http://www.rssboard.org/rss-specification 720 https://escholarship.org/uc/ucla_etd/rss Recent eScholarship items from UCLA Electronic Theses and Dissertations Fri, 15 May 2026 07:17:53 +0000 https://escholarship.org/uc/item/12m258vw The advent of new functional assays give researchers new ability to connect genetics to function. In turn, careful and specialized computational methods can use these data to ask questions about genetic regulation and architecture. In my first project I developed dotears, a method for learning causal gene regulatory networks using Perturb-seq data, with guarantees of statistical consistency under mild assumptions as well as improved performance in simulations and real Perturb-seq data. In my second project I developed keju, a Bayesian hierarchical model that estimates transcription rate and differential activity in Massively Parallel Reporter Assay data. keju improves inference by tying uncertainty estimation to assay design, with better power and calibration than previous methods. Together, these methods use functional assay data to better characterize causal gene-gene regulation and the impacts of genetic variation on transcription in varied contexts. https://escholarship.org/uc/item/12m258vw Tue, 12 May 2026 00:00:00 +0000 Xue, Albert Shaoyang https://escholarship.org/uc/item/6b98j4jq 2025 marks the 15th year anniversary of the Biologics Price Competition and Innovation Act. It is imperative to evaluate whether biosimilars have achieved the desired policy outcomes. This three-paper doctoral dissertation comprehensively examined the impact of biosimilar entry into the U.S. biologics market from three aspects: market competition, utilization, and financial implications. Drawing on three economic models, the first paper investigated the evolution of prices and market shares for biosimilars and reference products, as well as the determinants underlying these patterns. This paper found that the extended Stackelberg game model is the best model for the overall biosimilar market as well as the submarket where the premium pricing strategy was employed by the branded firm. The Bertrand model with product differentiation model is the best model for the submarket where the aggressive pricing strategy was used.The second paper examined treatment initiation with biosimilars... https://escholarship.org/uc/item/6b98j4jq Tue, 5 May 2026 00:00:00 +0000 Liu, Xiaoyu https://escholarship.org/uc/item/9jm060wd Ovarian hormones, estradiol and progesterone, have been identified as a female-specific biological factor that influences the consumption of substances of abuse, such as alcohol and cigarettes. Animal models show an enhancing effect of estradiol on alcohol and cigarette use, whereas progesterone has been demonstrated to protect against alcohol and cigarette use. Many clinical studies have evaluated the effect of menstrual cycle phases on alcohol and cigarette use as a proxy for ovarian hormone levels. However, fewer clinical studies have investigated the association of ovarian hormones with alcohol and cigarette use, and it is unknown whether ovarian hormones are differentially associated with alcohol and cigarette use. To translate preclinical findings, further investigations of the effect of menstrual cycle phases and ovarian hormones on alcohol and cigarettes in clinical populations are necessary. Additionally, sensitivity to ovarian hormone fluctuations is a hypothesized etiology... https://escholarship.org/uc/item/9jm060wd Thu, 30 Apr 2026 00:00:00 +0000 Henry, Brittany https://escholarship.org/uc/item/79h2d3p4 This dissertation investigates the fraught and often-ambiguous relationship between politics and substantive human meaning – considered here broadly as a framework within which individual human actions are situated and that suggests lives worth living, a proper order of human affairs, the appropriate relations between individuals or social/political positionalities, and/or the larger significance of human endeavor, suffering, etc. This project claims that discussions of the relation of meaning to politics are today trapped in a paradigm oriented around the liberal principles of secularism and public neutrality and whether these principles render liberal politics “meaningless” and thus uniquely susceptible to irruptions of meaningful politics from exclusivist nationalism, far-right populism, and religious fundamentalism. By engaging with three key participants in the German secularization debate (1922–1976), Carl Schmitt, Karl Löwith, and Eric Voegelin, and one late entrant... https://escholarship.org/uc/item/79h2d3p4 Thu, 30 Apr 2026 00:00:00 +0000 Campbell, Joshua William https://escholarship.org/uc/item/0263419c Electrochemical energy storage is essential for transportation electrification, grid-scale storage, and broader energy sustainability. Achieving these goals requires battery chemistry that is not only high-energy and fast charging, but also safe, durable, and practical under realistic operating conditions. In many next-generation batteries, these performance metrics are governed not simply by bulk materials, but by active interphases, where ion transport, electron transport, solvation, and parasitic reactions are tightly coupled. My dissertation centers on understanding and controlling active interphases across different battery systems, with a particular focus on two fundamental questions: how interfacial transport governs electrochemical performance, and how interfacial reactivity drives degradation and can be mitigated. The first part of this dissertation focuses on quantifying and regulating interfacial transport. In lithium metal batteries, I developed a separator-free... https://escholarship.org/uc/item/0263419c Mon, 27 Apr 2026 00:00:00 +0000 Liu, Bo https://escholarship.org/uc/item/0v64q8sh A physics-based digital twin framework is developed for transient molybdenum pentachloride (MoCl$_5$) transport in an optically-accessible, experimental atomic layer deposition (ALD) reactor at the National Institute of Standards and Technology (NIST). The framework is anchored to high-speed absorption-imaging measurements reported by NIST and is implemented using a three-dimensional, time-resolved computational fluid dynamics (CFD) model that resolves momentum, heat, and species transport during pulsed precursor delivery. Experimentally measured, time-dependent absorbance data are used to inform the inlet precursor waveform, enabling direct comparison of normalized transport behavior between simulation and experiment in the absence of calibrated absolute concentrations. The digital twin of the reactor gas delivery system is validated against multiple experimental observables, including inlet velocity, precursor buildup and decay dynamics, residence time, spatial plume structure,... https://escholarship.org/uc/item/0v64q8sh Tue, 21 Apr 2026 00:00:00 +0000 ALGHAMDI, ABDULRAHMAN https://escholarship.org/uc/item/4br3b0ft We investigate the energy-critical nonlinear Schr¨odinger equation, the generalized Korteweg– de Vries equation, and the energy-critical nonlinear wave equation: respectively,where u(t, x) is a function in spacetime Rt × R d x for d as above.For each of these models (assuming k ≥ 8 for (∗∗)), we prove that solutions exhibit pointwise-in-time dispersive decay, requiring only that initial data lie in a scaling-critical space. In particular, global, scattering solutions will decay at the same rate as the underlying linear model. In addition, for the model (∗), we demonstrate dispersive decay for the final-state problem, assuming only that scattering data lie in a scaling-critical space. Finally, for the model (∗∗) in the case 4 ≤ k < 8 (including the mass-critical k = 4) we prove dispersive decay with the additional assumption that initial data lie in a near-scaling-critical space.[Equation omitted]. https://escholarship.org/uc/item/4br3b0ft Sat, 11 Apr 2026 00:00:00 +0000 Kowalski, Matthew John https://escholarship.org/uc/item/3ch433fj This thesis presents the design, implementation, and operation of a data ingestion and visualization system built to support live monitoring and long-term research analysis needs of three distributed water treatment and desalination (DWTD) systems serving small rural communities in the Salinas Valley of California. This system, which has operated continuously for six years, has collected over one billion time-series data points, including sensor readings, valve positions, and programmable logic control (PLC) states. This operational data was combined with over 30,000 audio recordings of the systems’ pumps and actuators to develop inference models to reconstruct treatment system state from passive acoustic monitoring. Built on embeddings from a large pretrained neural network, a neural multi-label prediction model trained on the dataset achieved an F1 score of 0.557 in determining four individual pump states across a single site, and over .85 F1 score on multiple individual pumps.... https://escholarship.org/uc/item/3ch433fj Fri, 27 Mar 2026 00:00:00 +0000 Aguilar, Christian Bernardo https://escholarship.org/uc/item/8sv7c3mc This study used a qualitative case study design to follow up on the implementation of a completed research project (TEDI). While TEDI examined screening-based reading interventions in three different elementary schools, this study sought to examine three questions around implementing school-based interventions for students with dyslexia: (1) What do researchers need to consider with designing school-based studies? (2) What structural and internal changes do schools need support in making to accommodate school based intervention? and (3) How can future school-based research accommodate the needs of both researchers and schools? Through surveys and interviews of five personnel from the three schools and a focus group with the three researchers involved with TEDI, this study offers insight into participants' experiences during and after the TEDI study. These experiences highlighted ways in which schools benefited from participating and had a successful implementation. These successes... https://escholarship.org/uc/item/8sv7c3mc Thu, 26 Mar 2026 00:00:00 +0000 Pedroza, Veronica https://escholarship.org/uc/item/8pz030t0 Wafer-scale integration (WSI) using the Silicon Interconnect Fabric (Si-IF) enables heterogeneous assembly of thousands of bare dies on a single 300 mm wafer, supporting up to 50 kW of total power consumption. The power density of modern high-performance compute chips is rapidly approaching 1W/mm^2, and supplying tens of kilo-amperes at ∼1 V from a 48 V supply through conventional peripheral distribution leads to prohibitive IR drop, routing congestion, and poor scalability. Meeting this demand requires backside power delivery modules that simultaneously achieve a system-level conversion efficiency exceeding 85% and a power density on the order of 1W/mm^2—targets that neither existing PCB-based converters nor MEMS-based microtransformers have demonstrated. This thesis proposes a 4×12:1 stacked microtransformer architecture for Si-IF backside power delivery. Through a system-level efficiency budget and loss allocation analysis, the standalone transformer efficiency requirement... https://escholarship.org/uc/item/8pz030t0 Thu, 26 Mar 2026 00:00:00 +0000 LEE, NAMKANG https://escholarship.org/uc/item/8438495g Understanding how catalyst structure influences chemical reactivity is essential for design of materials for chemical transformation and environmental remediation. At the atomic scale, catalytic activity depends not only on the intrinsic properties of a material but also on the local coordination, electronic structure, and dynamic restructuring of surface atoms under reaction conditions. Computational modelling, particularly density functional theory (DFT), provides a framework for probing these factors and elucidating reaction mechanisms that are difficult to access experimentally. This dissertation employs atomistic simulations, combined with in-situ experimental observations, to investigate how surface structure and restructuring influence reactive sorption and catalytic processes on metal and metal oxide systems.The first part of this work examines the reactive sorption of hydrogen sulfide on CuO surfaces. DFT calculations reveal that the reactivity of CuO is strongly dependent... https://escholarship.org/uc/item/8438495g Thu, 26 Mar 2026 00:00:00 +0000 Jiang, David https://escholarship.org/uc/item/7vc7s7gj This master’s thesis examines working-class Black and Brown cultural politics in South LA, a historically Black neighborhood that has undergone significant transformations since the late 1980s, becoming an increasingly Latinx space. I ask: In what ways do aesthetic expressions emerging from South LA—particularly among Black and Brown working-class youth—respond to and resist systems of racial containment and urban transformation? To create an interdisciplinary foundation for this project, I draw on scholarship from cultural politics, relational race studies, and historical work on South LA. Through ethnographic observation, analyses of music and videos by Fuerza Regida and Buddy, and close readings of Born x Raised streetwear campaigns, I develop a critical account of Black and Brown cultural politics in South LA. I frame this account through what I call Hoodology, a relational theory of working-class aesthetics grounded in the lived experiences and cultural productions of Black... https://escholarship.org/uc/item/7vc7s7gj Thu, 26 Mar 2026 00:00:00 +0000 Cantero, Bryan Izac https://escholarship.org/uc/item/4sx7f3tq Adaptations to stress involve integrated systems and processes, including the functions of the sympathetic branch of the autonomic nervous system (SNS) to enable the organism to quickly learn about, fight, or flee the stressor. Sleep affects diverse processes, including learning