VictorJuiz/thesis huggingface dataset:
Privacy and Scalability for Decentralized Cryptographic Systems

The past few years have seen growing interest in decentralized systems owing to their improved censorship-resistance, fault tolerance, and auditability compared to their centralized counterparts. For example, ideas popularized in decentralized protocols like Bitcoin and Ethereum have seen widespread adoption and publicity. However, the benefits of these systems often come at the expense of privacy and scalability: to ensure the correctness of computations, decentralized systems like Ethereum require that parties publish their entire computational state, which is then checked by re-executing the computation. From the privacy perspective, this reveals which computation was performed, the data that was input to the computation, and the identity of the involved users. From the scalability perspective, re-execution means that the cost of expensive computations is borne by every party in the system, as opposed to just the party invoking the computation./nIn this dissertation, we show how to overcome these shortcomings and obtain decentralized systems that achieve strong privacy and scalability properties. We do so by providing new constructions and applications of a powerful cryptographic primitive: zero-knowledge succinct non-interactive argument systems, or zkSNARKs. We design new methodologies for constructing zkSNARKs that have lower deployment overhead and improved efficiency compared to the prior state-of-the-art. Finally, we go on to construct a system for decentralized private computation that takes advantage of these advances to make all transactions indistinguishable, thus ensuring privacy (transactions reveal no information about the computation) and scalability (transactions can be verified in time independent of the computation).

Advisor: Chiesa, Alessandro
Popa, Raluca
Strong Correlation Through Selected Configuration Interaction: From Molecules to Extended Systems

The theoretical description of many-body systems, be it molecular or extended, from first principles has been one of the principal goals of the physical sciences since the advent of quantum mechanics. This is unfortunately an exceptionally complicated endeavour, especially so in the so called ``strongly correlated'' systems. These are characterized by their qualitative behavior being dominated by particle-particle interactions, which precludes their accurate description using effective one-body approaches, such as Kohn-Sham density-functional theory. As a consequence of their remarkable complexity, strongly correlated materials present a wide palette of exciting collective phenomena of huge technological interest. Paradigmatic examples are high temperature superconductors based on transition metal oxides or pnictides, materials presenting colossal magnetoresistance, or iron/molybdenum based catalytic centers in biological systems. With the ample range of potential applications in mind, from energy conversion and storage to the development of new principles for information processing devices, great interdisciplinary effort, combining condensed matter physics, quantum chemistry and materials science, has been dedicated over the last decades to devising and applying accurate theoretical and numerical approaches for the description and prediction of electronic properties arising from strong correlation./nUnfortunately, due to the rich variety of physical and chemical principles which can result in strongly correlated behavior, there is currently no single method which can be successfully applied to all correlated many-body systems. On the contrary, a broad toolkit composed of analytical theories and computational approaches has been developed over the years, each based on a different heuristic to simplify the solution of the problem, and therefore each being applicable accurately on a different class of many-body system. In this thesis, we have refined and developed one such tool in the many-body toolbox: the adaptive sampling configuration interaction (ASCI) method. This is an exceptionally efficient selective configuration interaction approach, originally formulated to provide accurate ground state energies of molecular systems with a moderate computational cost. Here, we further extend the ASCI framework to compute accurate spectral properties, accessible through the one-body Green's function, allowing us to study excited state properties as well as to apply ASCI to extended systems by using it as impurity solver within the dynamical mean-field theory (DMFT). This makes ASCI noticeably versatile, and we employ it to contribute to open problems in quantum computation, molecular physics and computational condensed matter theory. This wide applicability shows ASCI to be a useful new addition to the many-body theory tool-set. In particular the ASCI-DMFT approach introduced here holds great promise for the \emph{ab initio} study of strongly correlated materials.

Advisor: Whaley, K. Birgitta
Privacy Controls for Always-Listening Devices

Intelligent voice assistants and other microphone-enabled Internet of Things devices are increasingly popular but may pose grave privacy risks. As more technologies take advantage of continuous audio access, new products may emerge that are passively listening and actively analyzing all conversations they hear, instead of only processing commands that follow their wake-words. The research in this dissertation investigates how to develop a privacy permission system for these devices. It takes a user-centered perspective on this problem and uses empirical methods to study the research questions that can guide the design of the privacy controls:/n- What are people's expectations about what information needs to be protected and in what context?- Which privacy-enhancing techniques could be feasibly applied to limit the devices' listening? How do people perceive their trade-offs and acceptability? - Which interfaces and affordances would allow users to express their privacy preferences and explore the implications of their choices?/nThis dissertation explores these questions through a combination of surveys, user studies, and prototype evaluations. Major conclusions include:/n- People exhibit nuanced and heterogeneous preferences, notably in relation to other members of their households, and are especially wary of undisclosed data flows to third parties. They are most protective of financial data and other information that can cause them harm.- Block-listing and filtering approaches may be most feasible to implement. In combination with existing techniques and privacy-friendly design choices, they can address immediate user requirements. However, more complex privacy needs must be addressed with content-based controls, which require additional research in privacy and natural language understanding. - People appreciate the control install-time and runtime permissions provide over their own data. However, both have challenges with their user experience. Transparency-based approaches may be comparatively frictionless.

