VictorJuiz/thesis huggingface dataset:
Building Trusted Execution Environments

Trusted Execution Environments (TEEs) offer hardware-based isolation, which protects the integrity and confidentiality of the in-use data of programs against various threats. Many hardware vendors have produced various TEE-enabled chips. However, there has been only a little public research on building TEEs. Building a TEE with different threat models and functionalities relies on design-space exploration. For example, a TEE must quickly adapt to various evolving threat models. In addition, a TEE can have different functionality requirements, which should not impact security guarantees. This thesis discusses research challenges in exploring the TEE design space. First, this thesis motivates why a TEE should not have a fixed threat model by demonstrating a novel off-chip side-channel attack on a TEE. Next, this thesis proposes Keystone, a software framework that enables building TEEs based on various needs, such as threat models and functionality requirements. Furthermore, this thesis discusses how to extend TEE functionality without breaking security guarantees using incremental verification.

Advisor: Asanovic, Krste
Optimization Algorithms in Variational Monte Carlo for Molecular Excited States

The accurate description of molecular excited states is an active frontier in the development of electronic structure theory. Compared to their ground state counterparts, electronic structure methods for excited states remain less well developed and many of the most widely used options struggle to provide accurate and predictive results across all varieties of excited states. This thesis presents a series of contributions to the development of variational Monte Carlo (VMC) as a broadly reliable tool for excited states, with a particular emphasis on wave function optimization algorithms./nWe first present an analysis of current first and second order optimization techniques in VMC, demonstrating that each class of algorithm has strengths and weaknesses in terms of convergence and computational efficiency. The complementary nature of these traits motivates the design of a hybrid optimization algorithm, which can overcome the individual disadvantages of its constituent methods. After first developing this approach for ground state energy minimization, we extend it to the minimization of a variance-based objective function for the state-specific targeting of excited states. We demonstrate that employing VMC with the hybrid optimization algorithm can obtain highly accurate excitation energies across multiple classes of excited states, including single valence excitations, double excitations, and charge transfer. This level of reliability currently eludes all other electronic structure methods that can be applied beyond small molecules and enables VMC to serve as a widely applicable benchmark method for assessing which computationally cheaper methods are most trustworthy in various chemical contexts. We also continue our methodological work by presenting a systematic study of the issue of optimization stability in VMC and identify best practices for successful variance minimization that may aid the work of other researchers.

Advisor: Neuscamman, Eric
Neaton, Jeffrey
Efficient and Scalable Neural Architectures for Visual Recognition

The successful application of ConvNets and other neural architectures to computer vision is central to the AI revolution seen in the past decade. There have been strong needs for scaling vision architectures to be both smaller and larger. Small models represent the demand for efficiency, as the deployment of visual recognition systems is often on edge devices; large models highlight the pursuit for scalability - the ability to utilize increasingly abundant compute and data to achieve ever-higher accuracy. Research in both directions are fruitful, producing many useful design principles, and the quest for more performant models never stops. Meanwhile, the very fast development pace in the literature can sometimes obscure the main mechanism responsible for certain methods' favorable results./nIn this dissertation, we will present our research from two aspects in this area: (1) developing intuitive algorithms for efficient and flexible ConvNet model inference; (2) studying baseline approaches to reveal what is behind popular scaling methods' success. First, we will introduce our work on one of the first anytime algorithm for dense prediction. We will then examine the effectiveness of model pruning algorithms by comparing them with an extremely simple baseline, and argue their true value may lie in learning architectures. Finally, We present our work on questioning whether self-attention is responsible for Transformer's recent exceptional scalability in vision, by modernizing a traditional ConvNet with design techniques adapted from Transformers.

Advisor: Darrell, Trevor
Breaking the Learning Curve: Assessing Flintknapper Skill at the Epipalaeolithic Site of Kharaneh IV, Jordan

