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VoxelCompress: Learned Implicit Neural Compression of 3D Connectomics Data
No full textConnectomics, the study of comprehensive maps of neural connections in the brain, faces a significant computational bottleneck in data acquisition and storage. Current methods for imaging brain tissue at the required nanoscale resolution via serial section electron microscopy demand an estimated 10,000 years and require 1000 exabytes to image a complete human brain. This thesis introduces VoxelCompress, a deep learning-based compression framework that drastically reduces storage requirements while preserving high-fidelity reconstructions of volumetric electron microscopy (EM) data. Through extensive experiments, we demonstrate that VoxelCompress achieves a 2048× compression ratio and 99.95% overall compression, with efficiency far surpassing traditional lossless methods (only 1.68×) and accuracy exceeding state-of-the-art learned approaches (PSNR 38+ dB). Notably, VoxelCompress is the first generalizable model that does not require retraining between volumes, making its incorporation into existing imaging pipelines highly practical. Additionally, we show that denoising the input data significantly enhances compression performance—improving the peak signal-to-noise ratio (PSNR) by 6.64 dB and enabling a reduction in model depth from six layers to five without compromising reconstruction quality.Computer Scienc
Essays on Early Education and Care Systems and Processes
No full textIn the three papers of this dissertation, I use data from a large study conducted in Massachusetts and regression-based approaches to analyze both access and quality in diverse early education and care (EEC) settings serving preschool-age children. In each of the papers, I include a broader range of EEC setting types than is common in prior literature (i.e., community center, Head Start, licensed family child care, and public school settings) and select measurement approaches that complement and extend those used in previous work, opening new avenues for understanding children’s opportunities and development in the context of EEC systems and settings.
In the first paper, I focus on a key component of EEC access: the availability of EEC near young children’s residences. I examine variation in EEC availability by neighborhood characteristics and explore the consequences of those patterns for families’ use of EEC. I find that young children residing in less densely populated areas and in areas with moderate socioeconomic opportunity tend to have less EEC available nearby than those living in other areas. I also find that, among families who selected group EEC for their children, children with more limited availability near their residences tend to have longer commutes to their providers.
The second and third papers of the dissertation consider the quality of the EEC settings children attend. In the second paper, I explore children’s multifaceted skill development during the kindergarten transition and the intersection between their skill development and prekindergarten process quality. I first examine child-level dynamics in skill development, analyzing cross-domain associations between children’s prekindergarten skills and their residual skill gains from prekindergarten to kindergarten in five areas: social competence, self-regulation, language, early math, and early reading. I find that children’s self-regulation, language, and early math skills are interconnected from prekindergarten to kindergarten, whereas children’s social and early reading skills are largely unassociated with the other assessed domains. I then turn to the setting level, analyzing associations between a fine-grained observational measure of prekindergarten process quality and children’s residual skill gains in the same five areas. I find few links between process quality and children’s later skills.
In the third paper, I explore a hypothesized predictor of process quality: early educator burnout. I first validate the internal structure of a widely used burnout measure in a sample of early educators working in a range of EEC setting types. I then use the measure to describe burnout levels among early educators, finding that burnout symptoms are on average infrequent. Finally, I examine associations between educator burnout and process quality in EEC settings and find few links.Educatio
Graph Embeddings for Harvard Widener Library Data
No full textIn this project, I consider complications with retrieval of resources in a database, particularly library entries and a catalog, and consider how graph machine learning can aid in that retrieval pro- cess. Typical retrieval systems are exclusively text-based. This means that they will rely on natural language models only when making determinations about which resources might be relevant for the user. Natural language data is indispensable and at the core of how search engines operate. One can embed the query and all entries in a coordinate space and then find the closest entries based on some distance metric to get the most relevant search results. However, limiting the model to just this natural language data is letting go to waste one of the most powerful tools for understanding the relationships between entries: keywords.