about the nature of stressors and memory of those stressors so they may be successfully avoided or dealt with in the future. The sympathetic nervous system, particularly as controlled by the noradrenergic locus coeruleus, undergoes extensive changes across the sleep/wake cycle. REM sleep, in particular, is critical to the consolidation of associative memories such as the relationship of context to fearful stimuli. Existing studies of the relationship between sleep and stress have incompletely measured whether the sleep states and traits prior to or after stress exposure led to adaptive or maladaptive learning outcomes. The research and theoretical construct of this dissertation addresses whether the sympathetic... https://escholarship.org/uc/item/4sx7f3tq Thu, 26 Mar 2026 00:00:00 +0000 Cabrera, Yesenia https://escholarship.org/uc/item/4r90s0d6 This thesis examines the historical relationship between xiangsheng (cross-talk comedy) and the space of Tianqiao in Beijing from approximately 1900 to 1966. Rather than repeating the conventional understanding of xiangsheng as a linguistic or literary art form (or as pop culture), it argues that xiangsheng must be construed as an everyday practice produced through specific spatial formations. Using performers’ memoirs, oral histories, documents from the Beijing Municipal Archives, contemporary newspapers, and recollections from later periods, this thesis reconstructs the social ecology of Tianqiao on paper, thereby demonstrating how Tianqiao performers, in order to eke out a living through words, developed a set of techniques closely tied to the district’s distinctive spatial formation. The divergent trajectories of two amusement parks—the New World Amusement Park and the South City Amusement Park—opened in the greater Tianqiao area further illustrate the futile Republican-era... https://escholarship.org/uc/item/4r90s0d6 Thu, 26 Mar 2026 00:00:00 +0000 ZHUANG, YU https://escholarship.org/uc/item/3qh1c99h Speculative decoding has emerged as a promising approach to accelerate autoregressive generation by exploiting hardware concurrency, yet existing techniques are primarily designed for Transformer architectures and do not directly extend to state space models (SSMs) due to their latent Markov states and distinct computational structure. This thesis develops scalable speculative decoding algorithms for SSMs and hybrid architectures combining SSM and Transformer blocks. We introduce methods that enable efficient backtracking and verification in SSMs, as well as the first tree-based speculative decoding framework tailored to SSMs and hybrid models, leveraging structured state transitions to support parallel token generation with minimal overhead. Combined with hardware-aware implementations, these approaches achieve substantial inference speedups across multiple benchmarks and improve utilization under variable workloads. Together, these contributions establish speculative decoding... https://escholarship.org/uc/item/3qh1c99h Thu, 26 Mar 2026 00:00:00 +0000 Wu, Yangchao https://escholarship.org/uc/item/3gc4w40h This dissertation studies how firm and product-level distortions propagate through supply chains and shape aggregate outcomes, including welfare and total factor productivity. Chapter 1, co-authored with Luca Lorenzini, examines the aggregate welfare consequences of price discrimination in supply chains. We make progress on three fronts. First, using product-level firm-to-firm transaction data in which we observe prices and quantities for each product–buyer–seller triple, we document how pricing works in the population of firms: unit prices systematically decline with quantities and firms price differently across buyers. Second, we build a structural general-equilibrium model of supply chains in which firms both price discriminate and are price discriminated against, allowing us to compare pricing regimes and assess their aggregate welfare effects. Third, we bring the model to the data and find that price discrimination matters quantitatively through two forces: it improves... https://escholarship.org/uc/item/3gc4w40h Thu, 26 Mar 2026 00:00:00 +0000 Martner, Antonio https://escholarship.org/uc/item/3717w536 This dissertation is a synthesis of work completed during my Ph.D., related to aspects of Scattering Amplitudes and Topics in S-matrix Bootstrap. In Chapter 1, we follow the paper written in collaboration with Enrico Herrmann where we build the integrand for the two loop four particle form factor of the stress-tensor operator in maximally supersymmetric Yang-Mills theory. This was motivated by the surprising finding of where they found an antipodal duality between the six particle maximally helicity violating (MHV) on shell amplitude and the three particle MHV form factor of the chiral stress-tensor supermultiplet operator in planar N = 4 SYM. The antipode refers to a special operation that exchanges derivatives with discontinuities. A natural question to follow is whether such a duality can be extended to higher point form factors as well, and our work is a significant step in that direction. We employ a variant of generalized Unitarity known as Prescriptive Unitarity ... https://escholarship.org/uc/item/3717w536 Thu, 26 Mar 2026 00:00:00 +0000 Gopalka, Tushar https://escholarship.org/uc/item/2dj0p9fk This dissertation examines how meaning is produced in text-based concert works through the interaction of text, voice, and sonic medium. Rather than centering on genre or explicit thematic content, the study investigates how different modes of vocal delivery and mediation shape the listener’s perception of meaning across acoustic and electroacoustic contexts. By focusing on compositional strategies rather than ideological intent, the dissertation proposes a flexible framework for understanding how text functions within contemporary musical practice. Drawing on historical and theoretical perspectives, the study identifies four defining dimensions that recur across text-based works: (1) text as a semantic catalyst; (2) vocal mode and perceived authority; (3) medium as a temporal and experiential frame; and (4) the composer’s role as mediator through intimacy distance. Together, these dimensions offer an analytical lens through which diverse approaches to texted music can be examined... https://escholarship.org/uc/item/2dj0p9fk Thu, 26 Mar 2026 00:00:00 +0000 Li, Shirunyu https://escholarship.org/uc/item/275158qv This dissertation examines how distributed leadership within a Research Practice Partnership (RPP) can support organizational learning and equity-focused change in a community college context. Focusing on the Learning Together Initiative, a collaboration between Crescent Valley Community College (CVCC) and the University of California, Los Angeles (UCLA), the study investigates how faculty participation in shared inquiry interacts with institutional routines, governance structures, and leadership practices to shape whether learning becomes visible, sustained, and actionable at the organizational level. Particular attention is given to equity gaps affecting African American/Black and Latine students. Using a qualitative focus case study design, the research draws on participant observation, semi-structured interviews, and document analysis to examine three research questions: (1) how organizational learning becomes visible through inquiry-related routines and practices; (2)... https://escholarship.org/uc/item/275158qv Thu, 26 Mar 2026 00:00:00 +0000 Oliveira, Kristine https://escholarship.org/uc/item/1qb334fz This dissertation constructs a speculative ethnography of psychoanalysis as a field structured around secrecy, censorship, and the repression of its own racial and collective origins. Part One situates the discipline within its Jewish and diasporic roots, mapping its various historical entanglements with social and political upheavals from fin-de-siècle Vienna to its fragmentation and dissemination during World War II. Drawing on textual analysis, ethnography, and personal interlocutors, I examine how the discipline’s early focus on group and racial life became a “secretized secret,” structuring acceptable forms of knowledge and delineating the boundaries of the field.Part Two considers psychoanalysis during the Covid-19 pandemic, when analysts were forced to contend with the uncanniness of collective existence and the limits of individual-centered practice. Ethnographic analysis of the professional activities of psychoanalysts in virtuality, including reading groups, town halls,... https://escholarship.org/uc/item/1qb334fz Thu, 26 Mar 2026 00:00:00 +0000 Berwald, Marisa https://escholarship.org/uc/item/14w2197g This thesis examines how Indigenous Mixtec knowledge is sustained across the U.S.-Mexico border under conditions of displacement, colonialism, and limited access to culturally responsive healthcare. It addresses how migration and border regimes threaten continuity of traditional healing practices, language, and intergenerational knowledge. Using a qualitative, decolonial methodology grounded in pláticas and convivencia, this study draws on relational conversations with two Mixtec women to document storytelling, medicinal practices, and linguistic transmission as lived and embodied epistemologies. The findings demonstrate that these practices form transborder meshworks through which knowledge, language, and memory circulate across borders. Finally, the transborder meshwork not only sustains Indigenous epistemologies in diaspora but also operate as networks through which place-making unfolds across shifting geographies, producing Indigenous futurity. https://escholarship.org/uc/item/14w2197g Thu, 26 Mar 2026 00:00:00 +0000 Garcia, Reno C https://escholarship.org/uc/item/0cr8k528 Over the past two decades, clumped isotope geochemistry has become increasingly utilized as a method for reconstructing past environmental conditions. This proxy relies upon the bonding of heavy isotopes in carbonate minerals, and how bond ordering varies with temperature. The focus of this Ph.D. dissertation is split between methodological and applied research in reference to clumped isotopes. Best practices for clumped isotope standardization are developed in Chapter 1, then applied to investigate links between climate change and early human evolution in eastern Africa throughout Chapters 2 & 3. Chapter 1 evaluates a carbonate-based standardization protocol testing data comparability across multiple instrument configurations using multi-year datasets, with the three goals of refining previously published data from 2006 to the present, suggesting best practices, and improving interlaboratory comparisons. Results show that a specific series of different instrument components,... https://escholarship.org/uc/item/0cr8k528 Thu, 26 Mar 2026 00:00:00 +0000 Upadhyay, Deepshikha https://escholarship.org/uc/item/9v99m7t4 A central challenge of biochemistry is determining the consequences of modifications to proteinaceous amino acids as they pertain to protein function and broader cellular function. Mass spectrometry (MS)-based proteomics enables proteome-wide identification and quantification of modified peptides either through chemical modifications to amino acids such as covalent probe addition or even genetic modifications such as single amino acid variants (SAAVs). Chemical modifications are often assayed through chemoproteomic workflows in order to identify specific ligandable sites by covalent probes designed to be reactive towards certain amino acids, such as cysteine residues in the case of cysteine chemoproteomics. While chemoproteomic workflows are great tools to discover targetable sites by many different types of covalent probes, the scope for which the direct and indirect effects of liganding specific cysteines contribute to reported modes-of-action remains under-characterized. Knowledge... https://escholarship.org/uc/item/9v99m7t4 Wed, 25 Mar 2026 00:00:00 +0000 Shikwana, Flowreen https://escholarship.org/uc/item/9564v3k6 Andeans have thrived in the extreme conditions 50°F to -40°F during austral winter) of the Altiplano for the last 10,000 years. While human adaptations to high-altitude hypoxia have long been studied in this region, cold adaptation has not received similar interest. To systematically investigate Peruvian Andean adaptation to cold climate, we performed a cis-eQTL analysis on 58 participant-matched DNA and RNA pairs followed by selection analysis. Our findings revealed several pathways under enhanced gene expression amongst Peruvian An-deans related to cold-adaptation physiology including mitochondrial transcription, positive regulation of adipose tissue development, fatty acid homeostasis, energy homeostasis, and negative regulation of lipid catabolic process. This research quantifies the capacity for cold adaptation in a cold, high-altitude residing population, and explores the genetic underpinnings of cold adaptation through the identification of functional variants. https://escholarship.org/uc/item/9564v3k6 Wed, 25 Mar 2026 00:00:00 +0000 Young, Emma Anna https://escholarship.org/uc/item/8qj4x59t Energy storage materials remain an enormous subject of scientific and engineering endeavors. Among energy storage devices, Li-ion batteries are ubiquitous and both applied and fundamental efforts continue to go towards improving fast-charging capacities and understanding the mechanisms that govern kinetics. In this dissertation, I characterized the connection between battery (dis)charging kinetics and structural (de)lithiation mechanisms in mixed transition metal oxide insertion host materials. Through sol-gel methods, I synthesized tunnel structure oxides: the distorted rutile (Mo,W)O2 family as a model system for microstructural variation and tetragonal Nb0.5Mo0.5O2 as a fast-charging lithium-ion anode material. Through a combination of materials