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Advancing Evidence-Based Maternity Care: Empirical Studies of Technologies, Policies, and Clinical Practices in the U.S. and Abroad
No full textWhile maternal and newborn health (MNH) outcomes have improved globally over the past couple decades, progress has been slow or stagnant in many low- and lower-middle-income settings. In Kenya, the maternal mortality rate remains well over five times the United Nations’ Sustainable Development Goal and high rates of severe maternal and neonatal morbidity persist. Meanwhile, the United States trails almost all high-income nations with respect to MNH care, including variable family planning support across states and minimal recent declines, if not increases, in rates of adverse outcomes like maternal and perinatal mortality. Amidst this backdrop, global maternity care utilization has been on the rise, with growing use of services ranging from patient support tools to contraception to advanced imaging. Accordingly, this dissertation expands the evidence base on 1) a patient-facing digital health tool implemented in health facilities across Kenya; 2) recent Medicaid payment policies regarding provision of immediate postpartum long-acting reversible contraception (LARC); and 3) the utility of electronic-health-record- (EHR) and machine-learning- (ML)-based risk stratification models to identify and guide management for individuals at high risk of adverse outcomes like late stillbirth.
In Chapter 1, jointly conducted with Wei Chang, Sharon Akinyi, Sarah Little, Catherine Gakii, John Mungai, Cynthia Kahumbura, Anneka Wickramanayake, Sathyanath Rajasekharan, Jessica Cohen, and Margaret McConnell, I describe a parallel arm cluster randomized controlled trial carried out in 40 health facilities in Kenya to evaluate the impact of a low-cost, digital health platform called PROMPTS. Developed by Jacaranda Health, a leading MNH nonprofit, PROMPTS consists of informational messages, appointment reminders, and a two-way clinical helpdesk. Using longitudinal surveys of participants, we find that individuals recruited from facilities offering PROMPTS exhibited modest but consistent improvements across the pregnancy-postpartum care continuum, including in knowledge, preparedness, routine and danger sign care seeking, newborn care, and postpartum care content. We identify notable advances in the postpartum setting, for both mothers and newborns, which has important implications for efforts to improve postpartum care quality in Kenya.
In Chapter 2, jointly conducted with Maria Steenland, Benjamin Sommers, and Jessica Cohen, I evaluate Medicaid payment policies in Georgia and New York aimed at expanding contraceptive choice through separate reimbursement of immediate postpartum LARC. Using statewide hospital discharge data from the Healthcare Cost and Utilization Project and an interrupted time series design, we find significant, post-policy increases in the provision of immediate postpartum LARC, with accompanying reductions in the rate of subsequent, short-interval birth. We also find coincident decreases in rates of immediate postpartum sterilization, suggesting some amount of substitution between highly effective contraceptive methods. In subgroup analyses of adolescent individuals, Hispanic individuals, and non-Hispanic Black individuals – all of whom have higher rates of unintended pregnancy – we identify larger than average increases in immediate postpartum LARC provision and more pronounced reductions in the rate of subsequent birth within 21 months. Ultimately, our findings suggest that the payment policies led to new use of LARC and likely some reduction in the rate of unintended pregnancy.