Learning is a fundamental aspect of the human condition. It allows us to interact within a world of socially constructed meanings and to create individual and group identities (Jarvis 2012; Lave and Wenger 1991; Wenger 1998). My research investigates knowledge transmission during the Epipalaeolithic Period at the hunter-gatherer site of Kharaneh IV (≈20,000 BP) (Maher and MacDonald 2013) and argues that stone tool production (flintknapping) can be viewed as a practice that reflects normative rules guiding the interactions of flintknapping communities in the ancient past. Evidence of the practice can shed light on an ancient habitus related to learning and participating within a community of practice (Lave and Wenger 1991; Cole 1996; Weisner 2002; Rogoff 2003; Maynard and Greenfield 2006; Joyce 2008; Wallaert 2012; Takakura 2013). The study of education in archaeology primarily focuses on ceramics as it is an additive process where each step is identifiable through microscopic analyses. While these studies have proven useful for understanding how novices learned practices in the past, in most regions ceramics only extend back to about 8,000 years BP and studies on apprenticeship and learning rarely extend past the Bronze Age (Hasaki 2012). To examine a reductive technology like flintknapping one must take a different approach than previously established ceramics studies on apprenticeship (Gosselain 2000; Wallart 2012; Hasaki 2012). The waste products, debitage, are the basis for analysis rather than the final tool form as each removal of flint during the production process preserves prior removal scars and indicates how an individual piece was removed. The knowledge of where to find raw materials, how to ‘correctly’ reduce a blade core, and what constitutes a tool is circumscribed by the community (Ortner 2001; Joyce 2008; Pea and Cole 2019). Therefore, lithic artifacts may represent normative practices of flintknapping during the Epipalaeolithic. New materials or techniques can reflect changing dynamics within a community as the establishment and continuity of traditions are reliant upon ongoing apprentice/master relationships (Lancy 1980; Lave and Wenger 1991; Wallaert-Pêtre 2001; Greenfield et al. 2003; Milne 2012; Takakura 2013). By studying how unskilled flintknapping events are spatially related to skilled flintknapping events we can begin to reveal the habitus of a community of practice. Applying Lave and Wenger’s (1991) legitimate peripheral participation to lithic artifacts and flintknapping education during the Epipalaeolithic, I pose a fundamental question: Can learning and evidence of a sociotechnological practice be used to understand the habitus constructed around flintknapping at the Epipalaeolithic hunter-gatherer site of Kharaneh IV?

Advisor: Maher, Lisa A
Probing Inflation from the South Pole: A Measurement of the B-mode Polarization of the Cosmic Microwave Background with SPT-3G

The Cosmic Microwave Background, the oldest light in the universe, provides a powerful tool to test the theory of inflation and constrain the standard ΛCDM cosmological model. The theory of inflation describes a period of rapid, exponential growth in the early Universe. A measurement of r, the tensor-to-scalar ratio of CMB polarization, would provide evidence for inflation and measure its energy scale. However, this is an extremely difficult measurement to make due to the faintness of the signal. Historically, Small Aperture Telescopes (SATs) have been used to constraint inflation. However, there is immense power that can be gained by combining the low-ℓ (large angular scale) measurements from Large Aperture Telescopes (LATs), such as the South Pole Telescope (SPT), with SATs./nThe first part of this dissertation describes the design, characterization, and deployment of the SPT-3G receiver on the SPT. There is special emphasis placed on the development and characterization of the frequency-multiplexed readout, and characterization of system crosstalk. The second part of this dissertation uses data from the 2019 and 2020 austral observing season over a 1500 deg² patch of sky to make low-noise maps of the B-mode polarization of the CMB. This delves into techniques used for mitigating low-ℓ noise sources, including polarized atmosphere. These include weighting schemes, and an unbiased method to remove this noise source from data utilizing co-pointing detectors of different frequencies and the fixed spectral scaling of polarized atmosphere in accordance with Rayleigh scattering. This work serves both as demonstration of a LAT achieving high sensitivity at low-ℓ and as a study of atmospheric noise that will inform the design and operation of future LAT and SAT telescopes. This shows a path for producing competitive r constraints from a LAT optimized for high-ℓ science, and is a proof-of-concept for using LAT data in the search for primordial gravitational waves with next-generation CMB experiments.

Advisor: Holzapfel, William
Music For Ending Things

“Music For Ending Things” is a 20-minutes long piece in two movements, written for piano and keys, tenor saxophone, electric guitar and percussion. It explores the potentials of a compositional approach based on creating a narrative by sound. The piece takes its inspiration from the art of cinema and weaves an imaginary midnight journey by the help of the diverse sonic palette created by the extended techniques used in the acoustic instruments, and live electronics.