characterization (XRD, SEM-EDS, TEM), electrochemical testing (GCD, CV, GITT, galvanostatic entropic potential measurements), and synchrotron experiments (total scattering/PDF, operando XRD and XANES), I related dynamic host structures... https://escholarship.org/uc/item/8qj4x59t Wed, 25 Mar 2026 00:00:00 +0000 Pe, David https://escholarship.org/uc/item/7q11m29t Advanced functional devices increasingly rely on complex three-dimensional architectures to precisely control the transmission and transduction of mechanical, electrical, and acoustic energy. However, conventional fabrication techniques impose severe geometric constraints, limiting the achievable device performance and functionality. This dissertation explores how architected structures, enabled by advanced additive manufacturing, can be used to design and fabricate high-performance piezoelectric and multi-functional devices with tailored force and energy pathways.A customized projection stereolithography platform, integrated with an extrusion-assisted resin spreading mechanism, is developed to enable the fabrication of high-viscosity functional materials with complex geometries. Using this system, we address a fundamental challenge in additively manufacturing piezoelectric ceramics: the trade-off between printability and functional performance. A novel photosensitive resin formulation... https://escholarship.org/uc/item/7q11m29t Wed, 25 Mar 2026 00:00:00 +0000 Lu, Haotian https://escholarship.org/uc/item/5v41111k Hexapods are well suited to serve as platforms for future space exploration missions. However, due to the inherent complexity of multi-legged systems, simpler platforms which utilize hopping or wheeled robots are often preferred. While less complex, wheeled platforms lack the ability for precise manipulation of objects, and hopping systems are difficult to control with accuracy. Detailed exploration of small body objects in deep space requires precise locomotion, adaptability to variations in terrain, and the ability to manipulate objects of interest. Conventional platforms used for space exploration are limited in these capabilities. This thesis presents the development of TOCATL, a hexapod designed as an experimental platform to advance multi-legged systems while addressing concerns of complexity through robustness and serviceability. The robot was developed to utilize modern additive manufacturing techniques, user-focused design philosophy, and structurally robust components... https://escholarship.org/uc/item/5v41111k Wed, 25 Mar 2026 00:00:00 +0000 Parres, Federico Tonatiuh https://escholarship.org/uc/item/566947b7 In this dissertation, I present work completed during my PhD on ultrafast light-matter interactions in quantum materials. I begin with an introduction to ultrafast phenomena in cooperative systems, placing an emphasis on time-dependent Ginzburg-Landau (TDGL) theory. I then introduce the foundations of time-resolved second harmonic generation (tr-SHG), the technique that is used in all of the work presented here. In the first part of my results, I investigate a photoinduced phase transition in Ca3Ru2O7. By supplementing tr-SHG measurements with numerical simulations, I reveal underlying percolative and glassy phase transition kinetics. In the last chapter, I investigate a purely electronic polarization in Cr2O3 induced by sub-gap light in which the polar direction is controlled by the light polarization. https://escholarship.org/uc/item/566947b7 Wed, 25 Mar 2026 00:00:00 +0000 Carbin, James Tyler https://escholarship.org/uc/item/4q14k7xf High Bandwidth Memory (HBM) has become a critical technology for modern high-performance computing systems due to the rapidly increasing memory bandwidth demand in data-intensive workloads such as artificial intelligence and large-scale data processing. By vertically stacking multiple DRAM dies using through-silicon vias (TSVs), HBM significantly improves memory bandwidth and energy efficiency compared to conventional DRAM architectures. However, the increasing complexity of stacked memory structures introduces new challenges in early-stage design exploration, including accurate modeling of memory die organization, TSV allocation, thermal constraints, and power delivery.In this thesis, we propose a flexible modeling framework for architecture-level exploration of HBM-based memory systems. The proposed framework models key physical and architectural components of HBM, including memory die structure, peripheral circuits, base die logic, and TSV interconnects. In addition, the framework... https://escholarship.org/uc/item/4q14k7xf Wed, 25 Mar 2026 00:00:00 +0000 LEE, CHANHEE https://escholarship.org/uc/item/3zw1z52g Methanol synthesis from CO2 hydrogenation is a key catalytic route for sustainable fuel and chemical production. Industrial catalysts are typically based on Cu/ZnO/Al2O3, yet the structural role of Zn under reaction conditions is not yet fully understood. In particular, the dynamic interaction of Zn with Cu surfaces and reaction intermediates may strongly influence catalyst structure and function.In this work, we use theoretical calculations to investigate the structural evolution of Cu-Zn surfaces relevant to methanol synthesis, focusing on crystalline Cu(111) and stepped Cu(533) facets. We examine the stability and preferred location of Zn in the presence and absence of OH adsorbates, which are important surface intermediates under methanol synthesis conditions. Our results show that, in the absence of OH, Zn preferentially remains alloyed within the Cu surface or subsurface. In contrast, OH adsorption drives Zn segregation from the alloyed state to the surface, where Zn preferentially... https://escholarship.org/uc/item/3zw1z52g Wed, 25 Mar 2026 00:00:00 +0000 Issac Paul, George https://escholarship.org/uc/item/0qh1g663 Gas reforming is a vital process that converts naturally available gas resources into useful and high value materials. In an effort to minimize emissions associated with endothermic gas reforming processes, this dissertation presents the advancement of a solar-driven reforming method. Direct concentrated solar-thermal energy is leveraged to provide the energy necessary for three reforming processes: (1) methane pyrolysis for production of hydrogen and graphite, (2) dry reforming of biogas for production of syngas and graphite, and (3) ethane pyrolysis for synthesis of ethylene and graphite. A high flux solar simulator and reactor system at UCLA is used to perform parametric analyses of the respective reforming processes by varying a range of process parameters that includes feedstock flow rate, reaction pressure, incident solar flux, and feedstock composition. The dissertation also presents the development of a mid-infrared laser absorption spectroscopy sensing method that is... https://escholarship.org/uc/item/0qh1g663 Wed, 25 Mar 2026 00:00:00 +0000 Jeevaretanam, Barathan https://escholarship.org/uc/item/0m55p5tc Background: Although vaccinations have been proven of their effectiveness and safety, due to an increase in parental vaccine hesitancy, routine vaccine uptake among children and adolescents has started to decline in the United States. Implementing policies permitting self-consent to adolescents may be a potential way to combat declining vaccination rates among adolescents and provide adolescents more medical autonomy to make decisions regarding their physical and mental health. However, there is little known about the attitudes of adolescents and their parents towards adolescent self-consent policies in the U.S. This study investigated attitudes regarding adolescent self-consent among parents and their adolescents and characterized who would most likely support or not support such self-consent for routine vaccinations. Methods: We conducted a nationally representative non-probability cross-sectional survey among 764 parent-adolescent dyads in the United States between October... https://escholarship.org/uc/item/0m55p5tc Wed, 25 Mar 2026 00:00:00 +0000 Moore, Jade https://escholarship.org/uc/item/072909j7 Field-Programmable Gate Arrays (FPGAs) have become an essential computing substrate for domains requiring high performance and energy efficiency, such as machine learning, signal processing, and scientific computing. Their fine-grained parallelism and hardware configurability enable tailored accelerators that outperform conventional CPUs and GPUs under strict power budgets.High-Level Synthesis (HLS) has emerged as a key enabler for FPGA-based acceleration by allowing developers to describe hardware in high-level languages (e.g., C/C++ or domain-specific abstractions) rather than low-level register-transfer level (RTL) code. In principle, HLS improves programmer productivity, shortens development cycles, and makes FPGA design accessible to a broader community by providing a compiler-driven path from software-like descriptions to hardware implementations. FPGAs are particularly attractive targets for HLS because they offer fine-grained parallelism, deep pipelining, and reconfigurable... https://escholarship.org/uc/item/072909j7 Wed, 25 Mar 2026 00:00:00 +0000 Pouget, Stephane https://escholarship.org/uc/item/97b3n4mf Aging is a complex biological process marked by gradual physiological decline and increased vulnerability to disease. Metabolomics, which captures the dynamic output of cellular processes, offers a powerful lens for characterizing aging at the molecular level. This study leveraged untargeted metabolomic profiling across cerebrospinal fluid (CSF) and blood serum to investigate aging-related signatures using high-dimensional data from 407 individuals aged 18 to 64. By integrating data from three distinct platforms and targeting primary metabolites, biogenic amines, and lipids, I assessed metabolic changes in both central and peripheral compartments.To overcome the challenges posed by high dimensionality, noise, and missing data, I evaluated a comprehensive suite of machine learning methods, including penalized regression (LASSO, Ridge, Elastic Net), ensemble learning (Random Forest, XGBoost, LightGBM), kernel-based models (Support Vector Regression), and deep learning approaches... https://escholarship.org/uc/item/97b3n4mf Tue, 24 Mar 2026 00:00:00 +0000 Lee, Calvin https://escholarship.org/uc/item/8r65494d The rapid ascent of Large Language Models (LLMs) and Vision-Language Models (VLMs) has revolutionized semantic understanding, yet these systems remain “spectators”—observing the world through 2D projections without true physical grounding. This dissertation, Building World Models with Spatial Intelligence, addresses this critical gap by establishing a blueprint for AI systems that possess Spatial Intelligence: the ability to perceive, imagine, interact with, and reason about the 3D world. We posit that achieving this requires a symbiotic architecture that combines the vast semantic knowledge of 2D foundation models with the geometric precision of explicit 3D/4D representations, specifically Gaussian Splatting.The research is presented through four core contributions corresponding to the essential faculties of a World Model. First, we introduce Feature 3DGS, a framework for Perception that transforms 2D observations into a semantic, editable, and promotable 3D scene representation.... https://escholarship.org/uc/item/8r65494d Tue, 24 Mar 2026 00:00:00 +0000 Zhou, Shijie https://escholarship.org/uc/item/25r5w6tx The main aim of this dissertation is to expand the current knowledge on the condensed phase known as amphidynamic crystals. These special materials are solids that have been engineered to incorporate moving parts that can achieve molecular motion in the range of a liquid or a gas while retaining the high phase order characteristic of a crystal. The seminal work presented by my research group and others in the field is showcased and further expanded by the contributions presented in this thesis regarding the synthetic methodology and study of these materials, as well as collaborations to help characterize the dynamic processes displayed by them.Chapter one serves as an introduction to artificial molecular machines in the solid state. Key definitions and general concepts illustrate and provide context to support the main thesis of this work. What is a Machine? What are the current known Molecular Machines? How can we design and synthesize Crystalline Molecular Machines? Answers... https://escholarship.org/uc/item/25r5w6tx Tue, 24 Mar 2026 00:00:00 +0000 Chavez, Roberto https://escholarship.org/uc/item/9hx5p222 As robotic agents increasingly operate alongside humans in real-world domains, effective collaboration requires more than individual autonomy. While much prior work in human–robot interaction has focused on dyadic settings, real deployments commonly involve non-dyadic teams composed of multiple humans and autonomous agents operating under uncertainty, partial observability, and time pressure. In such teams, coordination failures often arise from misalignment in how teammates perceive the environment, reason about plans, communicate intent, and execute actions. In this dissertation, we study mixed human–autonomous collaboration in non-dyadic teams by examining coordination across sensing, decision-making, communication, and action. We introduce a unifying perspective that treats coordination as a team-wide process spanning the full decision loop rather than as an isolated capability. To support this perspective, we develop an agent architecture that enables autonomous teammates... https://escholarship.org/uc/item/9hx5p222 Mon, 23 Mar 2026 00:00:00 +0000 de Gortari Briseno, Julian https://escholarship.org/uc/item/96c3k591 Online experimentation, most commonly implemented as A/B testing, evaluates product changes by randomly assigning users to different versions of a system and comparing their performance on key business metrics. Many commonly