Advisor: Wagner, David
Egelman, Serge
Isolated Photon Hadron Correlations in √sNN = 5.02 TeV pp and p–Pb Collisions

This work presents the measurement of isolated photon-hadron correlations and the first study of photon-tagged fragmentation in p–Pb at the Large Hadron Collider using pp and p–Pb data collected by the ALICE detector. Prompt photons produced at leading order in hard scatterings constrain the kinematics of the recoiling parton, enabling the study of parton energy loss and modification to the parton fragmentation function. For photons with |η| < 0.67 and 12 < pT < 40 GeV/c, the associated yield of charged particles in the previously unexplored kinematic range of 0.5 < pT < 8 GeV/c is measured. No significant difference between pp and p–Pb is observed. Pythia 8.2 and cold nuclear matter theoretical models can describe both data sets within uncertainties, setting constraints on cold nuclear matter effects on the parton fragmentation in p–Pb collisions.

Advisor: Jacak, Barbara
Trajectory Optimization and Control of Small Spacecraft Constellations

Large (> 1000kg), expensive (> $1bn), monolithic, flagship-class satellites (e.g., Hubble, Chandra, James Webb telescopes) may soon be overshadowed by constellations of many, smaller, cheaper, more agile spacecraft working together as a coordinated system. In this work, we study several important attitude and orbit control problems relevant to the formation and operation of small spacecraft constellations. Our example problems include agile attitude maneuvering for multi-target acquisition in an Earth observation application, a centralized approach to constellation formation in low Earth orbit, a distributed approach to constellation formation in Mars areostationary orbit, and orbital rendezvous with objects in the inner Solar System. Our main tool is trajectory optimization, an approach that is appropriate for spacecraft applications where we often seek solutions that are optimal (e.g., minimum-time, minimum-fuel, minimum-control-effort) in the presence of mission or spacecraft constraints. We employ recent advances in sequential convex programming to efficiently handle the nonlinear dynamics and non-convex constraints that exist in our problem formulations.

Advisor: Arcak, Murat
Three-Dimensional Phase Contrast Electron Tomography For Multiple Scattering Samples

Three-dimensional (3D) electron tomography (ET) is used to understand the structure and properties of samples, for applications in chemistry, materials science, and biology. By illuminating the sample at many tilt angles using an electron probe and modelling the image formation model, 3D information can be reconstructed at a resolution beyond the optical diffraction limit. However, as samples become thicker and more scattering, simple image formation models assuming projections or single scattering are no longer valid, causing the reconstruction quality to degrade. In this work, we develop a framework that takes the non-linear image formation process into account by modelling multiple-scattering events between the electron probe and the sample. First, the general acquisition and inverse model to recover multiple-scattering samples is introduced. We mathematically derive both the forward multi-slice scattering method as well as the gradient calculations in order to solve the inverse problem with optimization. As well, with the addition of regularization, the framework is robust against low dose tomography applications. Second, we demonstrate in simulation the validity of our method by varying different experimental parameters such as tilt angles, defocus values and dosage. Next, we test our ET framework experimentally on a multiple-scattering Montemorillonite clay, a 2D material submerged in aqueous solution and vitrified under cryogenic temperature. The results demonstrate the ability to observe the electric double layer (EDL) of this material for the first time. Last but not least, because modern electron detectors have large pixel counts and current imaging applications require large volume reconstructions, we developed a distributed computing method that can be directly applied to our framework for seeing multiple-scattering samples. Instead of solving for the 3D sample on a single computer node, we utilize tens or hundreds of nodes on a compute cluster simultaneously, with each node solving for part of the volume. As a result, both high resolution sample features and macroscopic sample topology can be visualized at the same time.