In Chapter 3, jointly conducted with Jessica Cohen and Mark Clapp, I describe the development of an ML-based risk stratification model to prospectively identify individuals at high risk of adverse perinatal outcomes. Using features readily available in the EHR of a large, Massachusetts-based health care system, we first demonstrate the improvement in risk stratification from supplementing traditional, clinical risk factors with additional clinical, geographic, and sociodemographic features. We then leverage model predictions to generate insights about utilization of outpatient antenatal fetal surveillance (AFS) and its association with rates of late stillbirth, across risk groups. We find that rates of AFS use increased with predicted risk, suggesting that providers conducted surveillance at least in part based on similar factors to our model. Finally, we prospectively identified a predictably high-risk set of pregnancies for which AFS was associated with a nearly 80% lower rate of late stillbirth, though – given our observational approach – we could not causally attribute the lower outcome rate to AFS. Descriptively, we find that high-predicted-risk individuals who did not receive AFS lived further from the hospital and got less prenatal care but had lower rates of nearly all traditional clinical risk factors, including at the end of pregnancy.Health Polic
Dangerous by Design: Distinct Patterns of Violence among Semi-State Terrorist Organizations
No full textSemi-State Terrorist Organizations (SESTOs) are armed groups that not only control territory but also govern civilian populations, blending militant violence with governance functions. Despite their rarity, SESTOs account for a disproportionate share of terrorist attacks and fatalities globally. Here we identify 24 SESTOs using explicit criteria applied to organizations in the Global Terrorism Database (1970–2020), constructing an organization-quarter panel to compare their violent activity against thousands of non-SESTOs. Fixed-effects regressions reveal that SESTOs sustain significantly higher attack frequencies and aggregate fatalities without systematically increasing per-attack lethality or targeting state actors disproportionately. Notably, SESTOs exhibit episodic, extreme bursts of violence. A Random Forest machine learning model trained solely on violent activity accurately distinguishes SESTOs from non-SESTOs, confirming their distinct operational profile. These findings suggest that governance capacity shapes SESTOs' sustained and intense violence, highlighting their outsized threat and the need for nuanced policy responses that consider their unique behavioral patterns.Author's Origina
Thicken the Balcony - A new model for Hong Kong old residential buildings redevelopment
No full text" We never see the existing as a problem. We look with positive eyes because there is an opportunity of doing more with what we already have." -- Lacaton & Vassal.
Hong Kong, as an innovative city, has been actively promoting urban development. However, a large number of residential buildings from the last century have been left behind in the urban renewal, gradually become an obstacle to urban development. These buildings are often in disrepair, their spatial environments have not adapted to the needs of modern life, and it creates many legal and property rights issues. It also negatively affect residents’ quality of life, making residents expand their private platforms without the permission of the government.
The old buildings in Hong Kong is hard to dismantled, and the narrow space does not allow a large number of transformations. Based on the extension idea of Grand Parc Apartment renovation, this thesis think about ways to regenerate old buildings beyond the simple extending through addition. Thus, this thesis attempts to propose a new balcony system based on the original site building, that continues the overflow expansion requirements of more outdoor and living space by residents. On the one hand, it cut out new voids from the building, creating an improved living environment. Meanwhile, it extends the balconies and transformed the single-function exterior wall into a thicker, programmatic space that offers more living and communal activities. By doing so, a new model is created to provide different degrees and levels of community, privacy, and public connection to become a brand-new social structure and opportunity of housing type, transforming an old residential building into a new dynamic community pattern that advances together with the city.Department of Architectur
ACCESSIBILITY AND REAL ESTATE PRICES IN MEXICO CITY: A HEDONIC APPROACH
No full textAccessibility—the ease of reaching destinations—is widely regarded as a key driver of real estate prices. Yet much of the literature limits its focus to a single destination type, coarse spatial units, and a single accessibility metric. This thesis addresses these limitations by estimating the impact of accessibility on housing prices in Mexico City through a hedonic price model. It draws on granular real estate data and incorporates destination-specific accessibility—covering jobs, health, education, recreation, gastronomy, public spaces, and retail—using both cumulative and gravity-based metrics across public and private transport modes. The findings reveal substantial variation in how accessibility influences housing prices, with positive, negative, and nonsignificant associations depending on destination type and transport mode. By jointly estimating multiple accessibility measures within a hedonic framework, the analysis offers a nuanced comparison of how residents value different forms of access, as capitalized into housing prices.Department of Urban Planning and Desig
Investigating Staphylococcus aureus Cell Envelope Enzymes for Antibiotic Discovery
No full textThe rise of antibiotic-resistant Staphylococcus aureus, particularly methicillin-resistant Staphylococcus aureus (MRSA), has created an urgent need for new antibacterial strategies. The bacterial cell envelope—comprising the peptidoglycan cell wall, membrane-bound enzymes, and teichoic acids—remains a validated but underexploited target space for antibiotic discovery. This thesis describes three complementary approaches to address antibiotic resistance by investigating S. aureus cell envelope enzymes.