used metrics are ratio metrics, such as click-through rate (CTR). To improve statistical sensitivity, variance reduction (VR) methods are widely adopted in practice. However, ratio metrics are nonlinear functions of unit-level outcomes and often exhibit substantial heterogeneity in unit-level contributions. These features limit the applicability and performance of classical variance reduction methods developed for mean outcomes. This thesis first provides a review of VR methods for ratio metrics and then proposes a stratification-based VR method designed for settings with heterogeneous unit-level contributions. Simulation results show that the proposed method achieves strong variance reduction while remaining unbiased. Overall, this work provides a clear... https://escholarship.org/uc/item/96c3k591 Mon, 23 Mar 2026 00:00:00 +0000 Li, Lingyi https://escholarship.org/uc/item/7dc421fx Beginning in the 1890s, with the exhaustion of “unoccupied” lands in the American West, the closing of the frontier became a prevailing framework for reconsidering the mission of American land-grant universities. Without free land to sustain the Jeffersonian ideal of a democratic republic, the vision of individuals securing property, exercising exclusive rights, cultivating moral character, and contributing to the wealth of the nation appeared increasingly baseless. In response, the nation’s political imagination were taken up by a professional class of agricultural scientists, land economists, home economists, and urban planners. They sought new ways to scrutinize, manage, and redistribute property. Their effort to reconfigure the imbrication of subjecthood, wealth, and ownership did not simply extend the scientific and industrial logics that had shaped nineteenth-century development. Rather than endorsing the unbounded expansion of mechanized production, they questioned its... https://escholarship.org/uc/item/7dc421fx Mon, 23 Mar 2026 00:00:00 +0000 Hou, Chi-Chia https://escholarship.org/uc/item/67x6v3qd This thesis leverages the transparent, on-chain architecture of Polymarket to empirically study algorithmic arbitrage and insider trading within NBA prediction markets. Analysis of high-frequency limit order book snapshots reveals extreme microstructural efficiency; single-market mispricings resolve in a median of 3.614 seconds, while combinatorial arbitrage is economically bounded by shallow liquidity. To detect insider trading without regulatory labels, an unsupervised Isolation Forest model is trained on pre-resolution behavioral features and calibrated against a quantitative Pseudo-Ground Truth (PGT) Oracle. The model’s top 1.0% anomaly cohort captured a statistically significant 11.7% of aggregate market profits. These findings demonstrate that while structural inefficiencies on Polymarket are fleeting, distinct on-chain behavioral signatures effectively isolate insider trading.  https://escholarship.org/uc/item/67x6v3qd Mon, 23 Mar 2026 00:00:00 +0000 Yang, Jiaxin https://escholarship.org/uc/item/6514d7bj Move towards electrification creates massive strain on the existing electric grid. Implementing sustainable sources of energy like wind, solar, hydrogen, and batteries can provide sufficient power, but associated capital costs are too great for widescale adoption. Therefore, it is imperative that new power supplies integrate to existing infrastructure to minimize initial capital investments and generate useful electricity as a product.Microbial fuel cells (MFCs) are a form of bioelectrochemical system that fits this profile due to the conversion of organic waste streams to electrical energy using electroactive bacteria biocatalysts. Despites its conversion capabilities, MFCs face critical barriers in commercialization: material longevity, limited power output, limited substrate conversion. Therefore, the research mission addressed herein is to develop a scalable, practical, affordable method of waste conversion to useful byproducts using yeast species Saccharomyces Cerevisiae... https://escholarship.org/uc/item/6514d7bj Mon, 23 Mar 2026 00:00:00 +0000 Lopez, Fernando Andres https://escholarship.org/uc/item/63w095dm Plasma-based acceleration (PBA) refers to a class of advanced accelerator concepts in which the electromagnetic fields sustained in a plasma wave are used to accelerate charged particle beams. The strength of these fields can be orders of magnitude higher than those achievable in conventional radio-frequency accelerators. Thus, PBA offers the prospect of dramatically reducing the accelerator size and cost for a given beam energy. This makes PBA attractive for a variety of accelerator-based applications including high-energy collider physics, microscopy using free electron lasers, radiotherapy for cancer treatment, and ion implantation in semiconductors. Laser wakefield acceleration (LWFA), in which an intense laser pulse drives the plasma wave, is one of two concepts of interest for PBA. In this dissertation, new results on LWFA and new capabilities for its simulation are presented through a combination of theory and particle-in-cell computer simulations.In LWFA, the acceleration... https://escholarship.org/uc/item/63w095dm Mon, 23 Mar 2026 00:00:00 +0000 Pierce, Jacob https://escholarship.org/uc/item/5v84d00g This thesis examines the 1948 Costa Rican Civil War in an effort to challenge the dominant narrative of Costa Rican exceptionalism. Drawing on archival research, oral histories, and family testimonies, it argues that Costa Rica’s “Second Republic” founded by José Figueres Ferrer was built upon selective remembering, historical erasure, and unacknowledged U.S. intervention. The analysis traces the rise of the Communist Party and its unique “comunismo a la tica,” which, through an unlikely alliance with the catholic church and President Calderón Guardia, enacted sweeping social reforms in the 1940s. However, this coalition was dismantled by the rising tide of anti-communism and red-baiting propaganda that framed legitimate domestic politics as a foreign threat. After the annulment of the 1948 election, Figueres launched an armed insurrection where evidence reveals that U.S. diplomatic pressure, selective arms embargoes against the government, and tolerance of rebel supply... https://escholarship.org/uc/item/5v84d00g Mon, 23 Mar 2026 00:00:00 +0000 Sotillo, Luis Antonio https://escholarship.org/uc/item/5dh012x3 Recent advancements in image-based Bird's Eye View (BEV) and 3D occupancy perception have significantly improved the ability of autonomous vehicles to understand their surrounding environments from camera inputs alone. By projecting multi-view camera features into a unified representation, these methods have achieved strong performance on core perception tasks such as 3D object detection, semantic segmentation, and occupancy prediction. Despite this progress, current methods still face fundamental limitations in the effectiveness and efficiency perspective: the learned feature representations in BEV models remain underexplored, and temporal information is insufficiently and inefficiently exploited for volumetric scene understanding. This thesis focuses on representation learning for image-based autonomous driving perception, addressing these challenges through two complementary contributions.The first part of this thesis proposes BEVCon, a contrastive learning framework designed... https://escholarship.org/uc/item/5dh012x3 Mon, 23 Mar 2026 00:00:00 +0000 Leng, Ziyang https://escholarship.org/uc/item/4273r613 Retrieval-augmented image generation is designed to improve text-to-image generation for rare, previously unseen, or highly specific visual concepts by retrieving external reference images at inference time. In these systems, the retrieved images are not used only as background information for a user or a reasoning module. Instead, they are passed directly into the image generation model through image-prompt mechanisms such as IP-Adapter, which converts a reference image into visual features that guide the final output. This design improves generation quality, but it also creates a new security risk: a malicious image placed in the retrieval database may influence both which image is selected and what the model ultimately generates.This thesis studies whether a single poisoned image can attack both stages of such a pipeline. We propose a joint attack framework that optimizes one imperceptible perturbation for two objectives. First, the perturbation increases the chance that the... https://escholarship.org/uc/item/4273r613 Mon, 23 Mar 2026 00:00:00 +0000 Yu, Pengyue https://escholarship.org/uc/item/3qw2743c As cellular networks continue to evolve toward the sixth-generation (6G) of wireless, joint communication and sensing (JCAS) has emerged as a promising research direction that aims to equip these communication networks with high-resolution sensing capabilities. Opportunities for JCAS are particularly ripe in systems operating at millimeter-wave (mmWave) frequencies, as they can offer both high range and angular resolution, courtesy of wide bandwidths and many antennas. Recent research aims to realize JCAS on such systems through a variety of innovative beamforming strategies, spanning compressive sensing, clutter rejection, interference cancellation, and others. Due to hardware imperfections, however, implementing these beamforming techniques on actual mmWave transceivers with high precision can be considerably difficult, but this has largely been overlooked in the majority of prior work on JCAS. In light of this, the objectives of this thesis are twofold. The first aim is to... https://escholarship.org/uc/item/3qw2743c Mon, 23 Mar 2026 00:00:00 +0000 Olson, Dominic Kleinschmidt https://escholarship.org/uc/item/2gs892sb Subscriber Identity Module (SIM), including eSIM (embedded SIM), is ubiquitous as an essential part of widely-deployed 5G connected devices. The SIM possesses rich capabilities beyond its conventional use, including autonomous on-card processing, secure storage, and a standardized interface for device control and information retrieval. Despite the potential of SIM to uniquely benefit the device and user applications, its usage today are still largely confined to the traditional network authentication and limited application-specific or operator-centric functions. We identify three roadblocks hindering the development of practical SIM-based mini systems, including (1) interaction with users and applications, (2) limitations of SIM hardware and interface, and (3) the ability of verification on commercial SIM and network. This dissertation introduces SIM-Based Mini Systems, a systematic approach to building practical SIM-based systems for a wide range of user applications.... https://escholarship.org/uc/item/2gs892sb Mon, 23 Mar 2026 00:00:00 +0000 Ding, Boyan https://escholarship.org/uc/item/2f7898np This study compares machine learning approaches for detecting cheating in online interviews from a production dataset using anonymized behavioral features and social network data from ∼272,000 candidates. The dataset presents severe class imbalance, a large volume of unlabeled observations with weak labels, and a sparse social graph with over 1.7 million edges. We engineer 36 predictive features – including missingness indicators and graph- derived metrics – and evaluate three approaches: an XGBoost baseline, a semi-supervised XGBoost extension with differentiated sample weighting, and a GraphSAGE neural network. Models are evaluated under a cost-based metric with asymmetric penalties, where missing a cheater ($600) is twice as costly as incorrectly blocking a legitimate candidate ($300). The XGBoost model achieved the best cost score, outperforming both the semi-supervised model and GraphSAGE. Threshold analysis reveals auto-blocking is only cost-effective above 96.77% confidence.... https://escholarship.org/uc/item/2f7898np Mon, 23 Mar 2026 00:00:00 +0000 Mahalley, Anshuman https://escholarship.org/uc/item/22z722q5 Causal discovery seeks to infer the underlying causal relationships among a set of variables from observational data, typically represented through a directed acyclic graph. The assumption of independence between observations (units) in a dataset is prevalent across various methodologies for learning causal graphical models. However, this assumption often finds itself in conflict with real-world data, posing challenges to accurate structure learning. First, we propose a de-correlation-based approach for causal graph learning on dependent binary data, where the local conditional distribution is defined by a latent utility model with dependent errors across units. We develop a pairwise maximum likelihood method to estimate the covariance matrix for the dependence among the units. Then, leveraging the estimated covariance matrix, we develop an EM-like iterative algorithm to generate and de-correlate samples of the latent utility variables, which serve as de-correlated data. Any standard... https://escholarship.org/uc/item/22z722q5 Mon, 23 Mar 2026 00:00:00 +0000 Chen, Alex https://escholarship.org/uc/item/19f3f02w This dissertation examines how sample-based virtual instruments (commonly referred to as sample libraries) reshape contemporary composition pedagogy and musical agency. As composition increasingly unfolds within digital audio workstations, software functions simultaneously as instrument, studio, and interface, altering how composers encounter sound, labor, and orchestration. Situating sample libraries within the histories of digital sampling and media-industry restructuring, the study argues that these tools transform recorded performance into modular, commodified assets that mediate many composers’ first sustained encounters with orchestral sound. To clarify their aesthetic and structural differences, the dissertation develops a dual-axis taxonomy that maps