human capital of children and families may be effective and equitable tools to prevent interpersonal violence within and across generations