By including keywords in the model, we can understand the hierarchical nature of the relationships between entries and keywords and among the keywords themselves, and this gives us additional information about the extent to which entries might be related when the text might be deceiving at face value. This introduces a new complication, however, as the keywords and entries are related in a graph structure. The keywords and entries are nodes and relations indicate the connection between an entry and a keyword that describes that entry. Since computers cannot look at a graph and make sense of it like humans can, we must use graph machine learning techniques to embed the graph into a coordinate space. Then, we can use the coordinates to make conclusions about the relatedness of entries and the relevance of search results. This gives use a new way to approach retrieval and can be paired with the common natural language model approach to enhance retrieval and return more relevant results to the user.Computer Scienc
Proof of Life: The Biopolitics of Visual Media
No full textThis study outlines a genealogy of media that claim to prove something about human life. It draws on archival and historiographical research to analyze interactions between photography, the history of statistics, activist art and video, public health crises, and digital media. Across a series of case studies spanning the twentieth and twenty-first centuries, the dissertation argues that visual media emerges as a biopolitical tool for governing populations in tandem with new forms of biometric surveillance that work to structure space and movement. The chapters examine the relationship between photography, social reform, and statistics; the role of aesthetics in AIDS activist media, art, and public health campaigns; the history of biosurveillance in relation to the cultural and political imaginaries that emerged after the completion of the Human Genome Project; and the role of contemporary artists in understanding how the body is reconceptualized—or reformatted—as an object for the extraction of data within regimes of “surveillance capitalism.” The concluding chapter looks to early experiments with responsive environments in artificial intelligence research to contextualize productive encounters between statistical science, cybernetics, architectural design, and organizational management in the mid-twentieth century that implemented multimedia surveillance as a mechanism of control—encounters that continue to influence the ideological aims and technical operations of contemporary therapeutic and assistive digital tools. By focusing on the diagnostic aspect of biometric capture and visual surveillance in relation to risk management, the dissertation frames media as an unexpected technique and tool of biopolitical governance. Across chapters, Proof of Life: The Biopolitics of Visual Media introduces the concept of "biosurveillance media"—media forms designed to surveil, track, and quantify the body. The dissertation contributes to a critical body of scholarship in film and media studies and the history of technology that unravels the fraught relationship between media technologies, political agency, and the governance of human life.Film and Visual Studie
The Un-Mattering of People: The Present and Near-Future of Surveillance Capitalism and the Fate of Care in Healthcare
No full textThe encroachment of surveillance capitalism into healthcare takes place as healthcare becomes increasingly industrialized. The industrialization and datafication of healthcare create a receptive environment for firms that concentrate the means of computation—companies that have grown thanks to technologies of surveillance and remote behavioral actuation.
In healthcare, Big Tech finds a massive business opportunity as it becomes fundamental to infrastructure and an unavoidable mediator of medical services. Also, Big Tech can now capture the missing piece in its quest to harvest, control, and use the complete human experience as raw material for their business interests. Central to this encroachment is the misguided notion that the problems of care are problems of information. Big Tech is best situated to address problems of information using powerful data platforms and artificial intelligence systems. Care, a practice by which a human sets out to solve the problematic situation of another human, is replaced by the processing of their data. Care becomes depersonalized, dehumanized, disembodied.
Evidently, advances in information technology can make significant contributions to the project of offering careful and kind healthcare to every person. And yet, the realization of this vision would require outlawing Big Tech’s parasitic practices as they commodify humans to advance these firms’ anti-human and anti-democratic project of domination. Abolishing surveillance capitalism and its contribution to corrupting the mission of healthcare may help ensure that information technologies can be harnessed to advance the core mission of healthcare: the care of people.Author's Origina
The Impact of Concussion History on Cognitive and Emotional Depression and Post-Concussive Symptoms in Adolescent Athletes
No full textConcussions pose serious risks to those who incur them, particularly in
adolescents. The developmental milestones of this cohort expose them to prolonged risks
of negative physiological and psychological symptoms. This study explored the
relationship between concussion history and the subdomains of cognitive and emotional
symptoms of the Post-Concussive Symptom Scale (PCSS) and Mood and Feelings
Questionnaire (MFQ) measures in an adolescent athlete population with a hypothesis of
significant differences in measure scores between prior concussion history and no prior
concussion history groups. Participants (N = 155) between the ages of 13-18 years were
analyzed, with (n = 49) reporting a history of prior concussion and (n = 106) reporting no
history of prior concussion. Higher PCSS item 13 scores were observed in participants
with prior concussion history through descriptive statistics (M = 0.78, SD = 1.46), when
compared to participants with no such history (M = 0.34, SD = 0.88). Additional
significant differences for this variable were detected through ANOVA F (1, 153) = 5.29,
p = .023. Effect size estimates demonstrated a small effect, with eta-squared = .033 and
omega-squared = .027. Variability was present in the precision of estimates as measured
by confidence intervals.
A multivariate analysis of variance indicated no further significant differences in
other cognitive or emotional subdomain variables across groups F (18, 136) = 1.56, p =
.080. Variability in the dataset was observed via Levene’s Test of Equality of Variances,
with unequal variances found for PCSS 12, PCSS 13, and MFQ 22 items.