libraries according to production logic and correlates it with the aesthetic practices of the 20th and 21st centuries.The project also identifies two central tensions in sample-library-mediated composition: reification, in... https://escholarship.org/uc/item/19f3f02w Mon, 23 Mar 2026 00:00:00 +0000 Duran Zarate, Carlos Alberto https://escholarship.org/uc/item/105050xf This dissertation develops novel methodology for transfer learning under the Bayesian statistical framework. We approach transfer learning from two different angles: by training on existing interpretable statistical models with the original data restructured to make training feasible, and by training on synthetic data generated by an existing model to learn the posterior distribution function. Beginning with the first approach, we take multiple solutions generated from computer models of physical or mechanistic systems and compile them as data to train our statistical model. If individual solutions of the data consist of a large number of points, it is segmented into smaller sets of points to make it feasible. The trained model may then be used to seek optimal values of unknown parameters from observational field data under an inverse problem framework. In short, this setup trains on segmented data and is then applied to larger non-segmented data to acquire parameter estimates.... https://escholarship.org/uc/item/105050xf Mon, 23 Mar 2026 00:00:00 +0000 Zhou, Daniel F. https://escholarship.org/uc/item/777180bq Perovskite solar cells (PSCs) have emerged as a promising photovoltaic technology due to their high power conversion efficiency and compatibility with solution-based processing. Among scalable deposition techniques, blade coating offers significant advantages in material utilization and industrial adaptability. However, the blade-coating process involves multiple interdependent parameters, and precise control of film crystallization under ambient conditions remains challenging, which hinders its transition from laboratory-scale fabrication to industrial production.In this study, a systematic optimization strategy for blade-coated perovskite solar cells was developed by integrating data-driven modelling, solvent engineering, and interfacial passivation. A novel Complex System Response (CSR) function was introduced to quantitatively correlate blade gap and coating speed with device efficiency. A second-order nonlinear response surface was constructed using experimental data, enabling... https://escholarship.org/uc/item/777180bq Sun, 22 Mar 2026 00:00:00 +0000 Tong, Yiu Shun https://escholarship.org/uc/item/85b1t1xw The study of magnetic phenomena at the nanoscale requires modeling frameworks that bridge the gap between computationally expensive quantum mechanical treatments and spatially averaged continuum micromagnetics. This dissertation presents the development of a fully coupled, atomistic magnetoelastic energy method implemented within a hybrid Molecular Dynamics–Atomic Spin Dynamics (MD–ASD) framework. By treating individual atoms as classical particles and magnetic moments as classical spin vectors subject to quantum-informed energetics, the model enables the direct coupling of atomic displacements and spin evolution. The framework is implemented as a custom pair potential in the LAMMPS software package, incorporating exchange, magnetocrystalline anisotropy, dipole–dipole interactions, and a novel atomistic formulation of cubic magnetoelastic energy. The model is validated against established micromagnetic solvers for BCC iron, demonstrating its capability to capture both linear and... https://escholarship.org/uc/item/85b1t1xw Sat, 21 Mar 2026 00:00:00 +0000 McIntosh, Matthew https://escholarship.org/uc/item/44s6r728 The ability to repair reinforced concrete walls with modest damage following earthquake shaking is important because walls provide substantial lateral load strength and stiffness and because damage is likely to be concentrated at a limited number of locations. Accordingly, guidance supported by experimental evidence is required to enable practicing engineers to select optimal repair strategies. Relatively few experimental studies have been performed to address this issue; therefore, an experimental study was conducted to investigate the post-repair behavior of approximately one-third scale slender walls with rectangular and C-shaped cross sections. The study focused particularly on walls incorporating lap splices at the wall–foundation interface, non-weldable longitudinal reinforcement, large shear span ratios, and either special or ordinary boundary detailing. During the initial testing phase, Performance-Critical Damage, as defined by FEMA P-2335, including concrete core crushing,... https://escholarship.org/uc/item/44s6r728 Sat, 21 Mar 2026 00:00:00 +0000 Rodriguez Sanchez, Santiago https://escholarship.org/uc/item/0164q1x6 Light scattering by nanoparticles plays critical role in a wide range of technologies and applications. In the food and pharmaceutical industries, it enables accurate optical characterization of nanoemulsions and colloidal suspensions. Light transfer is also important for design of solar absorbers and color filters where metallic nanoparticle embedded matrices are engineered to enhance solar absorption or filter colors. Light transfer also plays a key role for design of aerogels for transparent insulation of commercial building windows. Typically, light scattering by nanoparticles is handled by using the independent scattering approximation which assumes that the effective scattering properties of a suspension of particles can be obtained by the superposition of each individual particle's contribution. However, when the concentration of particles increases, their interparticle spacing becomes small and the scattered wave spherical wave of one particle may interact with the scattered... https://escholarship.org/uc/item/0164q1x6 Sat, 21 Mar 2026 00:00:00 +0000 Martinez, Ricardo https://escholarship.org/uc/item/9t88s2z1 Diabetes treatment has been revolutionized by the introduction of the new diabetes drug classes, glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium glucose transporter-2 inhibitors (SGLT2i). These drugs are the first to demonstrate improved cardiovascular and kidney disease outcomes in clinical trials while also reducing blood glucose and weight. However, uptake of the drugs in clinical practice has been slow, especially for individuals at higher risk of cardiovascular and renal complications. Also, ethnic and racial minority patients have been found to receive the drugs at lower rates than White patients in the early period after FDA approval of these drugs. This dissertation investigates the factors influencing the prescribing of GLP-1RA and SGLT2i medications in type 2 diabetes, with a focus on addressing disparities in their adoption. The study uses electronic medical record data from a large academic health system to analyze trends in prescribing from 2016 to... https://escholarship.org/uc/item/9t88s2z1 Fri, 20 Mar 2026 00:00:00 +0000 Torres, Hugo https://escholarship.org/uc/item/8km8s0r6 Adolescence is a developmental period in which peer relationships play a critical role in emotional well-being, identity formation, and social development. This dissertation examines how agency in shared activities (ASP) contributes to adolescents’ peer relationship quality (PRQ), and how access to flexible low barrier community environments (ATP) can facilitate ASP.Drawing on theories from developmental psychology, play research, and the learning sciences, the dissertation introduces Agentic Social Play (ASP); shared, peer-directed activities in which adolescents shape the flow, tone, and purpose of their interactions. ASP emphasizes voluntary participation, flexibility, and intrinsic motivation, conditions that facilitate authenticity, emotional responsiveness, and sustained peer engagement. The dissertation also introduces Adolescents’ Third Places (ATP), defined as flexible, low-barrier community environments that adolescents can access independently and that plausibly support... https://escholarship.org/uc/item/8km8s0r6 Fri, 20 Mar 2026 00:00:00 +0000 Bigsby, Menissah https://escholarship.org/uc/item/8825v8ks Formins are a class of actin nucleators that build unique cytoskeletal structures necessary for different cellular functions. Mammals express fifteen different formins divided into seven families. The C-terminal half of formins contain the formin homology 1 (FH1), FH2, and tail domains. The FH2 domain dimerizes to bind and processively travel with the barbed-end of actin filaments during elongation. The FH1 domain is intrinsically disordered and contains proline-rich motifs (PRMs) to bind profilin-actin monomers to add to the barbed-end where the FH2 domain is. Some formin families have been predicted to have a coiled-coil domain N-terminal to the FH1, suggesting that the FH1 could dimerize at its N-terminal end. This can have alternate effects on the FH1: 1) it can extend the FH1 to free any PRMs previously occluded due it its intrinsic nature, and 2) any PRMs that are close to the dimerization point—where the coiled-coil domain ends—can become occluded due the ends coming into... https://escholarship.org/uc/item/8825v8ks Fri, 20 Mar 2026 00:00:00 +0000 Christian, Bryan Andrew https://escholarship.org/uc/item/842447xx Foundation models have transformed artificial intelligence, yet they still falter on reasoning tasks that demand multi-step inference, temporal understanding, and real-world commonsense, capabilities essential for truly intelligent systems. This thesis diagnoses critical multimodal reasoning failures and presents a unifying solution: principled synthetic data supervision. We address three frontier challenges: (1) mathematical reasoning over visual contexts, where careful multi-stage data curation achieves state-of-the-art performance across model sizes; (2) semantic alignment in video-language models, where LLM-generated contrastive captions unlock stronger temporal and compositional reasoning; and (3) physical commonsense reasoning, where we benchmark and substantially advance video models' understanding of real-world plausibility. Collectively, this work establishes that data quality, not merely scale, is a primary driver of reasoning capability, charting a path toward breaking... https://escholarship.org/uc/item/842447xx Fri, 20 Mar 2026 00:00:00 +0000 Bansal, Hritik https://escholarship.org/uc/item/6gb7t7r3 This dissertation proposes a novel view of phases titled Read-Only, which is necessitated due to the possibility of certain cross-phasal syntactic dependencies in Hindi-Urdu, as well as the impossibility of other such dependencies. I observe that in Hindi-Urdu, phases are opaque to dependencies—like case assignment and nominal licensing—which require a spelled-out goal to be modified. On the other hand, phases are transparent to phi-agreement, wh-licensing, movement, and dependent case competition, where the goal is not ultimately altered in the process. While traditional views of phases either rule out all cross-phasal dependencies (Chomsky 2000, 2001) or permit all of them (Fox and Pesetsky 2005), Read-Only offers a nuanced perspective on these dependencies based on how a particular dependency affects the features (and relative order) of the goal in a phasal spell-out domain. This theory that bases the viability of a cross-phasal dependency on if it changes the goal derives... https://escholarship.org/uc/item/6gb7t7r3 Fri, 20 Mar 2026 00:00:00 +0000 Agarwal, Hashmita https://escholarship.org/uc/item/5sh3w0xg Peptide-peptoid copolymer hybrids are an emerging class of biomaterials that combine polypeptide and polypeptoid features. Polypeptides are commonly synthesized by ring-opening polymerization of amino acid N-carboxyanhydride (NCA) monomers, and polypeptoids can be prepared in a similar manner using N-substituted N-carboxyanhydride (NNCA) monomers. Homopolymerizations of these monomers are well understood, but the study of their statistical copolymerization has only recently been investigated. A quantitative method to analyze kinetics as well as initiators that can alter comonomer reactivities are both needed to control synthesis and properties of these materials. Controlled statistical copolymerization of NCA and NNCA monomers would enable the synthesis of peptide-peptoid copolymers with well-defined compositions and comonomer sequence distributions. Controlled sequence distributions of these copolymers will enable tunable properties not currently accessible in diblock copolymers... https://escholarship.org/uc/item/5sh3w0xg Fri, 20 Mar 2026 00:00:00 +0000 Tan, Aryan Louise Anabo https://escholarship.org/uc/item/3885g5qz The ever-growing data and model scale have created a tension between efficiency and effectiveness. Model compression techniques such as pruning, distillation and quantization can significantly improve inference efficiency at the cost of downstream task performance. To go beyond this trade‑off, this thesis investigates lightweight models not merely as compressed versions of large models but as more diverse roles that accelerate both ML and non‑ML applications while preserving or even improving effectiveness. We explore three roles for lightweight models. (i) Lightweight drafters for large‑language-model inference: we design novel decoding algorithms that improve both inference speed and downstream task accuracy via using a small model to generate draft tokens. (ii) Lightweight pruners for large-scale search tasks: for HLS design automation and graph similarity search, we train lightweight models to efficiently and effectively prune unpromising candidates to facilitate downstram... https://escholarship.org/uc/item/3885g5qz Fri, 20 Mar 2026 00:00:00 +0000 Qin, Zongyue https://escholarship.org/uc/item/17h0s5s1 California has experienced