Cornell Theses and Dissertations
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The theses and dissertations of graduate students at Cornell University have been deposited in Cornell's institutional repository (eCommons) since about 2004. This collection also includes a few earlier Cornell theses.
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Item TOWARDS EFFICIENT AND SCALABLE MACHINE LEARNING FOR FUTURE NEURAL INTERFACESZhu, Bingzhao (2023-08)Closed-loop approaches in systems neuroscience and therapeutic stimulation have the potential to revolutionize our understanding of the brain and develop novel neuromodulation therapies for restoring lost functions. Neural interfaceswith capabilities such as multi-channel neural recording, on-site signal processing, rapid symptom detection, and closed-loop stimulation are crucial for enabling these innovative treatments. However, current closed-loop neural interfaces are limited by their simplicity and lack of sufficient on-chip processing and intelligence. This dissertation focuses on the development of next-generation neural decoders for closed-loop neural interfaces, utilizing on-chip machine learning to detect and suppress symptoms of neurological disorders. These neural decoders offer high versatility, low power consumption, minimal on-chip area, and robustness against neural signal fluctuations. Chapter 2 explores migraine state classification using somatosensory evoked potentials, an emerging application for neural interfaces. In Chapter 3, we introduce a resource-efficient oblique tree model that enables low-power, memory-efficient classifiers for realtime neurological disease detection and motor decoding. Chapter 4 presents a novel Tree in Tree decision graph model with applicability beyond neural data, demonstrating success in general tabular prediction tasks. In Chapter 5, we propose an adaptive machine learning-based decoder to compensate for fluctuations in neural signals during test time. The dissertation concludes with a discussion of future research directions for on-chip neural decoders.
Item CREATING AN EXPERIENCE SHARING COMMUNITY IN LEARNING: ENVIRONMENTS, BEHAVIOR, AND LEARNING EXPERIENCEZhu, Wangda (2023-08)In the juncture of virtual and physical learning environments, Experience Sharing Community (ESC) supports learners to create course related posts based on their experience in physical environments, share posts in virtual environments, and interact with peers and instructors. The ESC, via technology and instruction designs, provides students with a place to create, interact, and reflect, influencing diverse learning experience. The idea of ESC is not brand new, similar topics of ESC were explored by studies related to social media use in education for two decades. While there is still a lack of a systematic understanding of how technology and instruction together contribute to learner behavior and experience. This dissertation mainly includes two projects. Study#1 investigates creating an ESC via Instagram in an online learning environment during the Covid-19 pandemic. In a large online course, Introduction to Environmental Psychology, 110 voluntary participants posted photos of their surroundings that were related to the course on Instagram every week. Mixed methods including survey experiment, interview and network analysis were applied to understand their behavior and experience in this community, and how key features of Instagram influenced their experience. The main environments’ features to afford interaction, behaviors including interact, post, and reflect, experience including social presence, cognitive presence, sense of place and sense of belonging, and the relationship between environments, behaviors and experience were identified and explored. While social media such as Instagram was an effective tool for building the ESC, they were not designed for educational settings, and many of their features had to be adapted to better support the ESC. After summarizing the lessons learned from Study#1, I designed and developed my own web application to provide a more tailored experience for students. In Study#2, 114 voluntary participants followed the similar instruction as Study#1 and posted photos on the new app in the same course in a traditional learning setting after the pandemic. This project received positive feedback in terms of engagement, sense of place, and knowledge understanding. Mixed methods including design-based research, interview, and log analysis were applied to further understand how both technology and instruction design influenced student behavior and experience in this community. Based on these two projects, I summarized a framework of conducting longitudinal study to understand participant experience using web applications, regarding its research design and technology needs. This summary extends the scope of the dissertation beyond the ESC, to inspire research methodology development such as Ecological Momentary Assessment. Overall, this dissertation is a unique and valuable addition to the educational landscape, on “what is ESC” and “how to create ESC”, providing students with an opportunity to engage with their peers and expand their knowledge in a dynamic and interactive way. The project also highlights the potential of technology to support and enhance traditional classroom settings, demonstrating the power of innovation and creativity in the pursuit of educational excellence. This learning community can be expanded to broader class settings in the future, including across classes in design fields such as Human-Centered Design, Architecture, and Landscape Architecture. Students across different disciplines can benefit from sharing their knowledge and experience in the community. In addition, the