Findings suggest a modest relationship between concussion history and cognitive
symptom severity in PCSS 13 scores. There was no clear evidence of broader interactions
on other cognitive or emotional symptoms. Additional research is needed to investigate
emotional and cognitive symptom severity and concussion history relationships without
the methodological concerns of small effect sizes and unequal variances present in this
study due to the limitations of secondary analysis.Extension Studie
The Geopolitics of Surveillance Capitalism
No full textSurveillance capitalism is a new form of capitalism that turns human behavior into data to be tracked, analyzed, and monetized. However, this narrow framing obscures the deeper architecture that allows surveillance capitalism to thrive. Surveillance capitalism is not just a business model. It is a geopolitical system with institutional scaffolding. It is grounded in regulation (or lack of), legitimized by economic theory, promoted by trade rules, and protected by powerful countries. Its sustainability depends on more than market incentives; it is built on a distributed architecture of norms, institutions, actors, and governance failures.
At its core, surveillance capitalism is an extractive political economy built on the systematic capture and monetization of human experience. As Shoshana Zuboff argues, this system represents an “epistemic coup,” in which corporations unilaterally assert ownership over behavioral data, undermining both privacy and democratic legitimacy. This is not only the privatization of information, it is also the expropriation of the very condition of self-knowledge and collective autonomy. This coup did not occur by accident. It was made possible by deliberate political choices, neoliberal market ideologies, legal loopholes, and the strategic retreat of the democratic state (Zuboff 2022a).
The surveillance capitalist order extends far beyond tech companies. It is built on a set of foundational assumptions about markets, innovation, and governance. It draws on economic theories that treat data as a neutral input and surveillance as the price of personalization. It is reinforced by legal doctrines, from trade secret protections to arbitration rules, that prioritize corporate control over democratic oversight. And it is institutionalized through international organizations, development finance institutions, and standard-setting bodies that diffuse and normalize extractive data practices as a form of modernity and progress. While the United States is often seen as the chief architect and promoter of surveillance capitalism, the system it anchors is far from national. Regional and bilateral trade agreements protect cross-border data flows while restricting the ability of other governments to regulate. Development institutions promote digital infrastructure projects that deepen surveillance logics in the Global South, often under the banner of inclusion. Multilateral forums and technical standards bodies entrench the norms of “trustworthy AI” and “data free flows with trust,” offering legitimacy without transparency. All these are geopolitical strategies embedded in regulation, code, and economics.
This paper takes a bird’s-eye view of the global surveillance eco-
system. It maps the institutional foundations and geopolitical dy-
namics that sustain it. It traces the actors, alliances, and narratives
that normalize mass corporate surveillance and promote the glob-
al surveillance capitalist economy. It goes beyond a Big Tech cri-
tique and traces how power is produced, distributed, and enforced
across this global order. Surveillance capitalism is a geopolitical
system, and dismantling it requires more than privacy reforms or
antitrust action. It requires structural transformation of the polit-
ical, legal, and epistemic arrangements that have enabled it. This
paper aims to lay the groundwork for coordinated action.Author's Origina
Medieval and Early Modern European, African and Asian ivories seen through the Data Lens
No full textIvories of different natures are one of the oldest materials of artistic expression, and they have been used widely through space and time. The purpose of this article is twofold: on the one hand, to offer a data driven analysis of Medieval and Early Modern ivories in Europe, Africa and Asia (ca. 1000 to 1600); on the other hand, to offer a critical perspective on the proposed query method itself. Nine museums with 2123 objects have been chosen for this analysis, based on the availability of a query endpoint. The proposed method has clear advantages and disadvantages. To the advantages belong the possibility of researching through several museum holdings at the same time (once the dataset is modelled), to query museum object data on view and on deposit all together, to be potentially able to provide insights into a given category from a very broad perspective, but also to search for unusual objects. To the disadvantages belong the fact that data is changeable, and that the selection of the museums is driven by the availability of a query structure. Therefore, the choice of the museums is also problematic, if one wants to address an international comparison. Furthermore, each museum offered data only in specific fields, which adds complexity to an overall query.Version of Recor
Investigations of bacterial natural products in microbe-microbe interactions
No full textBacteria are prolific producers of natural products, diverse secondary metabolites that can play crucial roles in their survival, interactions, and environmental adaptation. While many natural products have been harnessed to treat human diseases, their ecological functions in natural environments are often overlooked and poorly understood. In complex microbial communities encompassing bacteria, fungi, and viruses, natural products shape microbial interactions and ecosystem dynamics, with potential implications for host homeostasis. An understanding of their functions and downstream impact may inform new strategies for manipulating microbial communities in medical, agricultural, and environmental applications. This dissertation documents our efforts to advance our understanding of the ecological roles of colibactin, a genotoxin produced by strains of Escherichia coli found in the human gut. It also reveals a newly discovered function for aryl polyenes, a highly abundant class of Gram-negative bacterial natural products. These investigations have revealed unprecedented roles for these compounds and their influence on the viruses that infect bacteria (bacteriophages), offering new perspectives on the chemical language that shapes microbial communities.Chemistry and Chemical Biolog