increasingly frequent and severe wildfires in recent decades, of- ten attributed to a combination of climate change and land management practices. Public discussions sometimes claim that counties with stricter vegetation or “brush” policies experience lower wildfire risk, yet these claims are rarely evaluated using formal spatial–temporal statistical models.This thesis examines the relationship between wildfire occurrence in California and county- level brush policies using a Stoyan–Grabarnik (SG) objective framework for spatial–temporal point processes. The analysis combines wildfire ignition records from the U.S. Forest Service with daily temperature data from Google Earth Engine, precipitation observations from NOAA stations, and county-level brush policy indicators collected from California county fire agency sources. After cleaning and merging the datasets, the modeling sample contains 35,500 wildfire ignition records between 1987 and 2021, along... https://escholarship.org/uc/item/17h0s5s1 Fri, 20 Mar 2026 00:00:00 +0000 Liang, Jiayi https://escholarship.org/uc/item/0fb4d1rh Advances in physics-based simulation and data-driven generative modeling have significantly improved our ability to construct digital representations of the physical world. High-fidelity numerical solvers grounded in partial differential equations (PDEs) provide principled and interpretable models of physical phenomena, while modern diffusion-based generative models enable scalable and expressive synthesis of shape and motion. Despite their complementary strengths, these two paradigms have largely evolved in isolation. Simulation emphasizes physical correctness but often lacks scalability, whereas generative models excel at visual realism yet frequently neglect physical validity. As a result, current digital world models risk achieving improved visual appearance without the functional reliability required for downstream applications, such as robotics and embodied AI, where accurate physical reasoning is essential. This dissertation argues that physically grounded world modeling... https://escholarship.org/uc/item/0fb4d1rh Fri, 20 Mar 2026 00:00:00 +0000 Chen, Yunuo https://escholarship.org/uc/item/0594q70q Understanding the dynamics of energetic electron fluxes in Earth’s radiation belts remains one of the key challenges in Heliophysics. The two most studied mechanisms contributing to these dynamics are (1) wave–particle resonant interactions, which can accelerate and pitch-angle scatter electrons, and (2) radial diffusion driven by ultra-low-frequency (ULF) waves. Yet, observations often reveal behaviors that cannot be fully explained by these two processes. In particular, they necessitate considering radial transport mechanisms that go beyond classical diffusion. Radial transport can arise even in the absence of waves, solely due to the topology of magnetic field lines. This mechanism is known as Drift-Orbit Bifurcation (DOB), which occurs on the dayside, where solar wind compression splits the equatorial magnetic field minimum into two off-equatorial minima, violating the second adiabatic invariant and enabling radial transport. This mechanism has been investigated for magnetic... https://escholarship.org/uc/item/0594q70q Fri, 20 Mar 2026 00:00:00 +0000 Kamaletdinov, Sergei https://escholarship.org/uc/item/9jn8x24g Variation is a necessary component of evolution. Without phenotypic variation, natural selection has nothing to select from, and evolution slows. It is thus a fundamental goal of evolutionary biology to describe and understand the generation of the variability that selection requires. The generation of variation, or how a genotype is transcribed and translated to form differing phenotypes, is essentially the process of development. Investigating how development shapes the available variation for natural selection to act upon is therefore crucial to our understanding of the evolution of life.The system I leverage to investigate the generation of variation by development and its impact on evolution in this dissertation is the mammalian limb. The limb is an ideal system for this because it is readily investigated at multiple biological scales. Across mammals, the patterning of the limb is largely invariant; there is a single proximal element (stylopod), two medial elements (zeugopod),... https://escholarship.org/uc/item/9jn8x24g Thu, 19 Mar 2026 00:00:00 +0000 Howenstine, Aidan Oliver https://escholarship.org/uc/item/7nz1j4s2 Restoring and enhancing images is a central part of vision, both as a foundation upon which robust perception and understanding is built and as a tool for aesthetic fruition. Unfortunately, vision, especially at the pixel level, can become exceedingly difficult under harsh, adverse conditions. This thesis addresses these challenging conditions in two low-level vision tasks: weather removal and face restoration. For weather removal, while a majority of previous methods focused on synthetic weather patterns, we focus on the more complex task of removing real-world weather. These can manifest in a multitude of different ways depending on camera intrinsics, atmospheric pressure, or even geographic location. We overcome this challenge for rain removal by introducing time-multiplexed rain/clear image pairs and collecting a dataset capable of training a model that is able to bridge the sim2real performance gap. We then expand this to multiple weather conditions by introducing a semi-automatic... https://escholarship.org/uc/item/7nz1j4s2 Thu, 19 Mar 2026 00:00:00 +0000 Zhang, Howard https://escholarship.org/uc/item/6x47f75p The agentic paradigm offers a promising route to intelligent and adaptive wireless systems. This dissertation shows how agentic approaches can be made feasible in 5G. We make a case for infrastructure-level agents by developing FIRM, which senses the wireless channel and enables adaptive interference mitigation through standardized 5G mechanisms. We further develop DeepSpecs as a grounded, traceable human-machine interface that helps agents follow standards. At the application layer, we develop IoTGen and study IoT application generation as a tractable case for automating device-cloud interaction under wireless constraints. Overall, the dissertation demonstrates how agentic concepts can be realized across key layers of wireless systems. https://escholarship.org/uc/item/6x47f75p Thu, 19 Mar 2026 00:00:00 +0000 Xu, Yifei https://escholarship.org/uc/item/67k2k36h Sleep is important for a wide range of physiological processes and sleep disruption leads to impaired mood, poor cognition, and a host of pathological conditions ranging from cardiovascular disease to mental and neurological disorders. Sleep has been viewed as a homogeneous brain state, but animal research suggests different brain regions display distinct sleep states simultaneously. Prior to this dissertation, the occurrence of regional sleep across the night in human recordings has never been investigated. Studies that follow standard methods of sleep state determination are likely to miss hidden sleep stages with important implications for health and disease. I used scalp electroencephalography (EEG) and intracranial recordings (iEEG) from human subjects undergoing implantation of depth electrodes to score sleep independently in the posterior hippocampus and neocortex. I found strong evidence of regional sleep in the hippocampus and neocortex throughout the night. The hippocampus... https://escholarship.org/uc/item/67k2k36h Thu, 19 Mar 2026 00:00:00 +0000 Jang, Rockelle https://escholarship.org/uc/item/5d84714h Recruitment for community-based public health research often raises challenges related to organizational engagement and geographic disparities, particularly in rural and underrepresented minority populations. Ensuring that such groups are effectively recruited and engaged was one of the key goals of this study, as diverse and representative samples are essential for valid public health research. This study evaluates recruitment patterns and predictors across a multi-county region of Central California, where outreach to various community organizations was conducted to support a population-based study of neurological health, specifically Parkinson’s disease (PD) and related conditions, in older minority individuals with an emphasis on recruiting Latinos. Here, we describe data we collected on recruitment efforts for organizations and different means of recruitment in the three Central California counties targeted by this research study. Each organization was categorized by type,... https://escholarship.org/uc/item/5d84714h Thu, 19 Mar 2026 00:00:00 +0000 Tran, Lauren https://escholarship.org/uc/item/5485g8vd This dissertation explores the role of automobiles, airplanes, and motorcycles in a selection of Mexican literary works published from the second half of the 20th century to the present. This work demonstrates that motorized vehicles in a sample of novels, short stories, and chronicles function as means of organizing emotions and memory, of expressing their characters' identities, and of translating their presence into agency to navigate difficult or unforeseen situations. This work proves how motorized vehicles are central to the configuration of these texts and demonstrates that their presence, which transcends the anecdotal, the ornamental, or the accessory, is essential as a catalyst and organizer of literary texts.One core element of the theoretical analysis comes from Ottmar Ette, who states that one of the most fascinating aspects of travel literature lies in its omnipresent movements of understanding, which can be understood as movements of spatial comprehension. Ette... https://escholarship.org/uc/item/5485g8vd Thu, 19 Mar 2026 00:00:00 +0000 Martinez-Moron, Nylsa https://escholarship.org/uc/item/4w70957q Within the development of perovskite solar technologies, the development of passivation materials for defect and interfacial engineering has been crucial for the prevention of energy losses and improving device efficiency. This work reported within this study describes the preliminary development of a new first-in-group class of intrinsically conductive interfacial materials. While the preliminary results of the first of these radical passivators were not promising, due to steric hindrance preventing interaction between the perovskite and the passivator, attempts were made to synthesize a new derivative designed to overcome this issue.In addition to the synthesis of the radical passivators, a new methodology was developed to synthesize aryl tert-butyl nitroxyl radicals from aryl bromides in a three-step one-pot reaction. This methodology, after optimization, showed replicable near-quantitative yields of over 90%. To date, it is one of the only high-yielding one-pot methodologies... https://escholarship.org/uc/item/4w70957q Thu, 19 Mar 2026 00:00:00 +0000 Kundu, Arnesh https://escholarship.org/uc/item/30s726hm Modern machine learning systems rely on heterogeneous multimodal data and large-scale foundation models with billions of parameters. While such scale enables remarkable performance, it also introduces fundamental inefficiencies in how information is represented, shared, and stored. This dissertation studies information-efficient representations from two complementary perspectives: redundancy in multimodal data and redundancy in over-parameterized models. The first part develops an information-theoretic framework for understanding the minimal complexity of shared structure in multimodal data. Through analytical and empirical studies of distributed detection, feature compression, and factorized representation learning, we demonstrate that multimodal observations admit substantial representational redundancy due to their inherent dependencies. These findings motivate a fundamental characterization of shared information among high-dimensional continuous sources. We introduce a new... https://escholarship.org/uc/item/30s726hm Thu, 19 Mar 2026 00:00:00 +0000 Li, Xinlin https://escholarship.org/uc/item/85p7h9rs This project argues that eighteenth-century authors used the language of the vermicular imaginary to represent the boundaries between human bodies and their nonhuman environment, using worms as a fleshly metonym for atoms or other invisible minutiae. Each chapter of the dissertation is a case study which examines the textual discourse generated around a specific worm in the years following the evolution of the microscope. Because those chapters take a particular worm species or figuration as their organizing principle, they collage genres, authors, and chronologies, assembling a bricolage of texts documenting cultural representations of creatures that still to this day resist easy definition or Linnean taxonomizing. From the chronically worm-infested bodies I present in Chapter One to the unusually-minded readers and thinkers examined in Chapter Three, my project centers bodies and minds which, through encounters with the nonhuman, reconsider the boundaries of disability and able-bodiedness.In... https://escholarship.org/uc/item/85p7h9rs Wed, 18 Mar 2026 00:00:00 +0000 Happe, Marguerite https://escholarship.org/uc/item/70c6j40s This dissertation develops statistical methods for estimating the reproduction rate and for forecasting infectious disease. We present: (1) direct, stable estimators for the productivity in Hawkes processes, with a comparison of their relative performance; (2) an application to COVID-19 case data demonstrating the utility of the estimated reproduction rate, which corresponds to the Hawkes productivity, as an early warning signal for surges; and (3) a framework for sharing information across outbreaks by fitting each wave separately with simple curves, borrowing strength from prior outbreaks to stabilize estimation and improve forecasts. https://escholarship.org/uc/item/70c6j40s