open-sourced technology framework of longitudinal study via web applications including study design, data collection, data analysis and presentation for stakeholders of researchers and instructors can facilitate the research innovation beyond educational technology field.Item RADIAL PROJECTIONS, CONVEX FEASIBILITY PROBLEMS AND MARGIN MAXIMIZATIONZhou, Song (2023-08)This work comprises two parts. Part I focuses on the convex feasibility problem (finding or approximating a point in the intersection of finitely many closed convex sets). We avoid the need for orthogonal projections by using radial projections, introduced by Renegar. The main requirement is that an interior point is known in each of the sets considered. By developing Renegar’s theory, we obtain a family of radial projection-based algorithms for the convex feasibility problem which recover the linear convergence rates of orthogonal projection-based methods. Through studying different assumptions on the emptiness of the interior of the intersection set in the convex feasibility problem, we also exhibit how radial projections can be applied to solve constrained optimization problems when certain conditions are met.Part II can be seen as an application of the theory of radial projections developed in Part I. Here, we revisit the notion of maximal-margin classifiers, from around 2000, but now from a general perspective – the intersections of generic closed convex cones, not just half-spaces (i.e., the perceptron). This requires extending concepts and establishing more general theory of the margin function, which is achieved by applying and refining the results in Part I in the conic case. Even more interestingly, we are led to the first Õ(1/ε) first-order method for approximating, within relative error ε, the margin-maximizer of the intersection cone. Previous results, only in the case of the perceptron, were O(1/ε²), making our result a notable improvement even in the most basic of cases.Item Phenomenal Time and the Metaphysics of the MindZhou, Lyu (2023-08)My dissertation concerns phenomenal time, i.e. how time appears to us subjectively. The key theme of my dissertation is that thinking about how time appears to us subjectively helps us answer many classic metaphysical questions about the nature of time and human consciousness. Chapter I argues that our mind imposes time upon our consciousness as its essential constitutive structure: in Immanuel Kant’s (1781/1787/1996) language, phenomenal time is an a priori form of our consciousness. I argue that our consciousness is necessarily temporal, and this necessity has an important revelation: our mind does not perceive time, because perception is a causal process, and yet no causal mechanism, due to the contingency of its operation, can ensure that our consciousness is necessarily temporal. Instead I propose that our mind imposes time upon our consciousness as its essential constitutive structure. My proposal leaves open the question of whether the world as it is independent of our conscious experience is temporal at all. Chapter II argues that given how time appears to us subjectively, our consciousness cannot be purely physical. Our immediate present consciousness – what William James (1890/1950) calls the specious present – has a (non-instantaneous) duration. I argue that this specious present is a phenomenally extended unit of consciousness that is mereologically inverted in the sense that the parts depend on the whole: the shorter constituent durations of the specious present cannot exist except as parts of the whole specious present. Yet what is physical – a physical object, process, or functional system – does not have this peculiar property of mereological inversion: instead, any physical whole depends on its parts. Therefore, given such a structural discrepancy, our specious present cannot be identical to, or purely constituted by, what is physical. Chapter III defends the methodology of conscientious introspection employed in the preceding chapters. After clarifying Uriah Kriegel’s (2015) helpful distinction between the reliability and the potency of introspection, I argue that a full appreciation of this distinction has important revelations: one is that many of the pessimistic concerns with introspection threaten not so much the reliability as the potency of introspection; and another is that, once the two notions are disentangled, the reliability of conscientious introspection emerges as eminently defensible.Item Experimental and analytical techniques for studying mechanotransduction in articular cartilageZheng, Jingyang (2023-08)Tissues are often complex heterogeneous systems, where individual cells coordinate responses to internal and external stimuli. To fully understand cell function in such environments, it is critical to connect the behavior of individual cells with the full tissue-scale response. Articular cartilage is one such system where the complex extracellular matrix and heterogeneous cell responses make it difficult to understand how chondrocytes respond to injury-inducing strain. In this thesis I will explore the methods I developed to map the spatiotemporal behaviors of chondrocytes in articular cartilage after impact. These methods combine microscopy techniques with large scale data analysis, making use of a custom-programmed decision tree algorithm, supervised time series classifiers, and unsupervised clustering via a variational autoencoder to identify and categorize cell phenotypes. Time series data collected from thousands of chondrocytes \textit{in situ} during and after impact allow me to probe responses through the lenses of calcium signaling, mitochondrial polarity, and nuclear membrane permeability. This thesis serves to outline the experimental and analytical methods