The first approach focuses on discovering small-molecule inhibitors of FtsW, a highly conserved and essential peptidoglycan polymerase involved in septal cell wall synthesis. To identify FtsW inhibitors, we developed a time-resolved FRET (TR-FRET) assay capable of detecting polymerase activity in vitro. Screening a curated library of compounds lethal to S. aureus revealed a set of candidate inhibitors, including compounds that act through substrate competition. Biochemical validation and substrate displacement assays confirmed their activity and provided insights into the mechanism of inhibition.
The second approach centers on the identification and characterization of SpbR, a previously uncharacterized membrane protein discovered through transposon sequencing under teichoic acid inhibition conditions. SpbR modulates lipoteichoic acid (LTA) length and physically interacts with SpsB, the essential type I signal peptidase in S. aureus. Genetic and biochemical evidence shows that SpbR inhibits SpsB-mediated cleavage of LtaS, the LTA polymerase, resulting in extended LTA polymers. SpbR also partially inhibits cleavage of other canonical SpsB substrates, functioning as a general modulator of SpsB activity. To our knowledge, SpbR is the first described modulator of a bacterial type I signal peptidase.
The third approach involves structure-guided discovery of inhibitors targeting DltB, a membrane protein involved in D-alanylation of teichoic acids. While D-alanylation is not essential under normal conditions, it plays a key role in virulence and antimicrobial resistance. Virtual screening against the cryo-EM structure of DltB identified compounds that inhibit growth only in strains missing a membrane protein that is synthetically lethal with the Dlt pathway, but not in wild-type S. aureus. Genetic suppressor analysis and saturation mutagenesis revealed a previously uncharacterized binding site and provided insight into the mechanism of inhibition.
Together, these studies advance our understanding of S. aureus cell envelope biology and highlight diverse strategies for antibiotic development—through inhibition of essential enzymes, identification of modulators of envelope biogenesis, and targeting of non-essential enzymes to potentiate existing antibiotics.Chemistry and Chemical Biolog
The Afghanistan Quagmire: Comprehending the Challenges in the U.S. Nation-building Efforts (2001-2021)
No full textThe U.S. two-decade-long nation-building and reconstruction efforts in Afghanistan following the 9/11 attacks ended with the collapse of the Afghan state and a swift Taliban takeover in 2021. This research attempts to comprehend the systemic challenges that the U.S. faced in the process of nation-building, arguing that a combination of strategic, political, socio-cultural, security, economic, and regional factors led to an intractable quagmire. The thesis adopts a mixed-methods analysis to understand the constraints the U.S. faced, revealing that ethnic fragmentation, endemic corruption, and imposition of the Western governance model conflicted with the tribal socio-political landscape, eroding public trust and legitimacy. The Afghanistan experience underscores the limits of nation-building through foreign intervention in deeply divided societies., when the local agencies, socio-cultural dynamics, historical contexts, and regional factors are ignored. Rathe future interventions should be based on the consensus of local people, ensuring public trust, legitimacy, and participation.Extension Studie
Statistical Estimation of Circadian Time Using Gene Expression Data
No full textThis dissertation develops statistical methods and evaluation standards for estimating circadian time using high-throughput gene expression data. The first paper introduces an alternating weighted least squares framework that robustly infers circadian time, with strong generalization across tissues and platforms. The second paper extends this framework by incorporating batch adjustment through low-rank latent factors, yielding accurate performance on both simulated and real batch-confounded data. The third paper introduces a unified benchmarking framework that standardizes preprocessing, choice of assessment, and performance metrics, and evaluates a comprehensive selection of circadian time estimation algorithms across diverse contexts. Together, these studies both establish a comprehensive benchmarking approach for circadian time inference and demonstrate a modeling strategy that is robust, transferable, and state-of-the-art across real and simulated settings.Biostatistic
Align. Activate. Agitate: Designing a Professional Learning Network for Community and Systems Transformation
No full text“Change happens when a vast number of people come together and defend a vision of the future they’d like to see.”
-Angela Davis, Civil Rights Leader—
The Community Schools strategy is a national reform model with proven results. Yet still, its expansion and sustainability has been hindered for a myriad of reasons, including: lack of awareness, systemic capacity gaps, fragmented implementation, and the lack of supportive legislation and funding. As the United Way of Massachusetts Bay (UWMB), a credible intermediary with a 90-year track record of social impact, joined the movement to expand the Community Schools strategy locally while mobilizing Massachusetts Coalition for Community Schools, the central question was: What role might they play in supporting learning to ground this school improvement reform strategy across the state? .