Wed, 18 Mar 2026 00:00:00 +0000 Phillips, Sophie https://escholarship.org/uc/item/3398t17x The development of Large Language Models (LLMs) has advanced significantly, with pre-training on extensive text corpora and subsequent post-training processes such as Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) enhancing their alignment with human values and tasks. Despite these strides, the reliance on human-annotated datasets for post-training presents challenges of scalability, cost, and domain-specific data scarcity. My research focuses on synthetic data generation as a solution to the data bottleneck in LLM post-training. By leveraging the generative capabilities of LLMs, synthetic data can reduce dependency on human annotation while maintaining diversity and quality. The core focus includes three aspects of synthetic data for LLM post-training: preference data construction, instruction augmentation, and response generation. This thesis outlines key findings from my PhD works. STIC introduces methods for self-training vision-language... https://escholarship.org/uc/item/3398t17x Wed, 18 Mar 2026 00:00:00 +0000 Deng, Yihe https://escholarship.org/uc/item/9xw9z7dw Precise control over light emission at the nanoscale is essential for advancing energy-efficient optoelectronic devices and emerging quantum photonic technologies. As semiconductor nanocrystals approach near unity photoluminescence quantum yield (PLQY), further performance improvements depend increasingly on directing emitted photons. Lead halide perovskite (CsPbX3 (X=halide)) (LHP) nanocrystals have unusually tunable angular emission due to their soft ionic lattice, which along with near-unity PLQY, defect tolerance, and facile emission wavelength tunability makes isolated LHP nanocrystals great candidates for photon qubit sources and close-packed films useful for light emitting diodes and solar energy technology. In this work, we investigate how the interplay of nanocrystal synthesis, surface chemistry, thin film assembly, and substrate interactions collectively govern transition dipole moment (TDM) orientation and thus angular light emission in CsPbBr3 nanocrystals.We developed... https://escholarship.org/uc/item/9xw9z7dw Tue, 17 Mar 2026 00:00:00 +0000 Grishchenko, Alexandra Yvette https://escholarship.org/uc/item/9nh5r9xp Cancer remains a leading cause of mortality worldwide, where patient outcomes depend strongly on early detection and rapid initiation of effective therapy. However, early cancer detection and effective targeted therapy remain critical challenges in modern medicine. Small extracellular vesicles (sEVs) or exosomes are nanoscale vesicles actively secreted by cells and carry molecular cargo reflective of their parental cell state, making them promising candidates for disease diagnosis and therapeutic delivery. However, conventional bulk averaged characterization techniques obscure vesicle-to-vesicle heterogeneity and often require destructive processing. This dissertation aims to overcome these limitations by enabling label-free, non-destructive, single-exosome biochemical analysis with high sensitivity and improved throughput via Surface-Enhanced Raman Spectroscopy (SERS) based single-vesicle analytical platform. A central technical contribution of this work is the batch fabrication... https://escholarship.org/uc/item/9nh5r9xp Tue, 17 Mar 2026 00:00:00 +0000 Liu, Jun https://escholarship.org/uc/item/8wm0x4vx Vision-Language Models (VLMs) achieve strong results on standard VQA benchmarks, yet it remains unclear how their performance is affected by low-level characteristic of target object. In this work, we take a controlled approach to diagnose visual perception limitations in current models. We formalize a patch-based input pipeline in which a scene is rendered on a fixed canvas, partitioned into non-overlapping patches, and encoded by a vision encoder into tokens for reasoning. Within this setting, we systematically examine three core factors that probe visual perception: (i) size sensitivity, analyzing how recognition varies as the target scales from tiny (few-token) to large (many-token); (ii) search complexity, evaluating robustness to distractors and background clutter; and (iii) alignment to patch grid, testing how the spatial alignment of small objects relative to the patch grid affects recognition. We construct a synthetic emoji-based dataset that precisely controls object... https://escholarship.org/uc/item/8wm0x4vx Tue, 17 Mar 2026 00:00:00 +0000 Yuan, Yuyang https://escholarship.org/uc/item/7z3046c8 Section 12.4.2 of the ASCE/SEI 7 (2022) provisions offer two alternative methods for estimating the seismic load effects due to vertical ground motions: one based on horizontal spectral acceleration at a short horizontal period, and the other on vertical spectral acceleration at a vertical structural period. This study examines the similarities and discrepancies between the two methods across the contiguous United States. A previous investigation, based on California sites, is generalized for the contiguous US covering Seismic Design Categories (SDCs) A through E and a full range of vertical structural period 0 to 10 seconds. Although structures with vertical periods approaching 10 s are unlikely in practice, this range is considered for completeness. Overall, 331,231 sites in the U.S. are analyzed in this study. A lognormal-based probabilistic model is developed to characterize the distribution of the ratio of the outcomes of the two methods across vertical period ranges for... https://escholarship.org/uc/item/7z3046c8 Tue, 17 Mar 2026 00:00:00 +0000 Peng, Cheng https://escholarship.org/uc/item/5dg508xg Noisy linear algebraic assumptions with respect to random matrices, in particular Learning with Errors (LWE) and Alekhnovich Learning Parity with Noise (Alekhnovich LPN), are among the most investigated assumptions that imply post-quantum public-key encryption (PKE). They enjoy elegant mathematical structure. Indeed, efforts to build post-quantum PKE and advanced primitives have increasingly focused their attention on these two assumptions and their variants.Unfortunately, this increasing reliance on these two assumptions for building post-quantum cryptography leaves us vulnerable to potential quantum and classical attacks on Alekhnovich LPN and LWE. Quantum algorithms is a rapidly advancing area, and we must stay prepared for unexpected cryptanalytic breakthroughs. Therefore, we ask the following question In a world where both LWE and Alekhnovich LPN are broken, can there still exist noisy linear assumptions that remain plausibly quantum hard and imply PKE?To answer this question... https://escholarship.org/uc/item/5dg508xg Mon, 16 Mar 2026 00:00:00 +0000 Ghosal, Riddhi https://escholarship.org/uc/item/5th2p5bv Mechanistic interpretability aims to reverse-engineer the internal computations of neural networks into human-readable algorithms. We study a decoder-only Transformer trained to predict legal moves in 6 × 6 Othello from move sequences alone, achieving 99.62% top-k legal-move accuracy. We train two sparse dictionary learning models using end-to-end cross-entropy training: JumpReLU transcoders (replacing MLP sublayers) and JumpReLU sparse autoencoders (reconstructing residual streams), preserving top-k accuracy at 99.3–99.6% across all layers.To measure each feature’s interpretability, we fit decision trees over hand-crafted boolean game features and evaluate the F1 score. A clear interpretability trend emerges across depth: in transcoder Layer 0, 58.1% of features achieve F1 > 0.99, whereas this fraction declines to 1.8% in Layer 5. The SAE exhibits a similar but smoother trend, from 35.8% in Layer 0 to 6.8% in Layer 5. We conduct causal intervention experiments to confirm that... https://escholarship.org/uc/item/5th2p5bv Fri, 13 Mar 2026 00:00:00 +0000 Zhang, Zhiyuan https://escholarship.org/uc/item/53w92385 Embodied AI is crucial for robotics applications, spanning autonomous driving and delivery systems to service robots in healthcare and hospitality. Traditional AI training methods, including reinforcement learning (RL) and imitation learning (IL), face significant challenges: IL requires expensive human demonstrations and struggles with distribution shifts, while RL, typically trained in simulation, suffers from the simulation-to-reality gap caused by simulator artifacts and reward misspecification. Recently, the emergence of large-scale vision-language foundation models has opened new avenues for embodied decision-making, yet effectively integrating these models into real-time robotic systems introduces unique challenges around inference latency, action grounding, and self-reflective reasoning. This dissertation addresses these challenges through three complementary pillars: large-scale data-driven simulation, vision-language foundation models for embodied decision-making, and... https://escholarship.org/uc/item/53w92385 Fri, 13 Mar 2026 00:00:00 +0000 Peng, Zhenghao https://escholarship.org/uc/item/8bz2c55m Young and older adults are often victimized by various forms of scams and fraud. However, few studies have investigated psychological factors that may make individuals more susceptible to scams. This dissertation explores the cognitive factors that could contribute to scam susceptibility in older adults, as well as potential interventions that could help young and older adults reduce the amount they fall victim to scams. Older adults’ trustworthiness, loneliness, confidence, and curiosity were examined as potential factors, as prior research has suggested that each may be linked to scam susceptibility. Associative memory deficits, gist-based false memory, and the reliance on schematic information in memory retrieval are all prevalent in older adults, and this dissertation aimed to investigate these further through their potential relationships to scams and fraud. In the present research, both younger and older adults participated in a scam susceptibility intervention for imposter... https://escholarship.org/uc/item/8bz2c55m Thu, 12 Mar 2026 00:00:00 +0000 Alberts, Kylie O'Brien https://escholarship.org/uc/item/6hq3c80n Epidermal growth factor receptor (EGFR) is the most frequently altered oncogenic driver in glioblastoma (GBM), yet prior EGFR inhibitors have demonstrated limited clinical benefit owing to variant heterogeneity and inadequate central nervous system (CNS) exposure. We developed KTM-101, a highly selective, reversible EGFR tyrosine kinase inhibitor engineered for potency against GBM-relevant variants, including amplified wild-type EGFR, extracellular-domain mutations, and EGFRvIII, while achieving robust brain penetration. KTM-101 demonstrated favorable brain-to-plasma ratios across species, durably suppressed intracranial EGFR signaling, and significantly prolonged survival in orthotopic patient-derived xenograft (PDOX) models. In early-phase clinical evaluation, KTM-101 achieved plasma and intracranial exposures exceeding preclinical thresholds for pathway inhibition, with initial evidence of disease control.Across a randomized efficacy study of 28 PDOX models recapitulating GBM... https://escholarship.org/uc/item/6hq3c80n Tue, 10 Mar 2026 00:00:00 +0000 Okobi, Quincy https://escholarship.org/uc/item/4611j60n The neocortex, particularly primary sensory cortices, develops under a dual mandate: establish pathways that provide stable perception, but allow room for experience-dependent adaptation to the statistics of the environment. Here, I examine the manifestation of this motif on the molecular, cellular, and circuit levels in the primary visual cortex (V1). I begin by reframing the classical critical period as a constructive developmental process beginning at eye opening, where a plastic pathway from the ipsilateral eye develops alongside a genetically specified contralateral scaffold. Largely hard-wired thalamocortical and layer 4 circuits provide tuned information to layer 2/3 (L2/3), where receptive fields in the binocular pool undergo experience-dependent sharpening via cellular exchange. My data reveal that long-range intracortical projections from L2/3 of V1 to higher visual areas (HVAs) are not uniformly experience-dependent. Dark rearing preferentially reduces feedforward projections... https://escholarship.org/uc/item/4611j60n Tue, 10 Mar 2026 00:00:00 +0000 Gorzek, Ryan https://escholarship.org/uc/item/1j8315gm As deepfake audio becomes increasingly realistic, the need for reliable detection models is critical. This thesis evaluates the effectiveness of statistical versus deep learning methods for identifying deepfake audio in the for-norm release of the Fake-or-Real dataset. Statistical baselines are established using Logistic Regression and Random Forest models trained on handcrafted, non-learned acoustic features. The Random Forest model achieves a strong test accuracy of 0.815 and a test AUC of 0.888, showing that classical signal processing features remain competitive. Deep learning models are evaluated using log-Mel spectrogram inputs and convolutional architectures, including a lightweight CNN trained from scratch and a ResNet18 model fine-tuned for single-channel spectrograms. Threshold-based metrics are computed using a decision threshold selected on the validation set and then fixed for test evaluation on the held-out test set. Using this framework, the CNN attains a test accuracy... https://escholarship.org/uc/item/1j8315gm Tue, 10 Mar 2026 00:00:00 +0000 Wen, Derek Haozhou https://escholarship.org/uc/item/6hs634p8 Democrats often live with minimal exposure to Republicans and Republicans often live with minimal exposure to Democrats. Leading accounts of partisan segregation document intense and rising segregation both across and within counties. Existing approaches for measuring partisan segregation either drop nonpartisans altogether or model their partisanship. These