developed to probe cellular response to external stimuli. While the focus is on method development, I will touch on some of the biological implications of impact on articular cartilage, and identify questions and hypotheses generated through the experiments conducted for this work.Item Single-molecule, single-cell imaging of stress response systems in Gram-negative bacteriaZhang, Wenyao (2023-08)The study of bacterial stress response systems is an important area of research with wide-ranging implications, from understanding the basic bacterial physiology to developing new antimicrobial treatments. This dissertation presents my recent efforts to understand how Gram-negative bacteria adapt to environmental stimuli using live cell fluorescence imaging, genetic engineering, bulk biochemical/cellular assays, and microfluidic mechanical manipulations. Employing these methods, I, in collaboration with others, investigated three types of stress response systems associated with the Gram-negative bacteria cell envelope: multidrug efflux pumps (MEPs), two-components signal transduction systems (TCSs), and metal homeostasis.Item PHYSICS-BASED DEEP LEARNING METHODS FOR MAGNETIC RESONANCE DATA SAMPLING, IMAGE RECONSTRUCTION AND QUANTITATIVE SUSCEPTIBILITY MAPPINGZhang, Jinwei (2023-08)Improved magnetic resonance (MR) data sampling, under-sampled image reconstruction, and dipole inversion can be achieved using physics-based deep learning methods. These methods leverage the physical models of MR imaging processes to improve the quality and accuracy of MR images. One approach to improving MR data sampling involves optimizing the k-space under-sampling pattern from fully sampled k-space dataset. A pioneering work is called LOUPE [1] which updates the probabilistic density function used to generate binary k-space sampling patterns, and uses a sigmoid approximation to sample from the learned density function. In addition, physics-based deep learning methods can be used for under-sampled image reconstruction by incorporating the imaging physical models into the deep learning architectures. Pioneering works, such as VarNet [2] and MoDL [3], have incorporated physical models by unrolling iterative reconstruction algorithms with deep learning-based regularizers. Moreover, physics-based deep learning has also improved the ill-posed problem of dipole inversion used to extract tissue susceptibility from magnetic field data. QSMnet [4] and DeepQSM [5] are two pioneering works that have tackled this problem by incorporating physical models either into the training loss function or through simulating the training dataset. This thesis contributes to physics-based deep learning for MRI by: 1) improving LOUPE using a straight-through (ST) estimator and extending the improved LOUPE to multi-echo and multi-contrast scenarios; 2) developing pulse sequence for prospective multi-echo gradient echo under-sampling and customized efficient multi-contrast sampling; 3) designing image reconstruction network architectures aggregating multi-echo and multi-contrast image features; 4) utilizing physical models into the loss function for test time fine-tuning to improve generalization; 5) solving Bayesian posterior estimation of dipole inversion problem using Variational Inference (VI) incorporating physical models.Item SELF-ENHANCEMENT, ATTRIBUTION, AND CULTURAL COGNITION: UNPACK DIFFERENT APPROACHES TO UNDERSTANDING ATTRIBUTIONAL JUDGMENTS ACROSS CULTURESZhang, Congcong (2023-08)Achievement attribution, which refers to the pattern of how people attribute their achievement outcome to specific causes, has been extensively studied in recent years. However, the cultural differences in making attribution and the underlying mechanisms of explaining attributional judgments in cross-cultural contexts still remain unclear. This dissertation explores multiple theoretical approaches to enhance our understanding of the complexities of attribution patterns observed within and across cultures. The first study (i.e., the meta-analysis in Chapter 2) adopted a meta-analytic approach to assessing the results of previous self-enhancement studies and explored potential moderators to explain variations found in existing results. The findings suggested that methodological factors, including the valence of events, explicit (vs. implicit) measures, the role of respondents as an actor (vs. an observer), the benchmark for comparison and the types of comparison (direct vs. indirect), can affect conclusions in self-enhancement studies across cultures. The second study (i.e., the experimental study in Chapter 3) further explored the mechanisms of predicting self-enhancing attribution between the East and the West. In particular, the role of self-esteem and self-concept and the mediated pathways through modesty and face concern were examined. We found that: a) first, explicit self-esteem, dialectic self and interdependent self-construal exerted a great influence on achievement attribution; b) second, modesty and face concern were two competing forces in explaining the influence of interdependent self-construal on self-enhancing attribution; c) third, the salience of the proposed mechanisms varied across cultures. And interestingly, the proposed mechanisms predicted the self-enhancing attribution in success conditions only (in comparison to failure conditions). In Chapter 4, I analyzed the multinational data from two experimental studies about achievement attribution to test the competing hypotheses informed by three theoretical approaches (i.e., universal self-enhancement approach, relative self-enhancement approach and cultural cognition approach). Results indicated that both self-enhancing motivations and cognitive processes, along with measurement instruments can affect what