This capstone proposes three strategic dispositions for intermediaries — Align, Activate, Agitate — and explores the catalytic power at the intersection of professional learning and networks to transform local practice while creating systems change. Grounded in research on effective networks, professional development, intermediary organizations, Mark Moore’s strategic triangle, and my experience as a principal and school district administrator, I designed the Aligned Regional Competencies (ARC) of Learning and Leadership for Community Schools Professionals, a conceptual blueprint for building a Professional Learning Network (PLN) infrastructure. Aligning with the three stages of Community Schools development the ARC guided the PLN’s sequence, coherence, and learning design. This capstone examines these efforts, including the launch and learning from a PLN pilot, and concludes with implications for my own leadership, UWMB’s role as an intermediary, and the sector at large.
Keywords: Professional Learning Network, intermediary, Community Schools strategy, liberatory leadershipEducatio
AP® STEM Student Assessment of ChatGPT Prompt Responses
No full textThis thesis explores the current accuracy of generative AI ChatGPT responses to Advanced Placement® (AP®) free response and multiple-choice questions found in high school courses covering AP® Physics 1 and AP® Calculus AB. Moreover, this thesis compares how high school students evaluate ChatGPT responses to algebra, precalculus, and calculus concepts found within these high school courses at participating high schools in the DFW area of Texas. In general, studies on generative AI use within STEM high school classrooms across the United States is limited. Current literature suggests that generative AI programs like ChatGPT have the potential to supplement classroom instruction by providing personalized assistance and immediate access to subject-specific information; however, there is a noticeable gap in understanding how high school AP® students perceive and interact with AI-generated responses, particularly in relation to accuracy and effectiveness as a study aid. Based on a literature review undertaken as a part of this thesis, a mixed-methods study was developed focusing on the perceptions of high school students interacting with ChatGPT written responses to AP®-style free response questions. The results of this thesis study show that while ChatGPT can offer detailed explanations and improve student understanding of complex topics, its generated responses can lack mathematical accuracy. Students generally viewed ChatGPT as a useful educational resource but often struggled to distinguish between AI-generated responses and official solutions provided by College Board®. Lower-performing students were more likely to overestimate the accuracy and completeness of ChatGPT’s outputs, potentially due to limited subject matter understanding. This study highlights the importance of developing high school students’ critical evaluation skills and suggests that integrating educational AI like ChatGPT into the classroom requires careful consideration of generative AI limitations and potential impact on learning outcomes
Exploring 2D Quantum and Acoustic Systems Using Scanning Probes
No full textThe world of quantum materials is made rich by the coexistence of many, many interacting electrons, giving rise to complex and fascinating phases of matter such as topological superconductivity. Such emergent quantum phenomena are associated with small interaction energy scales, appearing only in specific materials at ultra low temperatures. In this thesis I will address two distinct pathways towards studying strongly correlated materials: 1) creating better instrumentation and 2) discovering new materials.
In order to study already existing quantum materials, and more specifically topological superconductors, I will present the design and construction of a mK-base temperature scanning probe microscope. This system is the first of its kind to support simultaneous scanning tunneling microscopy and optical detection pendulum atomic force microscopy at mK temperatures. Such a combination opens the door for the realization of my proposed topologically protected quantum logic operation in the topological superconductors.
An alternative approach is to discover new systems that are potential hosts for strongly interacting phenomena. Discovering new quantum systems can be laborious and expensive; however, the dispersion of electrons can accurately be mimicked by classical waves, such as sound. The ability to quickly and cheaply 3D print acoustic metamaterials allows for rapid iterations and the discovery of novel lattice geometries which can then be brought to the quantum regime. I will present the experimental measurement and simulation of macro-scale acoustic metamaterials to prototype new flat band lattices. Additionally, I will discuss the development of a novel platform for designing arbitrary dispersions of surface acoustic waves in piezoelectric crystals using metamaterials.Physic