Advisor: Waller, Laura
Life Finds a Way: Carnivore Movement and Conflict in Developing Landscapes

Human-carnivore conflict (HCC) is a major conservation challenge that drives declines of large carnivore populations and impacts human livelihoods and major industries. Protected areas are often unable to support wildlife without surrounding unprotected and developed dispersal areas, where they may spend large portions of their time. Predictive mapping of carnivore predation risk based on verified livestock predation has created new tools for effective HCC management. Yet, rarely are verified conflict and ecological data integrated with social and attitudinal data describing people’s perceptions of risks from carnivores, despite their importance for carnivore conservation. This dissertation explores methods of incorporating participatory spatial knowledge with carnivore ecology and behavior, land use, human infrastructure, and human activity. This research contributes to theoretical understandings of social and spatial factors contributing to HCC and carnivore management in developed landscapes, and explores the effectiveness of using participatory and multidisciplinary methods for conservation in a rapidly changing world. In Chapter 1, I introduce theories underlying this research, describe the study site, and contextualize the research questions within the global trend of carnivore responses to increasing human activity. Chapter 2 applies ecological theory to describe predation on domestic prey and devises an ecological framework for understanding and mitigating HCC. Case studies demonstrate its utility for employing appropriate conflict interventions in varying ecological contexts. Chapter 3 maps patterns of verified and perceived HCC using community participatory mapping and verified livestock predation records, and provides recommendations for incorporating ecological data and participatory social data to more effectively and holistically address conservation challenges. Chapter 4 uses fine scale telemetry data to analyze spotted hyena behaviors around human infrastructure and human activity across land cover types, human risk perceptions, land management zones, and seasons. I then discuss the broader implications of these findings for “adaptable” large carnivore species that share landscapes with people globally. Chapter 5 explores wildlife behavioral responses to one of the most widespread forms of human-wildlife conflict mitigation: the conservation fence. I show that, regardless of fence maintenance, most wildlife species are likely to cross these fences. I discuss implications of these findings for fenced protected areas globally, and offer the first known guidelines for classifying wildlife fence-specific behaviors from camera trap imagery. Finally, in Chapter 6, I make recommendations on how carnivore conservation and HCC management should be informed by ecological, social, and participatory data and methodologies.

Advisor: Kelly, Maggi
Essays on Markets and Institutions

This dissertation studies how agents and firms interplay under different market institutions. In the first two chapters, co-authored with Rodrigo Carril and Michael Walker, we study the implications of policies oriented to intensify competition for procurement contracts. Conceptually, opening contracts up to bids by more participants leads to lower acquisition costs. However, expanding the set of bidders hinders buyers' control over the quality of prospective contractors, potentially exacerbating adverse selection on non-contractible quality dimensions. We study this trade-off in the context of procurement by the U.S. Department of Defense. Our empirical strategy leverages regulation that mandates agencies to publicize contract opportunities whose value is expected to exceed a certain threshold. We find that advertising contract solicitations increases competition and leads to a different pool of selected vendors who, on average, offer lower prices. However, it also worsens post-award performance, resulting in more cost overruns and delays. This negative effect on post-award performance is driven by goods and services that are relatively complex, highlighting the role of contract incompleteness. To further study the scope of this tension, we develop and estimate a model in which the buyer chooses the extent of competition, and the invited sellers decide on auction participation and bidding. We estimate sellers' cost and ex-post quality distributions, as well as buyers' preference parameters over contract outcomes. Simulating equilibrium conditions under counterfactual settings, we benchmark the current regulation design with complexity-tailored publicity requirements, and find that adjustments to publicity requirements could provide savings of 2 percent of spending, or $104 million annually./nOne of the main roles of the government involves enacting and enforcing regulation aimed at curbing the undesired behavior of agents. In the third chapter, co-authored with Mushfiq Mobarak, we study the consequences of deploying enforcement activities over illegal activities in local markets in Chile. The paper grapples with a key real-world feature that is that regulated agents adapt to circumvent enforcement. We present and test a model of enforcement with learning and adaptation by auditing vendors selling illegal fish in Chile in a randomized controlled trial and tracking them daily using mystery shoppers. Leveraging experimental variation on the frequency and predictability of enforcement, we can test the model's predictions and find that conducting audits on a predictable schedule and (counter-intuitively) at high frequency is less effective, as agents learn to take advantage of loopholes. A consumer information campaign proves to be almost as cost-effective and curbing illegal sales and obviates the need for complex monitoring and policing. The Chilean government subsequently chooses to scale up this campaign.