Advisor: Campion, Edmund
Smart Data-Driven Decision-Making with Uncertainty: Methods and Applications in Supply Chain Management

The past decade has seen tremendous growth in the availability of voluminous high-quality data in many modern decision systems such as supply chain management. Big data provides new opportunities to tackle one of the main difficulties in decision-making systems – uncertain behavior driven by some unknown ground truth probability distribution. My dissertation mainly focuses on answering the following question: How do we use (non-perfect) data samples generated from the unknown distribution to make more automatic and reliable decisions, especially for supply chain management and retail operations?/nIn Chapter 2, this dissertation study a practical multi-period inventory management problem faced by online retailers and propose a practical, data-driven, end-to-end (E2E) framework for multi-period inventory management that leverages the power of deep learning. Instead of adopting the two-step approach that first forecasts demand and vendor lead-time (VLT) separately and then, based on the predictions, solves for a solution that minimizes inventory costs, we directly learn the underlying mapping from features to the optimal solution by adopting a supervised learning approach./nIn Chapter 3, we propose an integrated conditional estimation-optimization (ICEO) framework that uses statistical learning theory to estimate the underlying conditional distribution while considering the structure of the optimization problem. This method provides a generic learning framework and applies to a broad class of convex contextual stochastic optimization problems with uncertainty in the objective. We provide statistical performance guarantees and address the computational challenges that arise in performing this framework./nIn Chapter 4, we focus on data-driven distributionally robust optimization (DRO) methods. We examine the conditional quantile prediction problem, which is equivalent to the contextual newsvendor problem, and propose a DRO framework. In contrast to the traditional setting where the design points are considered as random and i.i.d., we consider a fixed-design setting, which is more suitable for cases when features are pre-designed, such as through a series of controlled experiments./nChapter 5 continues our study on the contextual newsvendor problem and considers inter-temporal correlations and moderate non-stationarities in the contextual demand process. Under these comparatively more realistic assumptions, we provide performance guarantees in the form of out-of-sample generalization bounds.

Advisor: Shen, Zuo-Jun
Uneven Ground: The Archaeology of Social Transformation in Zanzibar, Tanzania

Uneven Ground synthesizes archaeological field survey, historical map analysis, ceramic analysis, and geospatial modeling to investigate a region of northern Zanzibar, Tanzania across multiple environmental zones and time periods. Results address fundamental anthropological questions related to landscapes of settlement, historical ecology, and social change. I reconstruct settlement systems in the inland areas of the island, across four transformative historical periods: 1) the initial recolonization of the island by early Swahili people in the late first millennium, 2) social stratification and precolonial urbanism in the early second millennium, 3) Portuguese and Omani rule in the early colonial period (1500-1830 CE), and 4) during the development of the plantation system starting around 1830, and the formation of the Omani (1749-1856) and Zanzibari (1856-1963) states.Results show that inland villages of the early second millennium (1000-1400 CE) and plantation estates of the late colonial period (1830-1963 CE) developed across similar contexts in the central and western regions of north Zanzibar, where environmental conditions favored intensive agricultural production. These areas supported large settlement systems, but sociopolitical changes disrupted occupation in this region across multiple periods. In contrast, the agriculturally marginal and rocky eastern regions supported enduring small-scale occupations from the earliest period to the present. Landscapes of the east have the longest and most consistent history of settlement and land use in the survey region. This was made possible by specific techniques of agricultural landscape modification and proximity to near-shore reefs. Parts of the eastern region may have served as a refuge during politically turbulent periods. I also demonstrate that starting around 1830, the development of the plantation system transformed settlements across rural inland areas in north Zanzibar. Archaeological and geospatial analyses show the effects of this episode on rural communities. Settlement systems clustered spatially and became more politically integrated for the first time. Imported ceramics increased in count and variability, and local ceramics became more standardized in temper, fabric color, clay color, and form. Settlement and ceramic trends reflected the impacts of the mass importation of enslaved East Africans into rural areas on the island, the entrainment of Zanzibar’s agricultural landscapes within global commodity flows, and the contours of state formation and political integration across the island. Spatial analyses show that while 19th-century elites in the urban center of Stone Town were able to extract wealth from the rural areas, they did not successfully integrate heterarchical elements within their state. This pattern shaped anti-colonial resistance and revolution at the end of the late colonial period.