we can observe. Implications and future directions for studying attributional judgments in cross-cultural contexts were discussed in Chapter 5.Item SPIRITED MOTIVATIONS, VIRTUE, & THE GOOD: THE INTERDEPENDENCE OF SPIRITED MOTIVATIONS AND RATIONAL BELIEFS IN PLATO’S MORAL PSYCHOLOGYZgurich, Brianna (2023-08)Confidence, courage, and shame are typically agreed upon by scholars to be what Plato refers to in his middle dialogues as spirited (thumoeidic) motivations; i.e., strong emotional responses that are not themselves rational (i.e., not calculating about what is best), nor appetitive (i.e., about bodily objects of desire such as food, drink, and sex). This dissertation focuses on courage and shame in particular. While courage finds itself as one of Plato’s four cardinal virtues (along with wisdom, moderation, and justice), shame, a particularly strong passion that can result in either virtuous or non-virtuous responses, is not quite so easy to place. Further the roles of these two motivations for virtuous action, along with their connection to reason, are not fully appreciated by scholars. I argue that we can use the psychology of Plato's final dialogue the Laws, and especially the famous "puppet passage", to understand what these “spirited motivations”. I have found that these motivations are especially closely linked to reason—not only in following reason but also in enabling reason’s best condition: wisdom. Along the way, I address some of the early and middle dialogues, arguing that the speech of the laws in the Crito appeals to shame (before those who share one’s conception of the good), and that such shame is crucial to Socrates' elenchus; however, whether the elenchus succeeds at getting the refuted party to seek knowledge or to avoid the shame by bringing down others (as in the Apology and also the Laches) depends on the person’s conception of the good. Further, I argue that the myth of the Protagoras depicts shame’s role as reason-dependent and, for that reason, is conducive to political community. Finally, I argue that courage in the Republic, understood as belief-preservation, is crucial for the development of reason’s best condition: wisdom. So, using the Laws as a framework, I argue that we can recognize the interdependence of courage and shame with rational beliefs for virtuous action, answer questions that arise from some of the early and middle Platonic dialogues, as well as see a consistent, complex, and unique moral psychology emerge from Plato’s corpus.Item LANGUAGE–BASED TECHNIQUES FOR BUILDING TIMING CHANNEL SECURE HARDWARE–SOFTWARE SYSTEMSZagieboylo, Drew (2023-08)We rely on a deep stack of abstractions to efficiently build software applications without having to completely understand the nuance of language run- times, operating systems, and processor architectures. Each layer in the stack relies on the guarantees of the layer below, with all software relying on the functionality provided by the hardware on which it executes. Similarly, when we build secure software, we define security in terms of high level application policies and rely on a stack of abstractions to enforce those policies. Therefore, all of software security relies on the guarantees provided by processor hardware. However, those guarantees offer less protection than we have traditionally assumed, and real processor implementations routinely exhibit vulnerabilities that undermine traditional assumptions about hardware behavior. Modern processors incorporate a host of optimizations to execute software as quickly and efficiently as possible; unfortunately, these optimizations are at the root of some serious security weaknesses. In particular, researchers have recently discovered easily exploitable timing-channel vulnerabilities that arise due to processor speculation, like Spectre, Meltdown, and the many variants that have since been uncovered. Concerningly, these vulnerabilities are not the result of cutting-edge, untested optimizations; they are fundamental to the de- signs of almost all processors in the last 20 years. The existence of these vulnerabilities highlights the need for a well-defined contract between software and hardware that does not allow the hardware to leak software’s secrets arbitrarily, especially via timing channels. Furthermore, we need tools to enable the construction and verification of secure processors that adhere to these new contracts. As functional processor correctness is al- ready a difficult verification problem, we likely need new approaches to prove processor security. This dissertation addresses the above concerns by applying Information Flow Control (IFC) to both the hardware–software interface and to Hardware Description Languages (HDL) themselves. By using IFC as the de facto language of security, we can define a hardware–software contract capable of providing timing-channel security without exposing extraneous details about processor internals. Intuitively, using IFC as a tool to then build processors also enables proving that real processor implementations refine this IFC contract. This dissertation also addresses the problem of constructing correct processors by introducing a high-level HDL that targets the design of efficient processor pipelines. By raising the abstraction of hardware design, we can more easily connect the implementation’s semantics to the hardware–software contract. We can also reason statically about complex optimizations such as speculation by providing abstractions that generate correct circuitry by construction. We hope that future processors and interfaces are designed with timing- channel security in mind, and that these new abstractions will percolate back up the software stack to make timing-channel security available and efficient for all applications.