Advisor: Tadelis, Steven
The Autorickshaw Meter as Exemplar: Measurement, Commercial Publics, and Technological Infrastructures of Service in New Delhi

This dissertation takes up the autorickshaw meter – a government mandated and regulated fare meter for small, for-hire, three-wheeled commercial passenger vehicles – as an instrument through which to analyse configurations of commerce, service, labor, space, mobility, civility, aesthetics, technology, infrastructure, and regulation in New Delhi, India. If there is a primary logic through which the meter inflects these configurations, it is one of transaction, where the meter manifests its own material and social poetics of the substance and mediation of, and forms of participation in transactions, as well as inflecting mobility as their context, medium, and product. The meter itself is a simple device, and as such it emerges as an object of interest in its embedding within and entanglement with other structures that inform the shape of the city and relations within it. The dissertation is therefore organised to bring forward concrete abstractions of these entanglements. In a manner of speaking, the meter works as a miniaturization of the city which is too large, too heterogenous, and too full to apprehend or even index as a totality, where the dimensional reduction of the city produces, as Claude Levi-Strauss argued, perspective as an object. In recent times, the place of the meter has been complicated by the emergence of transport network firms and their commercial deployment of apps which in various ways mimic, complement, or displace meters. The implications of these developments as mediated through autorickshaws are complex, implicating reconfigurations of broad transport ecologies as well as giving rise to interesecting, overlaid, interrupting regimes of mobility and the spatial ontologies which undergird them. In the broadest frame, however, the autorickshaw meter and its relation to the app concern the material, technological, and social articulation of publics as structured by relations of equality, service understood through architectures of hierarchy, and how to understand rationales of service as a form of civility. In this context, I take up enclosure as a distributed theme, touching on both questions of framing the autorickhaw meter as object as well methodological questions the meter and its forms, formats, and contexts pose to ethnography.

Advisor: Cohen, Lawrence
Optical Beamforming Techniques for Solid-State Automotive LIDAR

The advent of new products in advanced driver assistance systems, virtual reality headsets, robotics, and biometrics has led to increasing demand for high resolution 3D depth maps. LIDAR (Light Detection and Ranging) has emerged as a strong candidate sensor to supply these applications with depth maps of the environment. In fact, LIDAR is already used as a primary sensor in experimental self-driving vehicles, since it provides high-resolution 3D images that existing RADAR solutions do not. However, the reliability and cost of these automotive LIDAR sensors has precluded their use in high-volume mainstream applications./nThis thesis explores and demonstrates beamsteering architectures that significantly reduce the size, weight, power and cost of LIDAR sensors. In particular, we focus on designs which achieve the high-volume, reliability, and resolution that automotive applications demand. We begin with an overview of existing LIDAR sensor architectures, and show that the key to improving cost and scalability is switching from traditional mechanical beam-steering to solid-state beam-steering using silicon photonic platforms. We then model and analyze the performance of different solid-state beam steering choices in the context of automotive applications, and arrive at a design for a thermal optical phased array. This thesis then outlines silicon implementation results from from the first 3D integrated the LIDAR SoC based on the aforementioned thermal optical phased array design. Next, we analyze several key issues that prevent this prototype from scaling to more demanding specifications, and propose a new beamsteering architecture based on focal-plane arrays which circumvents these fundamental issues. Finally, the models and automated electronic-photonic design methodologies developed in this work culminate in the design of a scalable monolithically integrated focal-plane array transmitter in a zero-change 45nm SOI CMOS process.

Advisor: Stojanovic, Vladimir
Model Minority: Black Sea Germans, Nazi Germany, and the Soviet Union (1917-1991)

My dissertation examines the historical experience of Black Sea Germans, a rural group from Sothern Ukraine, to understand the role of ethnic minorities in the development of the Soviet Union. The first German settlers arrived in Ukraine during the reign of Catherine the Great, creating a network of agricultural villages on the coast of the Black Sea. After the Russian Revolution, the community bore the brunt of Bolshevik policies before falling under the Nazi occupation in the summer of 1941. The members of the group were evacuated to Germany in the winter of 1943/44, repatriated after the war by the victorious Red Army, and promptly exiled to Central Asia to perform forced labor. My work reconstructs the historical trajectory of Black Sea Germans to understand how the experience of prolonged dislocation shaped the group’s identity and strategies that allowed it to adapt to rapidly changing conditions. Freed in the late 1950s, the Black Germans participated in the development campaign, known as the Virgin Lands Campaign, aimed at the modernization of Central Asia, particularly Kazakhstan. They took advantage of labor shortages in the region to fill critical jobs in agriculture and industries, which allowed for the economic stabilization of their community. Throughout the postwar period, the Black Sea Germans avoided most forms of political participation, focusing instead on preserving their identity and language. The development of the German press in Kazakhstan and the introduction of the German language to educational, cultural, and even religious institutions helped preserve German culture in the region. The politically passive, professionally successful, and culturally engaged character allowed the group to integrate into the social fabric of Soviet Kazakhstan and reinvent itself as the model minority of the republic.

Advisor: Connelly, John