Advisor: Maher, Lisa
A Dramaturgical Framework for Interactive Performance: Sensitizing Concepts at the Intersection of Performance and Technology

Performances tell compelling stories, provide an escape from (or new perspective on) everyday life, help us connect with each other, and teach us about the world. In this work, I seek to identify, categorize, and expand existing notions of “performance” as it is operationalized within the world of HCI, and articulate the ways in which core HCI concerns — including identity, agency, immersion, self-presentation, social interaction — can and should be investigated through performance. Through 1) incorporating core theatrical values into the design of novel computer-mediated communication systems 2) designing, constructing, and deploying functional prototypes during long-term collaborations with expert theatre practitioners, and 3) designing creativity support tools that embody expert values in order to scaffold newcomers into sustainable creative practice, my work emphasizes the ways that HCI can shape and be shaped by rich understanding of and engagement with performance. I embrace ‘performance’ as an understanding of the way people present themselves (as performers) to others (an audience) and investigate this in technologically-mediated environments. This thesis seeks to “illuminate the specific ways in which performance might further enrich...HCI research” (Spence et al., 2013).

Advisor: Paulos, Eric
Mexicana/Latina Campesinas Cultivating Knowledge: A Collective Agricultural Land-Based Education in Central Washington State in the Homelands of Yakama Nation

Rooted in Chicana/Latina feminism and interdisciplinary frameworks, this dissertation uses autoethnographic (Behar, 1996), participatory (Baquedano-López, 2021; Irizarry & Brown, 2014), and art-based research (Leavy, 2015; Delgado Bernal, Burciaga & Flores Carmona, 2012) to document Mexicana/Latina campesinas' education in agriculture in the homelands of the Yakama Nation. Agricultural land-based education, the education paradigm that I am theorizing, encompasses Mexicana/Latina campesinas' education or their active and intentional production of knowledge in which they are generating ways of being/knowing that entail sensibilities, skills/movements, and relationships to live, be, work, and teach/learn in agriculture. Guided by campesinas' conceptualizations of words, I break down three interconnected elements of campesinas' education: coyote literacies, ligera strategies, and pedagogies of barbear. The first element, coyote literacies, captures campesinas' ways of being/knowing and their reading sensibilities (in mind.body.spirit) to navigate across the terrains of agriculture to sobrevivir (survive and thrive) (Galván, 2015). The second element, ligera strategies, shows campesinas' life methods that actively build solidarity and meaningful interactions. The third element, pedagogies of barbear, highlights campesinas' teaching/learning approaches that draw on body-land-agriculture as the educational material. I argue that through campesinas' education, they demonstrate not to be passive workers but intersectional social actors/educators that create knowledge, literacies, and new identities to live and work with dignity.

Advisor: Baquedano-López, Patricia
Early dosage compensation of zygotically-expressed genes in Drosophila melanogaster is mediated through a post-transcriptional regulatory mechanism

Many key regulators of early embryogenesis in Drosophila melanogaster are X-linked. However, the canonical, MSL-mediated dosage compensation, which involves hyper-transcription of the genes on the single X chromosome in males, is not active until the post-syncytial stage of development. A separate MSL-independent dosage compensation system active earlier in development has been described, though the mechanism through which the process functions remain unclear. In this study, we quantified transcription in living embryos at single-locus resolution to determine if early dosage compensation of the X-linked genes buttonhead and giant is sensitive to X chromosome dose. We found no evidence for a transcriptionally regulated mechanism of early dosage compensation, suggesting that the previously observed compensation of mRNA levels for these genes is achieved via a post-transcriptional regulatory mechanism.

Advisor: Eisen, Michael B
Trauma and the Intergenerational Transmission of Disadvantage

Childhood trauma constitutes a major public health crisis in the United States, with an estimated two thirds of children experiencing at least one traumatic event by the age of 16. Despite the prevalence of childhood trauma, there has been very little sociological research on this subject. Using rich data from the National Longitudinal Study of Adolescent Health, the current dissertation project offers important new insights on the contours and consequences of childhood trauma. The first analytic chapter shows how neighborhood racial segregation is an important determinant for exposure to multiple types of violence. The findings suggest that adolescents living in more racially segregated communities are more likely to report exposure to violence. The second analytic chapter examines whether exposure to multiple traumas or “complex trauma” mediates the association between family structure and various “markers” of life chances in adulthood. The analysis shows that children born to single mother families, relative to children who are born to two biological or adoptive parent families, are more likely to experience complex trauma in childhood, which accounts for a significant portion of the association between family structure, adult incarceration, and college completion. Finally, the third analytic chapter examines the relationship between witnessing community violence and criminal legal system involvement in young adulthood. This analysis shows that adolescents who witness community violence are significantly more likely to become incarcerated in young adulthood. The analysis also finds significant racial disparities in witnessing violence, suggesting that exposure to community violence is a potentially important mechanism in the production of racial inequalities in criminal legal system involvement.

Advisor: Harding, David J