approaches also use single scale measures of segregation, like the index of dissimilarity. In this thesis, I measure partisan segregation with national voter registration records and a multiscale approach—Expected Kullback-Leibler Divergence—finding stable and relatively low levels of within-county segregation. I further describe patterns in segregation with a spatiotemporal conditional autoregressive model. https://escholarship.org/uc/item/6hs634p8 Mon, 9 Mar 2026 00:00:00 +0000 Straus, Graham https://escholarship.org/uc/item/9t19r1sg Superlattices, artificially structured solids composed of alternating layers with distinct compositions or electronic structures, have long served as a foundation for tailoring electrical, optical, and optoelectrical properties. Conventional epitaxial superlattices rely on covalent bonding and strict lattice matching between adjacent layers, which severely restricts the diversity of materials that can be combined. To overcome these constraints, layered hybrid superlattices (LHSLs) have recently emerged as a new class of designable solids composed of alternating two-dimensional (2D) atomic crystals and molecular intercalant inserted in their van der Waals gaps. LHSLs bridge the strengths of crystalline 2D layers, which exhibits long-range order, with the high-tunability of synthetic molecular systems that offer customizable structural topologies and diverse functionalities. This dissertation focuses on light–matter interactions in LHSPs, which bring unprecedented opportunities... https://escholarship.org/uc/item/9t19r1sg Fri, 6 Mar 2026 00:00:00 +0000 Zhou, Boxuan https://escholarship.org/uc/item/4w28h8m4 We study whether large language model (LLM) embeddings exhibit human-interpretable cluster structure. Using the Yelp Open Dataset for topic and sentiment labels, we extract sentence embeddings (primarily all-MiniLM-L6-v2) and evaluate unsupervised clustering via intrinsic indices (Silhouette, DBI) and extrinsic alignment (NMI, ARI, Purity). On a stratified sample of 60000 reviews across ten coarse topics (Restaurants, Food, Nightlife, Hotels, Shopping, Beauty, Automotive, Home, Health), fixed-k clustering with cosine geometry yields NMI=0.239, ARI=0.108, Purity=0.580 for topics, and NMI=0.060, ARI=0.040, Purity=0.740 for sentiment (positive=41755, negative=11362, neutral=6883). Encoder comparison indicates small but consistent gains from MPNet on NMI with a lower DBI, while MiniLM attains slightly higher Silhouette. Sensitivity analyses show modest degradation under class imbalance and little change with light Gaussian noise. We conclude that modern sentence embeddings support... https://escholarship.org/uc/item/4w28h8m4 Tue, 3 Mar 2026 00:00:00 +0000 Chen, Yutong https://escholarship.org/uc/item/5wz6s0hp Advances in single cell transcriptomics enable biomedical researchers to understand the molecular underpinnings of physiology and disease at unprecedented throughput and resolution. Gene regulatory networks (GRNs) have been powerful computational tools for single cell RNA sequencing (scRNAseq) to infer these molecular mechanisms in disease. While GRN methods and databases have been expanding in response to the expansion of scRNAseq data, they restrict their GRN modeling to known transcription factors and their targets, thereby overlooking many novel forms of gene regulation and interaction. Therefore, we created an open-access unbiased cell type GRN database and analysis platform to model global cell type interactions, hosting over 1300 human and mouse cell types across 8 scRNAseq data atlases to facilitate network biology research. We applied the database to study the genetic mechanisms driving learning and memory deficits in pediatric mild traumatic brain injury (mTBI) patients,... https://escholarship.org/uc/item/5wz6s0hp Mon, 2 Mar 2026 00:00:00 +0000 Cheng, Michael https://escholarship.org/uc/item/3p89g75q This thesis examines whether different machine learning models, when used to forecast firm-level equity returns, imply materially different stochastic discount factors, and whether those differences translate into economically meaningful variation in firm-level risk exposures and pricing errors. The analysis compares linear and nonlinear models including ordinary least squares regression, least absolute shrinkage and selection operator (LASSO) regression, principal components regression, gradient boosted decision trees, feedforward neural networks, and long short-term memory (LSTM) networks under a unified empirical design.Using monthly excess returns for S&P 500 constituent stocks from the Center of Research in Security Prices over the period 2000 to 2024, with predictors drawn from standard factor models and return-based anomalies, expected returns are first estimated at the firm level. These forecasts are then mapped into traded, time-varying stochastic discount factors... https://escholarship.org/uc/item/3p89g75q Tue, 24 Feb 2026 00:00:00 +0000 Berzins, Nils https://escholarship.org/uc/item/2hv655zj Foundation Models (FMs) have demonstrated strong generalization across a wide range of tasks. This success has motivated increasing interest in applying these models to sensor data processing, which underlies many Cyber-Physical Systems (CPS) such as autonomous transportation, smart infrastructure, and health monitoring. However, deploying FMs in sensor-driven applications introduces a complex design space. How the components in the system, such as data representation and model selection, interact and how they collectively shape model performance remains insufficiently understood. This dissertation investigates how FMs process sensor data from an end-to-end system. Rather than assuming FMs as a universal solution, the dissertation investigates their capabilities and limitations across different sensor processing problems, data characteristics, model families, inference interfaces, and adaptation strategies. To support this analysis, the dissertation introduces benchmark... https://escholarship.org/uc/item/2hv655zj Tue, 24 Feb 2026 00:00:00 +0000 Quan, Pengrui https://escholarship.org/uc/item/7hn5f9nd This dissertation presents three empirical studies examining the intersection of political institutions, information, and civic engagement in the United States. Together, these essays contribute to our understanding of how institutional design shapes political behavior and democratic participation, while also demonstrating some advantages and some nuances of using contemporary causal inference approaches in observational settings.The first essay examines whether federal disaster relief favors congressional districts represented by the president's copartisans. Using a regression discontinuity design that exploits close congressional elections from 2001-2020, I compare FEMA funding in districts that narrowly elect a member of the president's party to those that narrowly elect an opposition member. I find that copartisan districts receive approximately 45% less federal disaster relief than opposition districts (p=0.062), with this negative effect consistent across the Bush, Obama,... https://escholarship.org/uc/item/7hn5f9nd Fri, 13 Feb 2026 00:00:00 +0000 Geyn, Igor https://escholarship.org/uc/item/8fp651bd Traumatic brain injury (TBI) is a major public health concern affecting millions worldwide, yet the underlying alterations in brain dynamics remain poorly understood. This thesis presents a novel approach to analyzing dynamic functional connectivity in TBI using Gaussian Mixture Variational Autoencoders (GMVAE). We apply this deep learning framework to blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data from a controlled cortical impact (CCI) rodent model to identify distinct brain states and characterize their temporal dynamics.Our GMVAE approach demonstrates superior clustering performance compared to traditional methods including Leading Eigenvector Dynamics Analysis (LEiDA) with k-means clustering. The model reveals interpretable latent spaces and meaningful brain state configurations. Statistical analysis of fractional occupancy, dwell times, and transition probabilities reveals significant alterations in brain dynamics following TBI compared... https://escholarship.org/uc/item/8fp651bd Wed, 11 Feb 2026 00:00:00 +0000 Azargushasb, Azad https://escholarship.org/uc/item/76w0d9k1 Adoptive cell therapy using T cells engineered to express chimeric antigen receptors (CARs) has shown remarkable clinical efficacy in treating B-cell malignancies, yet its efficacy against solid tumors has been poor in part due to the highly immunosuppressive nature of the solid tumor microenvironment (TME). Specifically, vascular endothelial growth factor A (VEGF-A) presents as a physical barrier through its pro-angiogenic properties and contribution to excessive tumor vascularization, giving rise to abnormal and dysfunctional vessels with impaired perfusion thus leading to intratumoral hypoxia. Furthermore, VEGF-A serves as a chemical barrier by suppressing T-cell activation and cytotoxicity, upregulating immune checkpoints on T cells, inhibiting dendritic cell maturation, and recruiting immunosuppressive cells. In this dissertation, we present a strategy to enhance CAR-T cell efficacy and reprogram the TME by engineering CAR-T cells to secrete a newly developed anti-VEGF single-chain... https://escholarship.org/uc/item/76w0d9k1 Wed, 11 Feb 2026 00:00:00 +0000 Gao, Torahito Adachi https://escholarship.org/uc/item/73x2g7qr Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are major retinal diseases and the leading causes of vision loss in the working-age and elderly populations, respectively. Although current clinical therapies aim to resolve the advanced stages of both DR and AMD, there is a recognition that more effective therapy management can be achieved by intervening at earlier stages.Vascular inflammation is considered a key contributor to retinal and choroidal vascular degeneration, a clinical hallmark of both early DR and AMD. Yet, the underlying mechanisms leading to inflammation-mediated endothelial cell (EC) death, which ultimately leads to vascular degeneration, remain poorly understood.Past studies investigating these vascular abnormalities have focused primarily on the role of molecular or biochemical cues. However, scientific discoveries now highlight the critical role of mechanical cues in maintaining vascular stability in healthy tissue. Additionally, vascular... https://escholarship.org/uc/item/73x2g7qr Sat, 31 Jan 2026 00:00:00 +0000 Santiago Tierno, Irene https://escholarship.org/uc/item/28d8b7wd Most human–AI systems today are built around a default paradigm of turn-by-turn interaction: users act, systems respond, and collaboration unfolds through discrete exchanges. While effective for many tasks such as conversational agents, this model shapes interaction to be linear rather than multidimensional, reactive rather than proactive, and transient rather than persistent.Drawing on theories from communication and linguistics, this thesis argues that turn-taking has become an implicit and largely unexamined design constraint in human–AI interaction. I propose moving beyond turn-taking by introducing interaction structures that support parallel communication, proactive participation, and persistent shared spaces.This thesis presents three interactive systems that instantiate and evaluate these structures in real-world contexts: Visual Captions demonstrates parallel communication by augmenting verbal conversations with real-time, AI-generated visuals. Inner Thoughts demonstrates... https://escholarship.org/uc/item/28d8b7wd Fri, 30 Jan 2026 00:00:00 +0000 Liu, Bruce https://escholarship.org/uc/item/8xj4c26h This dissertation examines how regulatory shocks, information transmission, and policy uncertainty affect financial markets across three distinct settings. In Chapter 1, I study the financial market response to the SEC’s proposed climate disclosure rule announced on March 21, 2022. Using an event study, I document that firms with high environmental scores experienced negative abnormal returns while low-scoring firms earned positive returns. ESG mutual funds exhibited a similar pattern, reallocating capital toward environmental laggards in the post-announcement quarter. These results suggest investors interpreted the Scope 3 mandate as a regulatory equalizer that erodes the advantage of voluntary disclosure leaders.In Chapter 2, I examine whether sentiment expressed by social media influencers propagates through follower networks to affect housing prices. Using 1.2 million real estate-related tweets from the 50 most populous U.S. cities, I find that influencer sentiment predicts... https://escholarship.org/uc/item/8xj4c26h Thu, 29 Jan 2026 00:00:00 +0000 Cheah, May Lyn https://escholarship.org/uc/item/61f2t5g4 The thesis examines how birth control was practiced, represented, and morally judged in Ming-Qing China through legal, literary, and medical sources. Here, I define birth control as practices engaged in by women, couples, or families encompassing everything from contraceptive methods to abortion and infanticide. Because the state discouraged birth control, the archival record is marked by silence: medical handbooks did not record many effective and safe contraceptive or abortifacient formulae; legal cases frame abortion as evidence of illicit sex; and literary works picture birth control as dangerous moral transgression. However, by reading against the grain, it reviews that people across social classes employed a wide range of methods to manage fertility under economic or emotional pressures.The thesis argues that women’s autonomy in reproductive decision-making did not always align with better outcomes. When birth control was a collective family decision, women had access... https://escholarship.org/uc/item/61f2t5g4 Thu, 29 Jan 2026 00:00:00 +0000 Zhao, Wan